You spent years being told the path was clear. Pick a lane. Study it. Master one thing. Get hired for that one thing.

After that, you spend the next decade proving you could do it fast enough, cheap enough, and quietly enough to keep your seat.

Now that path is gone. Not because AI took it. Because it was always too narrow to be worth walking.

Today, a new generation of workers is figuring this out faster than anyone expected. Replit CEO Amjad Masad, freshly featured in Forbes after building his company to a $3 billion valuation, put a name to what he’s watching happen in real time:

> **_Agentmaxxing._**
> 
> ![Source: @TBPN on X](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/9bd484b2e2a44b388d94b58a2a243e6469dc5fd86ce2e05e352e42a66c6a0085.avif "Source: @TBPN on X")
> 
> And if you’re young and you’re paying attention, this is the most encouraging thing you’ll read all week.

## **What Agentmaxxing Actually Means**

If you have not come across the term yet, _agentmaxxing_ is exactly what it sounds like.

It is the practice of deliberately and systematically building out a personal stack of AI agents to handle as much of your workload as possible, and then pushing that stack as far as it will go.

Where someone else might spend three hours on a research task, an agentmaxxer has an agent running it in the background while they work on something else.

Where someone else writes a first draft, an agentmaxxer has already generated five versions, evaluated them against each other, and is editing the best one.

Where someone else attends a meeting and takes notes by hand, an _agentmaxxer_ has a transcript, a summary, and a list of action items waiting in their inbox before they have closed their laptop.

It is not about being lazy. It is about multiplying what one person can actually output in a day.

The people doing this well are not gaming the system. They are using the system to do what ambitious people have always done: **find every possible edge, and press it.**

@[youtube](https://www.youtube.com/watch?v=LmOooa1YB04)

## **The Fearmongering Misses the Point**

![Photo by Nathan Kuczmarski on Unsplash](https://miro.medium.com/v2/resize:fit:1400/0*HPmdjOhPoFiMuI9k "Photo by Nathan Kuczmarski on Unsplash")

If you’ve scrolled your feed lately, you know the dominant story about AI and young workers.

Entry-level jobs are shrinking. Graduates can’t get interviews. The robots are coming for junior roles first.

There’s enough truth in that framing to make it stick. Some entry-level work is changing. Some roles that existed five years ago look different today.

But the doom narrative has a blind spot, and it is a significant one.

It treats capability as a fixed competition between humans and machines, where every task AI can do is a task humans lose. That framing misses the more important question:

> **_What does a human become capable of when they have AI working alongside them?_**

Masad’s observation about _agentmaxxing_ points directly at this. The young people Replit wants to hire are not the ones who have accepted that AI will outperform them on tasks. They are the ones who figured out that using AI well is itself a high-leverage skill, one that most experienced professionals are still fumbling through.

The new constraint isn’t your degree or your years of experience. It’s about how ambitious you are, how generative you are, how creative you are, and how well you use the tools in front of you.

Those are not things you need permission to develop. You don’t need a senior title before you’re allowed to be ambitious. You don’t need ten years of experience to be creative with AI. The tools are available right now, and the people learning to use them well are compressing what used to be five-year career trajectories into eighteen months.

That’s what _agentmaxxing_ looks like in practice.

## **What This Actually Asks of You**

It’s easy to read “golden era” and hear hype. So be precise about what this moment actually requires.

It requires you to stop waiting for a job description that matches your degree and start building things before anyone asks you to.

It requires you to treat AI agents not as a crutch but as infrastructure, the same way earlier generations treated spreadsheets or search engines.

It requires you to get comfortable sitting at the intersection of disciplines that used to stay separate.

Design a little. Write a little. Ship a little. Then use agents to handle the mechanics while you move on to the next thing.

The people doing this well aren’t geniuses. They’re just not afraid of the tools.

## **The Optimism is Earned**

![Photo by Arno Senoner on Unsplash](https://miro.medium.com/v2/resize:fit:1400/0*SROjx3vk894rJThc "Photo by Arno Senoner on Unsplash")

There’s a version of “AI is exciting” that’s empty. It’s the kind that shows up in conference keynotes and LinkedIn posts from people who have nothing at stake.

This is not that.

Amjad Masad built a product that sits at the exact intersection of coding and accessibility. He watches new grads walk in and outperform people with far more experience, not because the new grads know more, but because they move differently. They don’t carry the assumption that one skill is enough. They reach for the tools, stack them, and ship.

He’s not speculating about what’s possible. He’s recruiting it.

The doom and gloom narrative about AI and young workers treats capability as fixed. It assumes that if your narrow skill gets automated, you’re done. But capability was never the thing that mattered most. It was always about how much you could get done, how fast, and how well.

AI just made “how much you can get done” a much larger number for anyone willing to find out.

You’re not competing against AI. You’re not competing against experience. You’re competing against the version of yourself that’s still waiting for permission to start.

**Agentmaxx**. The era is genuinely golden, but only for the ones who grab it.

* * *

_Speaking of tools that help you move faster:_ [_VideoTranslatorAI’s_](https://agent.videotranslator.ai/) _meeting agent transcribes, interprets, and summarises your meetings in real time, so you walk out with clarity instead of a page of notes you’ll never reread._

_Worth a look if you’re serious about agentmaxxing your own workflow._

Agentmaxxing Can Be Your Best Career Move This Decade

Agentmaxxing Can Be Your Best Career Move This Decade - Tat Banerjee

I was scrolling through Twitter before heading to bed when a tweet caught my eye, and that I just can’t shake off:

![@RaminNasibov](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/c003481a35e63063a1a591aae6faa5c166b86861cc88c3625d52ee18ae88e5bc.png "@RaminNasibov")

Source: [@RaminNasibov](https://x.com/RaminNasibov/status/2021176941819170973) on X

My gut answered before my brain caught up.

Yes. It’s the people. It’s always been the people.

We’ve spent years building a boogeyman out of algorithms and neural networks. Headlines scream about AI taking jobs, AI spreading lies, AI ending humanity.

But strip away the fear and look at what’s actually happening. In every case, a human made a choice. The AI just followed instructions.

We’re prosecuting the weapon while the criminal walks free.

## **A Tale of Two Wizards**

![Illustration of a good witch vs. wicked witch — created with Canva AI. ](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/60e77c846c3a26d92276fd1863478a1969a91777539ad2ebd8a384a324486133.png "Illustration of a good witch vs. wicked witch — created with Canva AI. ")

I always think of AI as a magic wand, a _tool_ of immense power that amplifies whatever the wielder intends.

Now imagine there are two wizards standing before identical wands, each crackling with the same raw power.

The first wizard raises her wand and heals. She mends broken bones, restores sight to the blind, conjures shields that protect villages from storms. When plague sweeps through a distant kingdom, she creates potions that cure thousands. Her magic flows outward, touching lives she’ll never meet, solving problems she’ll never see firsthand. The wand amplifies every generous impulse in her heart.

The second wizard raises her wand and destroys. She curses strangers, sows discord between neighbours, conjures illusions that deceive the vulnerable into ruin. When she sees power, she wants more. When she sees trust, she exploits it. The same wand that healed in one set of hands now corrupts in another.

**Same wand. Same magic. Different hearts.**

![Photo by Air Melody on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/3961c9974c1c02ba66e38d4b2b689c731aa81c7e641129adaa66cf54805fc5be.jpeg "Photo by Air Melody on Unsplash")

Now replace “wand” with “artificial intelligence.” Replace “wizard” with “builder.”

The metaphor collapses into reality. Same underlying technology. Same machine learning models. Same artificial intelligence.

The AI didn’t decide which path to take. The humans did.

## **The Good Wizards Among Us**

![Photo by Harpreet Singh on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/4416d6572083e84bf3ef458e8df21ababf38c2eccf47fbdd01aa8697e048e6ae.jpeg "Photo by Harpreet Singh on Unsplash")

That grammar checker suggesting clearer phrasing for your important email? AI making your communication better.

The recommendation that led you to your favourite song last year? AI understanding something about you that even you couldn’t articulate.

The fraud detection that blocked a suspicious transaction before someone emptied your bank account? AI protecting you while you slept.

Medical imaging analysis now catches tumours that human eyes miss. Not sometimes. Regularly. Thousands of people alive today who would have received their diagnosis too late.

Agricultural AI helps farmers in developing nations optimise water usage during droughts. Children eat because machine learning analysed satellite imagery and soil samples.

Accessibility tools powered by AI let blind people “see” photos their friends share, describe scenes in videos, navigate streets independently.

This is the technology being cast as humanity’s great threat.

## **The Dark Wizards are Real Too**

![Photo by JOE Planas on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/21eb3ac050eea08e904e63b8c7008a17b67ff0aeb94c9ed7fdc722fba4284ed5.jpeg "Photo by JOE Planas on Unsplash")

I won’t pretend the dark side doesn’t exist. It absolutely does.

Voice cloning has become terrifyingly accurate. Scammers need mere seconds of audio to replicate someone’s voice convincingly.

Parents have received ransom calls from their “kidnapped” children. The children were fine, sitting in school. But those minutes of terror were real.

Misinformation now generates itself. AI creates fake news articles, fake expert quotes, fake evidence for claims that would crumble under any scrutiny.

People believe it because it looks legitimate. Democracy suffers when truth becomes indistinguishable from fabrication.

Job displacement isn’t hypothetical anymore. Companies eliminate positions that AI can do cheaper. Workers with decades of experience find themselves competing against systems that don’t need sleep, benefits, or dignity.

And yes, weapons. Autonomous systems that could theoretically select and engage targets without human decision. The technology exists. The ethical framework for deploying it does not.

But here’s what I need you to notice: **every single one of these harms required a human decision.**

_Someone chose to use voice cloning for scams instead of helping stroke survivors speak again._  
_Someone chose to generate misinformation instead of educational content._  
_Someone chose to eliminate jobs without transition support._  
_Someone chose to develop lethal autonomy instead of search-and-rescue drones._

**Remove the malicious choice, and the technology becomes neutral or even beneficial.**

## **The Question We Should Actually Ask**

![Photo by Abu Saeid on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/996189cc6bcd4d62ca320914dbe9c60d3dc347a4e0947e4e3d5227bc3823d649.jpeg "Photo by Abu Saeid on Unsplash")

This brings us to the uncomfortable part.

If AI is just a tool, and tools depend on who wields them, then the problem we face isn’t technological. It’s human. It always has been.

We don’t have an AI crisis. We have an accountability crisis.

As someone who builds AI tools, I ask myself some questions before every feature or capability:

**_What’s the worst this could enable?   
Who might misuse this?   
Is the potential good worth the potential harm?_**

Sometimes the answer is no. And that’s the point.

The reflection isn’t about whether AI is inherently good or evil. It’s neutral. The reflection is about whether we, as builders and users, have the wisdom to wield it responsibly.

We don’t ban cars because drunk drivers kill people. We create laws, enforce consequences, and trust that most humans will drive responsibly.

We don’t prohibit kitchen knives because they can become weapons. We hold the attacker accountable, not the cutlery.

Why do we treat AI differently?

## **Stop Blaming the Mirror**

![Photo by Михаил Секацкий on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/d7687e1a12b249feb779906454da35f5f63fe68141d4b655a09df0b397ff77dd.jpeg "Photo by Михаил Секацкий on Unsplash")

Here’s my take.

> “AI scares us because it shows us ourselves.”

When we see AI generating misinformation, we’re really seeing human appetite for lies that confirm our biases.

When we see AI enabling surveillance, we’re witnessing human hunger for control over others.

When we see AI automating jobs away, we’re confronting human systems that value profit over people.

AI didn’t create these impulses. It amplified what already existed within us.

That’s uncomfortable. It’s much easier to point at the technology and say, “That’s the villain.” But comfort doesn’t solve problems. Honesty does.

The fear isn’t actually about artificial intelligence. It’s about human nature armed with increasingly powerful tools.

## **Where Do We Go From Here?**

![Photo by Vitaly Gariev on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/869c7bd6838942d7c44bebf8eba6fde579040f90e4d2a36a8dd24fb826fb8a3b.jpeg "Photo by Vitaly Gariev on Unsplash")

So what do we do with this realisation?

**First**, we stop the lazy narrative. “AI is dangerous” is incomplete. “AI in malicious hands is dangerous” tells the full story. Language matters. How we frame threats shapes how we address them.

**Second**, we regulate the wizards, not just the wands. Laws that punish deepfake creators more harshly than the platforms hosting them. Policies that hold scammers accountable rather than just blocking their tools. Frameworks that ensure human oversight in high-stakes AI applications.

**Third**, we build responsibly. Those of us creating AI tools must ask the hard questions before shipping features. We must design with misuse in mind. We must sometimes choose not to build something, even when we can.

**Fourth**, we educate. When people understand how AI actually works, they fear it less irrationally and guard against its misuse more effectively. Demystification is protection.

And **finally**, we remember that this isn’t new. Every powerful technology in human history has been used for both miracles and atrocities. Fire warmed our ancestors and burned their enemies. The printing press spread enlightenment and propaganda. The internet connected humanity and enabled its worst corners.

AI is simply the latest chapter in humanity’s oldest story: powerful tools amplifying whoever holds them.

The wand has never been evil. The wand has never been good.

The wand simply is.

What matters, what has always mattered, is the heart of the wizard who picks it up.

So the next time someone asks whether we should fear AI, I’ll give them the same answer:

> **Fear the human who wants to harm you with it. Celebrate the human who wants to help you with it. And if you ever hold that wand yourself, choose carefully what you conjure.**

The spell is yours to cast.

## Read more:

*   [Should You Still Learn to Code in 2026?](https://videotranslator.ai/blog/should-you-still-learn-to-code-in-2026)
    
*   [95% of AI Pilots Fail. Voice AI Explains Why.](https://videotranslator.ai/blog/95-percent-ai-pilots-fail-voice-ai-explains-why)
    
*   ["Yes, Okay, Thank You" and Your Child Just Failed Another Grade](https://videotranslator.ai/blog/yes-okay-thank-you-and-your-child-just-failed-another-grade)

We Don't Have an AI Crisis. We Have an Accountability Crisis.

Read We Don't Have an AI Crisis. We Have an Accountability Crisis. and explore practical insights from VideoTranslatorAI on multilingual communication, interpretation, and AI-supported workflows.

The most powerful artificial intelligence companies on Earth are hiring for soft skills. They’re advocating for humanities degrees. They’re telling people that creativity matters more than coding.

If this sounds backwards, you’re not alone. But when the architects of AI unanimously point toward human capabilities as the skills of the future, it’s worth paying attention.

In a recent [OpenAI town hall](https://www.youtube.com/watch?v=Wpxv-8nG8ec&t=2348s), Sam Altman was asked what skills people should develop as AI transforms every industry. His answer caught many off guard.

> _“Become high agency,” he said. “Get good at generating ideas. Be very resilient. Be very adaptable to a rapidly changing world. These are going to matter more than any specific skill.”_

Not coding. Not prompt engineering. Not technical expertise.

**Agency. Ideas. Resilience. Adaptability.**

This advice becomes even more striking when you realise it’s coming from multiple leaders across the AI industry. From OpenAI to NVIDIA to Anthropic to Microsoft, the founders shaping our technological future are pointing toward the same unexpected conclusion.

## **The Death of Raw Intelligence as Currency**

For decades, we’ve organised education and careers around a simple premise: accumulate knowledge, demonstrate expertise, climb the ladder. But Altman argues this model is becoming obsolete.

“There will be a kind of ability we still really value, but it will not be raw, intellectual horsepower,” he explained in a [podcast](https://www.ted.com/talks/rethinking_with_adam_grant_sam_altman_on_the_future_of_ai_and_humanity) with Adam Grant.

The new premium ability? **Learning how to ask great questions.**

Think about that shift. In a world where AI can access and synthesise virtually all human knowledge in seconds, memorising facts or knowing where to find them loses its value.

What remains valuable is the uniquely human capacity to frame problems, to ask questions nobody else is asking, to see connections others miss.

Altman put it bluntly when reflecting on future generations: “My kid is never gonna grow up being smarter than AI. And that’ll be natural.”

The question isn’t whether AI will surpass human intelligence in specific domains. It already has. The question is what humans will do that AI cannot.

## **Domain Expertise Meets AI Collaboration**

![Photo by National Institute of Allergy and Infectious Diseases on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/f6475086542519e369a0e47959a314d20a01ef0996675cc4f17ec4279918d7ee.jpeg "Photo by National Institute of Allergy and Infectious Diseases on Unsplash")

At the [Cisco AI Summit](https://www.youtube.com/watch?v=6fbyiPRhMSs) held earlier this month, NVIDIA CEO Jensen Huang offered a complementary perspective.

The man whose company powers most of the world’s AI infrastructure thinks that success in the AI era is no longer about coding, which, he believes, has become a commodity.

_“All of you have something of great value, which is_ **_domain expertise_**_, to understand the customer, understand the problem. And that is the ultimate value,”_ Huang emphasised.

This reframes the entire conversation. Rather than viewing AI as something to master technically, Huang sees it as something to **collaborate** with.

Your unique domain knowledge, whether in medicine, law, education, agriculture or any other field, becomes more valuable when amplified by AI.

Huang also gives us a specific recommendation: treat AI like your smartest colleague.

Learn to work alongside it, to prompt it effectively, to blend your expertise with its capabilities. _“It is vital that we upskill everyone, and the upskilling process, I believe, will be delightful. Surprising,”_ as he stated in last year’s [World Government Summit.](https://www.youtube.com/watch?v=8Pm2xEViNIo&t=430s)

The smartest people, according to Huang, aren’t necessarily the most technical, but those who are able to see around corners.

Foresight, intuition, strategic thinking. These human qualities become differentiators precisely because AI excels at processing what already exists, not imagining what could be.

## **The Humanities Revival**

![Photo by Christina @ wocintechchat.com M on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/3f893f8431d7c73ac2f6ce73a6846579e04f292e11e16338295ae0a7481752fe.jpeg "Photo by Christina @ wocintechchat.com M on Unsplash")

Perhaps the most counterintuitive advice comes from [Daniela Amodei,](https://finance.yahoo.com/news/anthropic-cofounder-says-studying-humanities-171902740.html?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAAMuZgLyagkGr8H1_x04Wt_wLuBIH9k0BO6l2SDHuD0nDoNn9dVOsxTPiNjfmDk6bFLB27DLrHOmNe1htwfnebZN_dMXNRR2sgl4xIrMkAhGffpfHcLq_KWTg5kYuIOkWkgfCavKXX-8-q3RsT7RdHgH3SJOJG1ugIegXaMc81Jy7) co-founder and president of Anthropic, the company behind Claude AI.

In a world racing to build artificial general intelligence, Amodei argues that studying the humanities will be **_“more important than ever.”_**

When Anthropic hires, they actively seek soft skills: communication, ethical reasoning, the ability to understand human context and nuance.

Why? Because AI excels at processing information but struggles with human context, ethical reasoning and nuanced communication.

Technical skills can be automated or augmented. But understanding human motivation, navigating complex social dynamics, exercising moral judgment in ambiguous situations: these capabilities remain stubbornly human.

The humanities teach exactly these skills. Literature develops empathy. Philosophy sharpens ethical reasoning. History provides pattern recognition across human behaviour.

In an age of artificial intelligence, these “soft” skills may prove to be the hardest to replace.

## **Three Adaptation Strategies**

![Photo by Simon Ray on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/b3da73d60718707ae756354cdcf67bce2b27a5115096725f24b257067cf8dc1d.jpeg "Photo by Simon Ray on Unsplash")

Synthesising advice from AI’s architects, three strategies emerge in my mind:

### **Strategy 1: Develop meta-skills over specific skills**

Specific skills become outdated. Meta-skills, the ability to learn, adapt and transfer knowledge, remain valuable regardless of what changes.

Altman’s emphasis on agency and resilience reflects this. These aren’t skills you deploy; they’re capacities that enable you to develop whatever skills become necessary.

### **Strategy 2: Go deep, then collaborate**

Huang’s advice suggests a two-step process. First, develop genuine expertise in a domain you care about. Then, learn to collaborate with AI to amplify that expertise.

Shallow knowledge of many things may matter less than deep understanding of something specific, combined with the ability to leverage AI for everything else.

### **Strategy 3: Invest in irreplaceable human qualities**

Communication, empathy, ethical reasoning, creativity, judgment: these capabilities remain stubbornly human. As technical tasks become automated, they become comparatively more valuable.

Amodei’s advocacy for humanities education reflects this. The “soft” skills may be the hardest to replicate, making them the safest long-term investment.

## **A Different Kind of Race**

![Photo by Enchanted Tools on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/d164d7512017ecdb6f39cc3db1f4f3639d9705ea825df838863de207d788c1e9.jpeg "Photo by Enchanted Tools on Unsplash")

There’s a race underway, but it may not be the race we imagined.

It’s not humans versus machines. The founders building AI don’t describe competition; they describe collaboration.

It’s not technical skills versus soft skills. Both matter, but soft skills may have more lasting value.

The real race is against stagnation. Against the temptation to assume current skills will remain sufficient. Against the comfort of expertise that resists change.

## **Moving Forward**

The path forward isn’t about predicting exactly which skills will matter in 2030 or 2040. Predictions that specific are impossible.

It’s about developing the capacity to adapt regardless of what emerges. Agency. Resilience. Continuous learning. Deep expertise combined with collaborative flexibility. Human capabilities that machines cannot replicate.

These aren’t things you learn from a textbook. They’re capabilities you develop by doing hard things, failing, learning, and trying again.

Practice asking great questions. Not just good questions, but the questions that reveal hidden assumptions, clarify confusion, and open new possibilities.

The founders building AI are offering a warning and an invitation. The warning: change is coming faster than most people expect. The invitation: the future favours those who develop distinctly human strengths.

The question isn’t whether you can keep up with AI.

**_It’s whether you can keep growing alongside it._**

## **Read more:**

*   [**The Teletubbies' Vacuum is Better Engineering Than Tesla's Optimus**](https://videotranslator.ai/blog/teletubbies-vacuum-is-better-engineering-than-tesla-optimus)
    
*   [**"Yes, Okay, Thank You" and Your Child Just Failed Another Grade**](https://videotranslator.ai/blog/yes-okay-thank-you-and-your-child-just-failed-another-grade)
    
*   [**95% of AI Pilots Fail. Voice AI Explains Why.**](https://videotranslator.ai/blog/95-percent-ai-pilots-fail-voice-ai-explains-why)

Here’s what OpenAI, NVIDIA, and Anthropic say you need to survive the age of AI

Should You Still Learn to Code in 2026?

A company just launched an AI pilot. The demo was impressive. The executives are excited. The budget is approved.

Six months later, it’s quietly shelved. No measurable impact. No adoption. No one wants to talk about it.

If this sounds familiar, you’re not alone. An MIT study analysing over 300 enterprise AI initiatives found that [95%](https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/) of AI pilots fail to deliver any measurable return on investment.

The number is almost too brutal to believe. But the problem isn’t the technology. It’s how organisations adopt it.

And nothing reveals this gap more brutally than **_voice AI_**.

Here’s my brief explanation.

## **Why Voice AI Is the Hardest Test**

![Photo by Egor Komarov on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/b7effc97803e13b6fe19da04cadfa8611956b37572170909533dc855259a1608.jpeg "Photo by Egor Komarov on Unsplash")

Text-based AI has a crucial advantage: forgiveness.

When ChatGPT makes a mistake in an email draft, you can edit it. When a document summarisation tool misses context, you can add it manually. Text AI operates in a forgiving environment where humans can catch errors before they cause damage.

Voice AI doesn’t get that luxury.

In live conversations, mistakes happen in real time. A second of lag during a client call. A mistranslated phrase in a medical consultation. The wrong tone in a customer service interaction. These errors don’t just sit in a draft waiting for correction. They immediately erode trust.

That’s why voice AI is the real test of organisational readiness. It forces companies to confront the hard truths they can ignore with text AI: brittle workflows, poor integration, misaligned expectations, and lack of proper governance.

## **What Voice Reveals**

![Photo by Bluestonex on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/3104ec564e4bb5abb64c6f85adce413e062a1a72286eee89b26fecab811a4da6.jpeg "Photo by Bluestonex on Unsplash")

Voice AI acts like a stress test for organisational infrastructure. When it fails, the failure almost never traces back to the model.

It traces back to workflows that were never designed for real-time accountability:

**Compliance processes** built on institutional knowledge that nobody documented. The AI can’t follow rules that only exist in someone’s head.

**Sales playbooks** that vary by rep, by region, by whoever happened to train the new hire. The AI can’t support a process that doesn’t exist consistently.

**Meeting cultures** where decisions are made but never captured, where action items are announced but never tracked, where “we discussed this” becomes an alibi instead of a commitment.

Text-based tools let these problems persist. Voice AI forces them into the open.

## **What Successful Adoption Actually Looks Like**

![Photo by Jo Lin on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/483428a6ab699c66287d95f0d32ba43606ab1f8b9edc571f816697d9c921eb84.jpeg "Photo by Jo Lin on Unsplash")

The companies that make voice AI work don’t have better technology. They have better organisational clarity.

They embed AI into workflows rather than running it alongside them:

**Customer support** teams use real-time transcription and multilingual interpretation to serve global clients without manual translation delays. The conversation stays fluid. Trust compounds.

**Meeting-heavy organisations** capture decisions, action items, and commitments as they happen — not as someone reconstructs them days later. Accountability becomes automatic, not aspirational.

**Compliance functions** generate audit-ready documentation without the 10+ hours of weekly manual reporting that burns out staff and introduces human error.

The pattern is consistent: voice AI succeeds when it’s designed into how people already work, not added on top.

## **The Generational Tension You’re Probably Ignoring**

![Photo by Eliott Reyna on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/d0dbaa16672df8cab2cdb72df41d555e8056219332915b4ef8a168eada9d0e04.jpeg "Photo by Eliott Reyna on Unsplash")

There’s a friction point most organisations underestimate: younger workers expect AI to reduce friction, while senior professionals often experience it as surveillance.

Gen Z employees treat AI assistance like autocomplete — natural, helpful, invisible when it works. They don’t feel monitored. They feel supported.

Experienced professionals who built their careers on judgment and expertise can feel differently. A machine transcribing their words in real-time can read like distrust. An AI summarising their meeting can feel like their assessment wasn’t good enough.

Successful voice AI adoption addresses this head-on. The framing matters: augmentation, not replacement. Enhancement of human judgment, not substitution for it.

When both groups trust the tool, adoption accelerates. When they don’t, it stalls — no matter how good the technology is.

## **Building for Real-Time Trust**

At [VideoTranslatorAI](https://videotranslator.ai/), we built a meeting assistant that transcribes, interprets, and summarises conversations in real time because we watched organisations fail to capture what actually happens when people talk.

The pattern was predictable. Meeting ends. Decisions get reconstructed from memory.

Action items turn into “I thought you were handling that.” Multilingual conversations lose nuance somewhere between the spoken word and the follow-up email.

Our agent works inside the conversation, not after it. Every word gets captured accurately. Every participant stays included, regardless of language. Every follow-up has clear documentation.

This isn’t about recording calls. It’s about building organisational memory that people actually trust.

![VideoTranslatorAI’s real-time interpreter](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/722aaaea7b6fd89c483167339c915daba98848cb5ed5bfa4386d81201d88718f.gif "VideoTranslatorAI’s real-time interpreter")

[VideoTranslatorAI’s](https://agent.videotranslator.ai) real-time interpreter

## **The Test Worth Taking**

Voice AI is a stress test for organisational readiness.

Can your compliance processes survive automatic documentation? Can your teams operate with full transparency into what was actually said? Can your workflows handle the accountability that comes with real-time capture?

If yes, voice AI multiplies your capabilities.

If no, you’ve just diagnosed exactly what needs to change.

Either outcome is valuable. But only one of them stays comfortable.

The 95% of failed pilots didn’t fail because AI isn’t ready.

They failed because organisations weren’t.

The question is whether yours is different.

## Read more

*   "[Yes, Okay, Thank You" and Your Child Just Failed Another Grade](https://videotranslator.ai/blog/yes-okay-thank-you-and-your-child-just-failed-another-grade/)
    
*   [The Teletubbies' Vacuum is Better Engineering Than Tesla's Optimus](https://videotranslator.ai/blog/teletubbies-vacuum-is-better-engineering-than-tesla-optimus/)
    
*   [Build in Public Hurts Startups. Do It Anyway.](https://videotranslator.ai/blog/build-in-public-hurts-startups-do-it-anyway/)

95% of AI Pilots Fail. Voice AI Explains Why.

Read 95% of AI Pilots Fail. Voice AI Explains Why. and explore practical insights from VideoTranslatorAI on multilingual communication, interpretation, and AI-supported workflows.

A teacher finishes explaining a child's reading struggles. The parent across the table nods politely, smiles, and says "Yes, okay." 

But something is wrong. The teacher can see it in the parent's eyes: confusion, uncertainty, the desperate attempt to follow along.

The meeting ends. Nothing changes. The child continues to fall behind.

This is the daily reality for millions of immigrant families worldwide. Parents who are deeply invested in their children's education but find themselves locked out of the conversations that matter most. 

They miss crucial information about academic struggles. They can't advocate for special services their children need. They sit in parent-teacher meetings nodding politely, understanding nothing.

If this is your experience, **_you're not alone. And it's not your fault._**

## **Invisible Wall for Immigrant Parents**

![Photo by Jhon David on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/3b36d748883c221309623b06d92250abb98a790c6d515e415787412e851e86df.jpeg "Photo by Jhon David on Unsplash")

Yesterday, I was doing some research for my upcoming app demo for my education sector client. Until I found a statistic that stopped me cold. 

**_“During 2023-2024 school year, around_** [**_79%_**](https://www.languageline.com/blog/study-school-involvement-drops-dramatically-for-non-english-speaking-parents) **_of Spanish-speaking parents who try to participate in school activities report that language barriers make it difficult.”_**

Let that sink in. Nearly four out of five parents who _want_ to be involved in their child's education are hitting a wall before they even start.

Even with the advancement of technology, the gap is widening, not shrinking. In 1999, 69% of non-English-speaking parents attended general school meetings. By 2024, that number had dropped to just 55%. Meanwhile, English-speaking parent attendance rose to 87%.

That's a 32-percentage-point gap. And behind every point is a child whose parent couldn't advocate for them.

## **A Real Story from Philadelphia**

Right after stumbling upon that heartbreaking statistic, I came across an article from 2025. It was a story from [Zulma Guzmán](https://www.chalkbeat.org/philadelphia/2025/07/28/latino-families-struggle-with-translation-communication-in-school-system/), an immigrant from El Salvador who now calls Philadelphia home. 

Zulma’s experience perfectly echoes the statistic: the frustration felt by Spanish-speaking parents as they navigate a school system that often feels designed to exclude them.

![Source: Chalkbeat](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/45b6f5753746d6e0ab34411f8c72b30ed778cbbf85eac89b747294002460d104.jpeg "Source: Chalkbeat")

Parents miss information about the academic interventions their children need. They don't understand the health services available through schools. They can't decode report cards or respond to urgent communications about their child's behaviour.

On the other hand, Philadelphia's Latino student population has increased by [**51%**](https://www.chalkbeat.org/philadelphia/2025/07/28/latino-families-struggle-with-translation-communication-in-school-system/) **since 2018**. That's remarkable growth. But the translation services haven't kept pace. And the children caught in the middle are paying the price.

_"We need more support,"_ Zulma says. 

Coming from someone who has witnessed this crisis up close, it's not a complaint. 

It's a plea.

## **Teachers Feel It Too**

![Photo by Vitaly Gariev on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/ec80c80600331ba2eae79d36ad9b1e88204062a24704f5d7b30ec4b62211d18f.jpeg "Photo by Vitaly Gariev on Unsplash")

This problem isn't just on one side of the desk.

**56% of teachers** in the US report being concerned about language barriers when communicating with ESL parents. 

They can see students struggling. They know what interventions would help. But they can't have the necessary conversations with the families who need to hear it most.

Consider what that means in practice. A teacher notices a student falling behind in reading. The standard approach would be to meet with parents, explain the situation, and develop a plan together. But if the parents speak limited English, that conversation becomes nearly impossible.

Some schools have bilingual staff. Some hire professional interpreters for important meetings. But these resources are expensive, inconsistent, and often unavailable when teachers need them most.

## **The Change We Can Make**

I've spent years building real-time translation technology. The applications I imagined were corporate: international business meetings, global team collaboration, conference interpretation.

Then I started hearing stories like Zulma's. I started reading the research about what happens when parents can't engage with schools. The outcomes are devastating.

In Australia, where I live now, more than 300 languages are spoken, and over one in five people speak a language other than English at home. Schools here face many of the same challenges as Latino parents in Philadelphia.

That’s when something clicked.

The technology I’d been building didn’t have to stop at translating corporate meetings. It could be used where understanding actually changes lives.

It could help a teacher explain to a parent why their child needs extra support in maths. It could help a parent ask questions about their child's progress. It could turn a polite, confused nod into a real conversation.

And I’m delighted to say I wasn’t wrong.

Recently, [VideoTranslatorAI](https://agent.videotranslator.ai) worked with an Australian school facing a delicate situation: a Korean Year 9 student wanted to attend an overnight camping trip for a friend’s birthday.

Using our real-time multilingual video call, the school was able to have a full, unhurried conversation with the parents. Every risk was explained. Every question was answered. Consent wasn’t just given. It was truly informed.

![VideoTranslatorAI multilingual video call platform featuring AI-generated faces. Real clients' faces are not displayed to protect their privacy.](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/7160abfd182046311402821ce5f5524748bd942dfb46779bb5b419be167165a2.png "VideoTranslatorAI multilingual video call platform featuring AI-generated faces. Real clients' faces are not displayed to protect their privacy.")

The student attended the trip. The school stayed legally protected. The parents felt respected and included in the decision.

Read the full story about this: [**What Happens When Consent Gets Lost in Translation**](https://videotranslator.ai/blog/what-happens-when-consent-gets-lost-in-translation)

## **An Invitation**

The tools exist. The research supports their impact. The need is urgent and growing.

This isn't about replacing human connection with technology. It's about enabling human connection that language barriers currently prevent. 

An interpreter tool doesn't substitute for a caring teacher or an engaged parent. It lets them actually work together.

Zulma and the parents she advocates for aren't asking to be coddled. They're asking to participate in a system that affects their children's futures. They're asking for the same access that English-speaking parents take for granted.

We can close the 87-55 gap. Not by changing parents, but by changing the systems that exclude them.

If you're an educator, administrator, or parent navigating these challenges, I'd genuinely like to hear from you. What's working? What's failing? What would actually help?

This problem is too important to solve in isolation. It requires teachers, parents, and technologists working together.

This is a conversation worth having. And thanks to technology, it can finally happen in any language.

## Read more

*   [The Teletubbies' Vacuum is Better Engineering Than Tesla's Optimus](https://videotranslator.ai/blog/teletubbies-vacuum-is-better-engineering-than-tesla-optimus)
    
*   [Build in Public Hurts Startups. Do It Anyway.](https://videotranslator.ai/blog/build-in-public-hurts-startups-do-it-anyway)
    
*   [How to Get 30 Minutes Back After Every Meeting](https://videotranslator.ai/blog/how-to-get-30-minutes-back-after-every-meeting/)

"Yes, Okay, Thank You" and Your Child Just Failed Another Grade

Inside the silent crisis affecting millions of immigrant families

Something about Tesla Optimus actually makes my skin crawl.

It's not rational. The robot is impressive. Smooth movements, precise grip, balanced gait.

But every time I watch it in my feed, I get that familiar shudder. The _uncanny valley_ pulling me back.

First month of 2026 has randomly turned my Twitter into a humanoid robot showcase.

![XPENG's next gen humanoid robot, IRON](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/8527ad5bd1bb53065dcca74011b2ff31e9acfd3de923795de0ab970b2139ec61.png "XPENG's next gen humanoid robot, IRON  (Source: X, @TheHumanoidHub)")

[Figure 02](https://www.figure.ai/news/production-at-bmw) at BMW plants. [1X Neo](https://www.1x.tech/neo) entering homes. Chinese firms deploying hundreds of sanitation units. The message: **_this is the future._**

But I've spent weeks now trying to articulate why this trend leaves me cold. And I think I've finally worked it out.

We're building the wrong kind of "humanoid." 

## **Reasons Why Humanoid Design Makes No Sense**

![Photo by julien Tromeur on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/5984fe20d54b9c7c01de56d1c42499371bdb2aad11c5bdd5d5e993c988ae599a.jpg "Photo by julien Tromeur on Unsplash")

### 1\. Human Body isn't a Good Blueprint

I'm going to say something that sounds obvious once you hear it: the human body is fragile and wildly inefficient for most tasks.

Our spines ache. Our knees blow out. We get tired after a few hours of repetitive work. Evolution optimised us for survival on the African savanna, not for warehouse logistics or precision manufacturing.

_So why are we giving robots these same limitations?_

A robot with four arms could complete assembly tasks twice as fast as any humanoid. 

A wheeled base beats bipedal walking for stability and energy efficiency. 

We used to understand this intuitively. Remember those cartoons where robots had extra limbs and could transform? That was better engineering thinking than what billion-dollar companies are pursuing today.

Teletubbies’ noo-noo is better at vacuuming than a humanoid holding a vacuum. Full stop.

![The famous vacuum robot from the Teletubbies show](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/f0e74bfd5ef5d3040b4a1aed0351d0a65c569ad3bc7152898a0abff7d8020c03.gif "The famous vacuum robot from the Teletubbies show")

### 2\. Energy Inefficiency

Walking on two legs is one of the least efficient forms of locomotion. Wheels, tracks, and even quadrupedal movement are all more energy-efficient than bipedalism. 

Yet we're building robots that burn battery power maintaining balance whilst walking, a problem that wheeled robots solved decades ago.

Current humanoid robots run for approximately four hours on a single charge, largely because bipedal movement is so energy-intensive. We're engineering inefficiency directly into our most advanced machines.

### 3\. Structural Fragility

The humanoid form prioritises mobility over durability. Joints that move in multiple directions are inherently more fragile than fixed connections. Bipedal balance requires constant micro-adjustments that increase wear on components.

We're building robots that will need the same joint replacements and structural repairs that plague human bodies, when we could build sturdy, stable platforms that last decades without major maintenance.

@[youtube](https://www.youtube.com/watch?v=kMfcGfRO0R8)

### 4\. Uncanny Valley Problem

There's a psychological phenomenon where humanlike robots that aren't quite human enough trigger discomfort and revulsion. 

The more closely robots resemble humans without being indistinguishable, the more unsettling they become.

We're spending billions developing robots that make people uncomfortable when we could build obviously mechanical systems that people find aesthetically neutral or even appealing. 

Industrial robots don't trigger uncanny valley responses because they don't pretend to be human.

### 5\. Overengineering for Most Tasks

![Photo by Accuray on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/c3a9a381d15a9116863a5d90a0e26d8c009210a0ec153f48feb6181549d9a6f9.jpg "Photo by Accuray on Unsplash")

Most tasks robots need to perform don't require human form. Warehouse logistics, manufacturing, agriculture, cleaning, inspection, and maintenance are all better served by specialised designs.

The humanoid form is a jack-of-all-trades approach that makes every task slightly worse than it could be with purpose-built robotics. 

We're choosing versatility over excellence, and in the process, creating machines that excel at nothing.

## **The Humanoid Technology We Actually Need**

The real breakthrough won't be robots that look like us. It will be systems that understand us. 

At [VideoTranslatorAI](https://videotranslator.ai/), we’re building tool for cross-lingual communication, systems that can translate, transcribe, and summarise meetings in real time whilst preserving the subtle meanings that get lost in translation. 

That's the kind of "humanoid" capability that matters: understanding human communication well enough to bridge language and cultural gaps.

When I watch humanoid robots struggle to walk on a runway or fold laundry in ways that would be trivial for purpose-built machines, I see billions of dollars chasing the wrong goal.

We don't need robots that mimic our physical form. We need intelligent systems that complement our capabilities, handle tasks we're poor at, and integrate seamlessly into our workflows regardless of their physical appearance.

A meeting assistant that captures every point in a multilingual discussion is infinitely more valuable than a robot that can physically attend the meeting but understand nothing being said.

![VideoTranslatorAI’s real-time interpreter](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/d11428991e3c40270a93f7e793dfb6f3568b95946835d4fb891387aac9144555.gif "VideoTranslatorAI’s real-time interpreter")

## **The Path Forward**

I won't pretend humanoid robots have zero applications. If you need a robot to navigate a space literally built for human bodies, the form factor makes sense.

But the breakthrough that actually transforms how we work and communicate won't come from perfecting synthetic knees. It will come from AI that genuinely grasps human language, context, and emotional nuance.

That's the humanoid revolution worth waiting for.

Walking robots make good demos. The understanding ones will change everything.

## Read more

*   [Build in Public Hurts Startups. Do It Anyway.](https://videotranslator.ai/blog/build-in-public-hurts-startups-do-it-anyway/)
    
*   [How to Get 30 Minutes Back After Every Meeting](https://videotranslator.ai/blog/how-to-get-30-minutes-back-after-every-meeting/)
    
*   [What Happens When Consent Gets Lost in Translation](https://videotranslator.ai/blog/what-happens-when-consent-gets-lost-in-translation/)

The Teletubbies' Vacuum is Better Engineering Than Tesla's Optimus

The humanoid hype is engineering inefficiency into our most advanced machines

Nikita Bier knows how to build viral apps. Two acquisitions totalling over $30 million, advisor to Solana, and now Head of Product at X.

His track record speaks for itself. So when someone with his credentials warns founders about building in public, it's worth listening to.

In his recent X post (January 27th 2026), he argued that Build in Public is "a wrong move for startups" sparked genuine debate.

![Screenshot 2026-01-28 at 22.09.16.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/5a34cfd66c9d83515c7deb5f86ced0ec23cd36147a23811a125744cfaba4fe2e.webp)

Source: [X](https://x.com/nikitabier/status/2016186182628249791?s=20)

His case is worth taking seriously. But I think he's right about some things and wrong about others, and the distinction matters.

## **What Nikita Gets Right**

![Nikita Bier](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/9fd809427142d77df912b9b13da5569a54d110375a96c79d6eb3ab12f73ff007.webp)

Let's start with the valid concerns, because dismissing them entirely would be intellectually lazy.

Nikita argues that startups need room to make drastic changes. He's correct.

The path to product-market fit is rarely linear. You might start with a consumer app and end up building enterprise software. You might scrap entire features, rename the product, or pivot to a completely different market. That flexibility is essential.

He's also right that building in public can create psychological pressure. When you've publicly committed to a direction, pivoting feels harder. There's ego involved, and the friction of admitting you were wrong in front of an audience.

And yes, some founders do get distracted by the performance of building in public. They optimise for engagement instead of product quality. They spend more time crafting threads than talking to customers.

As someone who builds in public, I admit that these are real risks. Nikita isn't manufacturing problems out of nothing.

## **Where The Argument Breaks Down**

![Photo by BoliviaInteligente on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/3584c92467b669efab5fb393c3c5251c0be35ef99d5312ad7a4181e6fdeed486.webp)

Here's where I diverge from his conclusion.

Nikita's framework assumes startups have "**finite attention**" they need to protect.

This makes sense for established companies with existing audiences and brand equity to preserve. But for early-stage startups?

The average pre-seed founder isn't managing audience expectations. They're trying to get anyone to notice they exist. Their problem isn't attention _overload_. It's attention _scarcity_.

For every startup that confuses their audience with pivots, hundreds die in complete silence. They build something nobody hears about, launch to indifference, and quietly shut down.

The risk of obscurity dwarfs the risk of "narrative complexity."

## **The Attention Economy Works Differently for Unknowns**

![Photo by Melanie Deziel on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/ecb198499a6e51897f7c6cfd54279d1d085cf121a3e91e48b610b71868ccfddf.webp)

Nikita's advice implicitly assumes a model where attention is a battery: you start with a charge, and every public update depletes it. Better to conserve that energy for one big precision launch.

But for startups starting from zero, attention isn't a battery. It's a muscle. You build it through consistent exercise, not conservation.

Building in public isn't spending attention. It's generating it.

Every update, every behind-the-scenes moment, every transparent reflection is an opportunity to be discovered. Someone finds your post, checks your profile, gets intrigued, follows along. Three months later, they become an investor, a customer, or an advocate.

The compounding effect of consistent visibility is hard to replicate through any other means.

## **Strong Founders Already Know When to Ignore The Room**

![Photo by Phil Cln on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/2da3030691c49784574e2e29165decbe68ef402a48d0bd5e7bf302599f132ca6.webp)

Nikita worries that having an audience makes it _"difficult to make those changes that only you can understand."_

![Screenshot 2026-01-28 at 22.15.08.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/b08e0b53b7bc918c0dd6cd5e70621933a1ea381eed13c2ae4f34cfdedd8fb139.webp)

I'd push back gently here. Founders face pressure from all directions: investors, advisors, co-founders, early customers.

The pressure of internet followers is actually the mildest form of scrutiny you'll encounter.

Founders who can't make bold moves because strangers might be confused are going to struggle with far more consequential pressures down the line. The ability to gather input, then ignore it when necessary, is a core founder skill.

Building in public doesn't create that challenge. It just surfaces it earlier.

The best founders I know treat their audience as a sounding board, not a governing board. They share openly, collect signals, then make their own calls anyway.

## **Accountability isn't Always A Bug**

![Photo by Timon Studler on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/d473b24a650a875f424910be2c3594b68c4dbb137ed34474d6ccd16d3e0cb3df.webp)

Yes, pivoting is harder when people are watching. But consider whether that friction is always negative.

Building in public forces you to articulate your reasoning. When you pivot, you have to explain why, which often clarifies your own thinking.

It creates a natural check against the kind of aimless thrashing that kills startups: changing direction every few weeks because nothing was ever committed to publicly.

The discipline of explaining your decisions to an audience, even a small one, reveals whether a pivot is strategic or just panic. Sometimes the best thing an audience does is make you pause and ask:

_can I actually defend this?_

If you can't, maybe the decision needs more thought.

## **Early Adopters Beat Launch Day Crowds**

Nikita suggests building quietly, then launching with "precision" after achieving PMF.

But consider who shows up for a cold launch versus a warm one.

Strangers who discover your polished product have no context. They'll churn at the first friction point. They have no reason to give you the benefit of the doubt.

![Fail In Public.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/22972802f0d511c788e8f85a3d37a9616f6bebebb5494a4ac8e981c4e5d07d25.webp)

The people who followed your journey?

They watched you struggle with that one feature for months. They understand your vision because you've explained it repeatedly.

When they encounter bugs, they report them instead of leaving. They tell their friends because they feel invested in your success.

I'll take 500 engaged followers over 5,000 cold visitors every time.

## **The Internet Forgets Faster than You Think**

![Photo by ROBIN WORRALL on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/fa35748677376050a6a6b9ab780f632913cd334700c8bccb76a1846fc0d1f6a8.webp)

Nikita warns that narratives become "so complex that no audience can keep up."

In my experience, this concern is overblown. The internet has a short memory. Most people who discover you won't scroll back through months of posts. They'll see your current positioning and current product. Your past pivots are invisible to them.

And for the few who do follow your entire journey? They often become your biggest advocates. They love origin stories. They appreciate transparency.

Think about the startup legends we celebrate: [Airbnb](https://www.cnbc.com/2023/04/18/airbnb-ceo-says-he-wooed-first-investors-with-boxes-of-cereal.html) selling cereal boxes, [Slack](https://www.justanotherpm.com/blog/what-can-product-managers-learn-from-the-growth-of-slack#:~:text=The%20Origin%20of%20Slack,missing%20this%20age%2Dold%20game\)) starting as a video game, [Instagram](https://www.instagram.com/reels/DQeUMUPkz3g/) beginning as a cluttered check-in app.

The pivots aren't embarrassing footnotes. They're part of the mythology.

## **It's about Distribution, Not Just Feedback**

Nikita frames building in public primarily as a feedback mechanism. Established companies do that better, with larger user bases and proper research teams.

But for startups, feedback isn't the main value. Distribution is.

Every update is content. Content gets discovered, shared, and amplified. Building in public is marketing that costs nothing but time. It's how you attract co-founders, early employees, investors, and future customers without a budget.

Startups can't afford PR agencies or paid acquisition at scale. What they can afford is transparency. Building in public converts your daily work into a distribution engine.

## **The Real Trap (And It's Not What Nikita Describes)**

![Photo by Kelly Sikkema on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/a4fca202ef213cfb93b68a3b75c822401f1eb565e906990cb355e735704e75b6.webp)

If I'm being honest about the risks, the genuine danger isn't narrative confusion.

It's that building in public can become procrastination dressed up as strategy. Some founders spend more energy on update threads than on actual product work.

The dopamine hit of engagement replaces the harder work of customer conversations and shipping features.

That's a real trap. But it's a discipline problem, not an inherent flaw in the approach. The solution is self-awareness, not silence.

## **The Asymmetric Bet**

Here's what it comes down to.

Building in public costs nothing material. No budget. No permission. Just your time and willingness to be transparent.

If it doesn't work? You can always go quiet. You can rebrand. You can start fresh. The internet will forget, and you'll have lost nothing but hours.

If it does work? You've built something valuable: an audience, a distribution channel, a community of people invested in your success. That's hard to replicate through any other means.

## **Who This Advice is Actually For**

![Screenshot 2026-01-28 at 22.23.57.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/ffbec8580e3198b4a000c3e760866640366f0d25846bfd8775ef5d66592ef1b9.webp)

Nikita's caution makes sense for founders at established companies launching new products. When you already have an audience with expectations, managing narrative becomes important.

But for the founder starting from nothing? The calculus is different.

Building in public isn't mandatory. If you're working on deep tech with IP concerns, stay quiet. If competitors will clone you instantly, be strategic about what you share. If you genuinely cannot filter external opinions without losing focus, protect your attention.

But for most consumer and SMB startups, the theoretical risk of narrative confusion is vastly outweighed by the practical benefits: distribution, accountability, audience building, and early adopters who actually care.

Most startups don't die from too many eyes on them. They die from too few.

## **The Bottom Line**

![Build in Public Hurts Startups. Do It Anyway - Blog.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/d44e37a19ffcd69615b3df394e9a6eb4a05fed2f851c0f403551c90438db4eec.webp)

Nikita Bier is sharp, and his concerns come from real experience. But that experience was earned at companies with existing audiences. The advice doesn't transfer cleanly to founders starting from zero.

Building in public isn't right for everyone. But for many founders, it's one of the few genuine advantages available. It costs nothing. The downside is limited. The upside is substantial.

If you're building something and nobody knows about it, the risk isn't that you'll confuse people with your pivots. The risk is that nobody will be around to notice when you finally get it right.

That's the risk worth worrying about.

_Where do you land on this debate? I'm genuinely curious to hear from founders who've tried both approaches._

## Read more

*   [How to Get 30 Minutes Back After Every Meeting](https://videotranslator.ai/blog/how-to-get-30-minutes-back-after-every-meeting/)
    
*   [What Happens When Consent Gets Lost in Translation](https://videotranslator.ai/blog/what-happens-when-consent-gets-lost-in-translation/)
    
*   [Sales Didn’t Kill My Deals. Silence Did.](https://videotranslator.ai/blog/sales-didnt-kill-my-deals-silence-did/)

Unpacking Nikita Bier's argument and where founders misapply it

Build in Public Hurts Startups. Do It Anyway.

You're in a client meeting. Important one. The kind where details matter.

You're trying to listen. Really listen. But you're also frantically typing notes because if you don't capture this now, you'll forget the crucial detail that makes or breaks the follow-up.

So you're half-listening, half-typing, and fully stressed.

By the end of the meeting, you have pages of notes. But here's the uncomfortable truth: **you missed things. Important things**. Because you can't fully engage in a conversation whilst simultaneously documenting it.

This scene plays out thousands of times daily across organisations. And most teams treat it as normal.

You know what? It's not. It's value leaking from every meeting you run

## **The Real Cost of Manual Note-Taking**

![Photo by Luke Southern on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/06f3acc793f864c610cc0d5ad5df55e2eb016b9e7692182d4ed86334193dbaf8.webp)

Let's talk numbers for a moment.

The transcription industry standard is [four](https://verbit.ai/real-time-cart/how-long-it-really-takes-to-transcribe-accurate-audio/#:~:text=The%20average%20time%20to%20transcribe%20audio%20definitely%20decreases%20when%20transcribers,are%20quality%20will%20be%20compromised.) hours of work for every one hour of clear audio. That's a 4:1 ratio. If you attend a one-hour meeting, creating accurate notes traditionally takes four hours of focused transcription work.

Most people don't spend four hours on their meeting notes. They spend maybe 20 minutes cleaning up what they scribbled during the call.

The result? Notes that capture 30% of what was actually discussed, with accuracy that depends entirely on how fast you type and how well you multitask.

Now multiply that across every meeting in your week. Client calls. Team standups. Strategy sessions. Performance reviews.

How much are you actually capturing? How much are you missing?

## **What Actually Happens in Meetings**

![Photo by Dylan Gillis on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/bcefd199547125dd0d24fc8ae1c947b098bc0809cd91ef2a9e17765b3bee91a2.webp)

Here's the pattern I've observed across hundreds of client meetings:

**Minutes 0-10**: You're engaged, alert, taking decent notes. You capture the main points.

**Minutes 10-30**: Your typing speed can't keep up with the conversation. You start summarising in your head, losing specifics. Someone makes an excellent point whilst you're still typing the previous one. You miss it.

**Minutes 30-45**: Fatigue sets in. Your notes become bullet points. "Follow up on Q3 numbers." What Q3 numbers? What context? Future you will have no idea.

**Minutes 45-60**: You've mostly given up on comprehensive notes. You're just trying to stay present in the conversation whilst occasionally jotting down things that seem important.

**After the meeting**: You spend 20 minutes trying to reconstruct what happened from your fragmented notes. You email colleagues asking "_What did the client say about the timeline?_" You wish you'd captured more.

This isn't a personal failing. It's a human limitation.

We cannot simultaneously engage fully in conversation and document it comprehensively. These are competing cognitive tasks.

## **The Multilingual Problem Gets Worse**

![Photo by Vitaly Gariev on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/cff88ff2a7cde953008716d52f49b1693d7d13d451ef47155269932e93e50a65.webp)

Now add language barriers to this equation.

You're in a meeting with international clients or team members. They're speaking English, but it's not their first language. You're catching most of it, but occasional phrases get lost. Cultural references don't quite land. Technical terms get mangled in translation.

You're now doing three things at once: **listening, translating mentally, and taking notes.** Something has to give. Usually, it's comprehension.

Or perhaps you're the non-native English speaker. You understand the conversation, but taking notes in real-time in a second language whilst processing complex information? Nearly impossible.

[Research](https://www.researchgate.net/publication/392502522_Language_Barriers_And_Their_Impact_On_Effective_Communication_In_Different_Fields) shows that language barriers significantly impact meeting effectiveness, with participants spending mental energy on language processing rather than content engagement.

The result is meetings where everyone leaves with different understandings of what was decided.

## **What If You Could Just Listen?**

![Photo by Stefan Cosma on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/76c66f5d902d4f76a935141a9048d828966a2bc45cde2dea9a5050ec69e54d21.webp)

Imagine walking into a meeting with one job: listen and engage.

No frantic typing. No splitting your attention between conversation and documentation. No anxiety about missing crucial details.

You're present. You're asking better questions because you're not worried about capturing the answers. You're noticing tone, body language, and subtext that you'd miss whilst staring at your keyboard.

The meeting ends. You have a complete transcript of everything discussed. An accurate summary of key points. Action items clearly listed. All without having typed a single word.

This isn't theoretical. It's how meetings should work.

## **How Real-Time Meeting Transcription Works**

![VideoTranslatorAI meeting tool.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/2c8bafaae7006323c13a0f8b52c6aa8c628af0b58faecdd9d89101a3b76fb6d9.webp)

The technology is simpler than you'd expect.

Before your meeting starts, you make three quick decisions:

**Step 1: Choose your output**

![Choose mode_ transcribe_interpret.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/f6b98fda58cdbd21a5e98af1af19f7823e6c2aee204e8df273e592a345e6b5ee.webp)

Do you need a transcript or a translation? Select your option. If you're working across languages, choose which language you need the output in.

**Step 2: Select your language**

![Select language (for interpret mode).webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/0f8df6d491ec5e4dd72adc34e657e59ba0daff2aebcabab053433c7dcd983818.webp)

Pick the primary language of your meeting. The system handles the rest, including multiple speakers and accents.

**Step 3: Customise your summary**

![Customise summary prompt.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/3d349e0325fd8af12ca0a4a0eaca5bbdb48668196a306896bcd1bfa8faa9ff48.webp)

This is where it gets interesting. You're not limited to generic summaries. Tell the system what matters to you:

*   "Focus on action items and deadlines"
    
*   "Capture technical specifications and requirements"
    
*   "Summarise client concerns and objections"
    
*   "List all numbers, dates, and commitments mentioned"
    

The AI will structure the summary around what you actually need, not what a generic algorithm thinks is important.

**Step 4: Click start**

![Click start to begin transcription_interpretation.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/050ddefefa584e2d3ac8391e826d0130e629817f6174c4575d7868b46b78af6a.webp)

That's it. Your meeting begins. You engage naturally. The system captures everything in real-time.

**After the meeting ends**

![Download meeting transcript and summary](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/61d3f6dfbd8da5cb0c5b22d678c1eff79abec1aba2df4c1f21111a4c68a328d1.webp)

Download the full transcript, get the customised summary, or send everything to your email for later review.

The entire process from "meeting starts" to "summary in your inbox" happens without you touching a keyboard.

## Calculating the Recovered Value

![Photo by Ocean Ng on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/fca6c4e4aca17836f250c3ceb3d6ea6fcb1a05f9c92953acf7d14805928280d1.webp)

Let's put numbers to this shift.

**Traditional workflow for a 30-minute multilingual meeting:**

*   Meeting duration: 30 minutes
    
*   Transcription wait time: 2 to 4 hours (often next day)
    
*   Human review and cleanup: 45 minutes
    
*   Translation for non-English speakers: 1 to 2 hours
    
*   Summary creation: 30 minutes
    

**Total time cost: 5 to 7 hours per meeting**

**With real-time processing:**

*   Meeting duration: 30 minutes (with live translation)
    
*   Summary generation: 15 seconds
    
*   Review and distribution: 10 minutes
    

**Total time cost: Under 45 minutes**

That's not a percentage improvement. That's an order of magnitude difference.

## **When This Matters Most**

![Photo by Amina Atar on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/4550fdc3005fa1909bb656f3bd716171e216faffa1f2238a01903c06a790e30c.webp)

Real-time meeting transcription shines in various scenarios:

**Client meetings**: When details matter and relationships are on the line, being fully present whilst capturing every commitment makes the difference between successful partnerships and missed expectations.

**Cross-functional collaboration**: When engineers talk to designers talk to marketers, terminology gets confused and context gets lost. Complete transcripts help teams align on what was actually decided.

**International teams**: Language barriers create information loss. Real-time translation and transcription ensure nothing important disappears in translation.

**Performance discussions**: When conversations have legal or HR implications, accurate documentation protects everyone involved whilst allowing the discussion to flow naturally.

**Technical requirements gathering**: When specifications matter and misunderstandings are costly, capturing exact requirements prevents expensive mistakes down the road.

**Board meetings and governance**: When decisions need documentation for compliance or legal purposes, automated transcription ensures completeness without disrupting the meeting flow.

If your work involves regular important meetings, the question isn't whether you need better tools. It's how much longer you can afford to wait.

## **What You're Actually Trading**

When you adopt real-time meeting transcription, you're not trading money for convenience.

You're trading incomplete, attention-divided documentation for complete, engaged participation.

You're trading "I think they said something about Q3" for "here's exactly what they said about Q3, with context, at timestamp 23:47."

You're trading post-meeting reconstruction from fragmented notes for immediate access to complete, accurate records.

You're trading cognitive overload for presence.

It's time to stop pretending you can do both and start using tools that let you do what actually matters: engage fully, listen deeply, and respond thoughtfully.

The documentation will take care of itself.

The first time you finish a call and receive a complete summary before you've even closed the window, you'll understand why teams are moving away from traditional transcription workflows.

\***_Ready to stop splitting your attention in meetings?_** _Our tool transcribes, translates, and summarises your conversations in real-time, so you can be fully present whilst capturing everything that matters. Simple setup. Customisable summaries. Complete documentation without the cognitive juggling act._

[_Try our product for free today →_](https://agent.videotranslator.ai/chat)_._

## Read more

*   [What Happens When Consent Gets Lost in Translation](https://videotranslator.ai/blog/what-happens-when-consent-gets-lost-in-translation/)
    
*   [Sales Didn’t Kill My Deals. Silence Did.](https://videotranslator.ai/blog/sales-didnt-kill-my-deals-silence-did/)
    
*   [This AI Should Never Have Been Built](https://videotranslator.ai/blog/this-ai-should-never-have-been-build/)

Here’s the fastest way to close the meeting for real

How to Get 30 Minutes Back After Every Meeting

A Year 9 student from Korea, studying at an Australian school, wanted to celebrate her friend’s birthday. The request seemed straightforward enough: it was an overnight camping trip in a nearby national park.

For any teenager, this is the stuff of core memories. Campfires, stars, the particular magic of being outdoors with friends.

For her school, it was the beginning of a complex risk assessment that would test the limits of traditional communication.

How do you explain duty of care obligations across a language barrier? How do you ensure parents truly understand the risks their child might face? And how do you protect your school if something goes wrong? These questions loomed large, creating a sense of unease.

This is where most schools would have said no. Because it’s too complicated. Too risky. Too hard to ensure everyone truly understood what they were agreeing to.

But this school found a different way.

_This is a real story from one of our clients in the education sector._

## **When Permission Slips are Not Enough**

![Photo by Anna Amelina on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/5e9a1f6d0982e433c1e0cf4f5e95cb27898a9f577a3531117b095a439bf5e6cc.webp)

The student was a minor, and her parents lived in Korea. Under Australian duty of care obligations, the school bore responsibility for her welfare. They could not simply send home a permission form and hope for the best.

The campsite presented genuine risks. Emergency vehicle access was limited, with boat transport the only option between 9 PM and 6 AM. The bushland environment meant potential encounters with snakes and other wildlife. Water safety was a consideration. Adult supervision ratios needed to be carefully planned.

None of these risks were insurmountable. But the school's leadership knew that the parents needed to understand them fully before giving consent.

Not a cursory acknowledgment buried in fine print, but genuine comprehension of what their daughter might experience.

The problem was obvious: _how do you have that conversation across 8,000 kilometres and a significant language barrier?_

## **Finding A Way Through**

Traditional options felt inadequate.

Written translations could convey facts but not nuance. Phone calls with interpreters were difficult to schedule across time zones and left no reliable record. The school needed something that combined the immediacy of face-to-face conversation with the accessibility of real-time translation.

They found their solution in a [**VideoTranslatorAI’s**](https://agent.videotranslator.ai/) **video call tool** that provided live translation and on-screen transcription. The assistant principal could speak in English while the parents followed along with Korean text appearing in real time. Questions could be asked and answered immediately, with both parties confident they understood each other.

![English-Korean Multilingual Video Call](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/159d52d83898ad9a1180953037d26d556be006b23c774393d4dfd342da2a511a.webp)

_(Multilingual video call featuring AI-generated faces. Real clients' faces are not displayed to protect their privacy.)_

The conversation covered everything: supervision arrangements, emergency protocols, environmental hazards, and the precautions the school had put in place.

The parents asked thoughtful questions. They appreciated the detail. They gave their consent with full knowledge of what their daughter's adventure would involve.

And the school had something equally valuable: a documented record of the entire discussion, evidence that informed consent had been properly obtained.

The student went on her camping trip. She experienced Australian bushland, celebrated with friends, and returned safely with memories that will last a lifetime.

That’s a win for everyone!

## **The Bigger Picture**

![Photo by Mitchell Luo on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/bbf0db53ad57549c98065fd49cf6e98c8e6804570a5ff4231dc4fa7c4c022299.webp)

This wasn't just about approving a camping trip. It was about equity of opportunity for international students.

When language barriers make complex conversations too difficult, schools default to "no."

Not because the activity is genuinely unsafe, but because communicating risk and obtaining informed consent feels impossible across language differences.

The result? International students miss out on excursions, sporting events, cultural experiences, and opportunities that their English-speaking peers access easily. Not because their parents don't care, but because the school can't effectively communicate with them.

Beyond this situation, language barriers in education impact numerous touchpoints throughout the school year:

*   **Parent-teacher conferences**: Without effective communication, parents struggle to understand their child's academic progress, behaviour concerns, or additional support needs.
    
*   **Special education services**: Obtaining an Individualised Education Programme or 504 plan is complex even for English-speaking parents. When language barriers prevent parents from understanding their child's rights and navigating these processes, problems compound, leading to increased spending on interventions down the road.
    
*   **Emergency communications**: When urgent situations arise, schools can't afford translation delays. Parents need immediate, clear information they can act on.
    
*   **Permission and consent**: Any situation involving risk, medical treatment, or student welfare requires documented informed consent. Without clear communication, schools expose themselves to legal liability.
    
*   **Cultural integration**: International students and their families need to understand school policies, expectations, and cultural norms. When communication breaks down, misunderstandings create unnecessary conflict.
    

## **The Documentation Advantage**

In addition to improved communication, there is a practical benefit that school administrators increasingly value: **evidence**.

In an environment where institutions must demonstrate compliance with duty of care obligations, having a clear record of parent communications is invaluable.

Transcripts of video calls provide documentation that emails and phone notes simply cannot match.

The camping trip approval was not just a successful conversation. It was a legally defensible record of informed consent, captured in real time, with clear evidence that the parents understood and accepted the risks involved.

For schools navigating complex regulatory environments, this kind of documentation is not a luxury. It is a necessity.

![What Happens When Consent Gets Lost in Translation](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/61d3f6dfbd8da5cb0c5b22d678c1eff79abec1aba2df4c1f21111a4c68a328d1.webp)

_(Instant meeting transcript and summary by VideoTranslatorAI)_

## **A New Standard for Inclusive Education**

![Photo by Sam Balye on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/30e1dc76137f5dba327d82f23e35f63738d5e89def2ed829423ce7ef2c57a0d0.webp)

International education has always required cultural sensitivity and adaptability. But for too long, language barriers have created invisible walls between schools and families.

[VideoTranslatorAI’s](https://agent.videotranslator.ai/) real-time translation technology does not just solve a logistical problem. It signals something important to families: that their understanding matters, that their involvement is valued, and that distance and language will not diminish their connection to their child's education.

The Korean student who went camping learned something valuable about Australian culture that week. But her parents learned something too: that their daughter's school saw them as genuine partners in her education, not obstacles to be managed.

That shift in relationship is worth more than any single permission slip.

When schools communicate clearly with every family, students get opportunities they might otherwise miss. Real-time interpreting tools are making that clarity possible, one conversation at a time.

**_Want to improve communication with your international families?_** [_VideoTranslatorAI_](https://agent.videotranslator.ai) _offers multilingual video calls that enable real-time, face-to-face communication between educators and parents, regardless of language differences._

If you're interested in learning more, [try our product now](https://agent.videotranslator.ai/chat).

## Read more

*   [Sales Didn’t Kill My Deals. Silence Did.](https://videotranslator.ai/blog/sales-didnt-kill-my-deals-silence-did/)
    
*   [This AI Should Never Have Been Built](https://videotranslator.ai/blog/this-ai-should-never-have-been-build/)
    
*   [I Built Software Wrong for 7 Years. You Shouldn’t Do The Same.](https://videotranslator.ai/blog/i-built-software-wrong-for-7-years-you-shouldnt-do-the-same/)

What Happens When Consent Gets Lost in Translation

A real case that exposed a hidden international school risk

You just finished a brilliant product demo. The prospect loved it. They asked smart questions, nodded at all the right moments, and promised to "circle back next week."

Then you spotted a critical bug in production.

Three weeks later, you remember the demo while brushing your teeth. You scramble to find the email thread. The prospect has gone cold. Another warm lead, lost to the chaos of founder life.

This kept happening to me. Not because I lacked ambition or sales skills, but because I kept choosing to ship features over sending follow-ups. 

And I wrote this article to tell you how I fixed this problem. 

## The Founder's Impossible Choice

![Photo by ThisisEngineering on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/144ef7f1933d752669ed763ee5b15e193754d6afd6a765ca43926b6ac2761ed4.webp)

As a small startup founder, I discovered that cold outreach and product demos were my most effective marketing channels. Nothing beats a live conversation where you can address objections in real time and show your product solving real problems.

But here's what nobody tells you about founder-led sales: the work never stops competing with itself.

Every hour I spent nurturing leads was an hour I wasn't fixing bugs. Every afternoon I dedicated to follow-up emails was an afternoon I wasn't shipping features. 

My brain constantly toggled between "build mode" and "sell mode," and **build mode almost always won.**

The result? Warm leads turned cold. Interested prospects forgot about me. Deals died in silence.

My goal is modest but meaningful: 100 loyal users by the end of 2026\. 

But I realised I would never reach it if I kept losing prospects to my own distraction.

## The Hidden Momentum Problem

When I realised I was losing leads, my first instinct was to look for a CRM solution. Surely there's a tool for this, right?

There are. Hundreds of them. However, they all miss the point.

Traditional CRMs are designed for sales teams with pipelines, stages, and conversion funnels. They're built for people whose full-time job is sales. They assume you have time to update dashboards, manage pipelines, and maintain detailed contact records.

As a founder, I don't have that time. I'm not a full-time salesperson. I'm a builder who occasionally needs to sell what I've built.

What I actually needed was simpler: 

**Tell me who I should follow up with today, and remind me what I already did.**

That's it. No complex pipelines. No elaborate stages. Just a daily list and a memory aid.

## A Nature Documentary that Changed My Thinking

Last Christmas, I found myself watching a nature documentary about honey badgers. 

These small African mammals have a reputation for fearless persistence. They chase prey twice their size. They raid beehives despite getting stung hundreds of times. They never give up.

Something clicked while watching. The best salespeople aren't aggressive or pushy.

They're persistent. They show up consistently, follow up reliably, and never let promising conversations fade away.

I decided to build a tool that would help founders adopt this mindset. I called it ***Honey Badger Sales.***

![Photo by Vincent van Zalinge on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/5847aadc6e943722ae84919c3a3a204b28a461a0520a1f777cf5d867f74342e3.webp)

## How The Tool Actually Works

I built Honey Badger Sales to solve one problem exceptionally well: **making sure warm leads never go cold.**

The workflow is simple. First, I create a new contact list or import from my existing CRM data. No complex migration required.

![Add Company propspect](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/8fc349f90b78220f5895fd5be97a899ebeeb3f9c4452e755e0078d507cc8d123.webp)
*(Adding a prospect contact on Honey Badger Sales)*

From there, I can draft and send outreach emails directly within the app. Everything stays connected to the contact record, so I always have context at my fingertips.

![Write or draft email](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/834129e0af07fb817238fd47029867f890acc0a6235dd6ed24db991a9a45e712.webp)
*(Send or draft an email outreach easily!)*

The homepage shows my daily focus list: contacts who need follow-up today. Each contact clearly displays whether they're due for a first follow-up, second follow-up, or fifth. I can also see the last thing I discussed with my prospect and what I planned to say next.

![Honey badger homepage](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/ebc0b374b736890f1ccbbf9426e9f971651758288866682bda7d71adf8c4ad55.webp)

That's it. No fancy pipelines. No overwhelming dashboards. Just a daily list and the memory you need to pick up where you left off.

## What I've Learned Building This

Creating Honey Badger Sales taught me something important about founder-led sales: consistency beats intensity every time.

I used to batch my sales work into marathon sessions. I would spend an entire day doing outreach, then disappear into code for two weeks. This created a boom-and-bust pattern that confused prospects and killed deals.

Now I spend 30 minutes each morning working through my follow-up list. It's not glamorous. But those 30 minutes, repeated daily, generate more results than sporadic bursts of intense effort.

The honey badger doesn't make one dramatic attack and hope for the best. It keeps showing up, day after day, until it gets what it came for.

## Your Leads are Waiting

![Photo by Lukas Blazek on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/ef41613426c323b951ca997939557c013409f198769519be04d867f144d60b42.webp)

If you're a founder struggling to balance building and selling, you're not alone. The pull toward product work is real and powerful. Shipping features feels productive in a way that sending follow-up emails simply doesn't.

But those warm leads represent real people who showed genuine interest in what you're building. They deserve a response. Your startup deserves the revenue.

Sometimes the best tool isn't the most sophisticated one. Sometimes it's the one that simply reminds you to show up.

Be the honey badger. Never let a warm lead go cold\!

**For now, Honey Badger Sales is something I built for myself. I'm still tweaking it, learning what works, and using it daily to manage my own outreach.*

*But if the problem I've described sounds familiar, I'd genuinely like to connect. Leave a comment or reach out to us by clicking here.*

## Read more
- [This AI Should Never Have Been Built](https://videotranslator.ai/blog/this-ai-should-never-have-been-build/)
-  [I Built Software Wrong for 7 Years. You Shouldn’t Do The Same.](https://videotranslator.ai/blog/i-built-software-wrong-for-7-years-you-shouldnt-do-the-same/)
- [You Sound Like ChatGPT Now](https://videotranslator.ai/blog/you-sound-like-chatgpt-now/)



Read Sales Didn’t Kill My Deals. Silence Did. and explore practical insights from VideoTranslatorAI on multilingual communication, interpretation, and AI-supported workflows.

Sales Didn’t Kill My Deals. Silence Did.

Open X (Twitter) right now and watch people become other people.

Not through makeup or costume. But through AI that maps their movements onto someone else's face with unsettling precision. 

The technology tracks every micro-expression, every head tilt, every blink. The result moves like a human because it is a human, just wearing digital skin that doesn't belong to them.

![Screenshot 2026-01-21 at 00.14.23.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/5f7bf76cfd721b22c1061dfa48609c35d23a2e9a2a940a18b18916076af87192.webp)
_(Posted by [@venturetwins](https://x.com/venturetwins/status/2011285029541077033) on X)_

Leonardo DiCaprio, Sydney Sweeney, your favourite actor, your least favourite politician, your ex. Anyone whose face exists in a training dataset.

The demos are technically impressive. The implications are horrifying. 

And I say this as someone who builds AI for a living.

## The Question We Stopped Asking
![Photo by Simone Secci on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/7f4dd031df294e1c596ffca3c2f2ef48789ba538ba502d244b5e88b565002eab.webp)

I run a company that develops AI-powered meeting tools. Real-time transcription. Live translation across languages. Intelligent summarisation. Every feature we ship starts with the same question: **what problem does this solve?**

It's not a complicated question. But somewhere in the race to build the most impressive thing, a lot of AI developers stopped asking it.

Now, let me ask you a question. 

**What problem does face-mimicking AI solve?** I dare you to name one legitimate application.

**Entertainment?** Perhaps. But we already have professional CGI, deepfakes with consent, and actors who can, you know, act.

**Marketing?** Sure, until Leonardo DiCaprio's lawyers come knocking because you used his face to sell protein powder without permission.

**Education?** I'm struggling to imagine the scenario where transforming yourself into Scarlett Johansson helps students learn algebra.

**Creative expression?** There's an argument here, but it falls apart the moment you realise most of these tools are being used to impersonate real, living people who never consented.

I've spent fifteen minutes on this exercise. Then an hour. Then I asked my team. We came up empty.

The charitable interpretation is that this technology is a solution searching for a problem. 

The uncharitable, and I suspect more accurate, interpretation is that the creators know exactly what it's for. They're just not saying it out loud

## What It's Actually Being Used For

Let me tell you what I'm seeing on my timeline.

People turning themselves into celebrities for clout. 
![Screenshot 2026-01-21 at 00.13.29.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/c263f1d5a4435955192274ff95a5b93172c3052e0c21c88df9fe6b446705b62e.webp)
_(Posted by [@EHuanglu](https://x.com/EHuanglu/status/2011812530637959629) on X)_

People creating "erotic" content using the faces and bodies of figures who never agreed to this. 
![Screenshot 2026-01-21 at 00.12.18.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/d4c5919e8a570395d59483af8f111c4772978696a37e6764a177ba80fbe8205d.webp)
_(Posted by [@mhdfaran](https://x.com/mhdfaran/status/2013257382345015320) on X)_

People testing just how convincing they can make a fake video of a real person.

This isn't hypothetical harm. It's happening right now, in public, with thousands of likes and shares.

The erotic applications alone should give us pause. We've spent years grappling with non-consensual intimate imagery. 

We've passed laws. We've built detection tools. We've had painful public conversations about consent and dignity.

And now we're handing people a tool that makes all of that exponentially easier to produce and harder to detect.

If you're building technology and you can't articulate a beneficial use case, but you can immediately see the harmful ones, that's not a feature gap. That's a warning sign.

## My Three Core Concerns

With this face-swapping technology, I see three glaring issues:

### 1\. Blatant Copyright Violations

<iframe width="1236" height="695" src="https://www.youtube.com/embed/6KbqaeAKZqI" title="Kling 2.6 Face Swap with Harley - AI" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>

Using AI to recreate a celebrity's likeness without permission is theft of intellectual property, plain and simple.

Imagine if someone used a digital version of Sydney Sweeney to advertise their dodgy cryptocurrency scheme. Sweeney didn't consent. She’s not being paid. Her reputation is being exploited without his knowledge or permission.

A similar case actually happened. A woman in France lost $850,000 after scammers used AI-generated images of [Brad Pitt](https://www.youtube.com/watch?v=ryOKnKCj3as&t=4s) to convince her she was helping the actor.

Actor [Bryan Cranston](https://www.cnbc.com/2025/10/20/open-ai-sora-bryan-cranston-sag-aftra.html#:~:text=OpenAI%20announced%20on%20Monday%20that,Cranston%20said%20in%20a%20statement.) raised concerns after Sora users created deepfakes featuring his likeness without consent or compensation, prompting families of Robin Williams, George Carlin, and Martin Luther King Jr. to also complain to OpenAI.

These aren't just famous people being precious about their image. They're professionals whose likeness has commercial value, and that value is being stolen by anyone with access to deepfake technology.

### 2\. The Primary Use Is Fraud

Strip away the marketing speak and ask yourself: what is this technology actually being used for?

The answer is scams and manipulation.

Since 2017, fraud has accounted for [31%](https://surfshark.com/research/study/deepfake-statistics) of all deepfake incidents. Deepfake fraud attempts spiked by [3,000%](https://keepnetlabs.com/blog/deepfake-statistics-and-trends) in 2023, with losses in North America exceeding $200 million in the first quarter of 2025 alone.

The ability to create convincing videos of famous people saying or doing things they never said or did isn't a feature. It's a weapon. And overwhelmingly, that weapon is being used to harm, deceive, and exploit.

### 3\. The Pornography Problem 

![Screenshot 2026-01-21 at 00.11.57.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/ebf9206ed9050f2f5b70c909e8800c7dc7aa7c5fd0aae357d584698a42c93533.webp)
_(Posted by [@YoRHa2Pee](https://x.com/YoRHa2Pee/status/2013189145816871131) on X)_

Let's address another elephant in the room: the overwhelming majority of deepfake content is pornographic.

The number of deepfake pornography videos produced in 2023 was [464%](https://www.securityhero.io/state-of-deepfakes/#:~:text=Appendix-,KEY%20FINDINGS,07.) higher than in 2022, with almost 4,000 female celebrities found across the top deepfake porn websites.

Analysis shows that [94%](https://www.securityhero.io/state-of-deepfakes/#:~:text=Appendix-,KEY%20FINDINGS,07.) of those featured in deepfake pornography videos are affiliated with the entertainment sector, including singers, actresses, social media influencers, models, and athletes.

When I see people on X casually sharing AI-generated videos of celebrities in suggestive poses or erotic situations, I'm witnessing the normalisation of something deeply unethical: the creation of sexual content featuring real people without their consent.

This isn't parody. It isn't satire. It's digital sexual violence.

If the primary application of your technology is creating non-consensual pornography, you've built something that shouldn't exist.

## The "Just Don't Look" Fallacy
![Photo by Ryoji Iwata on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/ad2f7f5d57d11ab527112cce2b0f42f7921dfd6b3b4cd45fcac33d12e6b67c30.webp)

Some will argue that if you don't like deepfake content, just don't engage with it. Scroll past. Don't create it yourself.

But that ignores the victims. The celebrities whose likenesses are stolen. The ordinary people whose faces end up in pornography they never consented to. The elderly people were scammed out of their life savings by deepfake videos of trusted figures.

Your choice not to create or view deepfakes doesn't protect anyone. It just means you're not personally contributing to the harm.

## What Responsible AI Development Looks Like

I'm not calling for bans. I'm not suggesting we halt all AI progress. That would be hypocritical given my work, and counterproductive given the genuine benefits AI can deliver.

But I am calling for something that seems to be in short supply: **honesty**.

If you're building AI tools, be honest about the likely use cases. Not the best-case scenarios in your pitch deck, but the actual ways people will use your technology in the wild.

If you're deploying AI tools, be honest about whether you've thought through the second and third-order effects. Not just "this is cool," but "this is cool and here's why the benefits outweigh the predictable harms."

And if you're a user experimenting with this technology, be honest about what you're actually doing. Turning yourself into a celebrity for a laugh might seem harmless. 

But you're training yourself and the algorithm that this is normal. That this is acceptable. That consent doesn't matter as long as the technology is fun.

## The Line I'm Drawing
![Photo by Hitesh Choudhary on Unsplash.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/7f353664ab46796727ab0bd96f26fe73b3afb8ddf9519b77db1551f70b8368c7.webp)

I work in AI. I'll continue working in AI. I believe it's one of the most important technologies of our generation.

But not all AI is equal. Not all applications are beneficial. And not every capability that can be built should be built.

Face-mimicking motion AI, as currently deployed, fails every test I can construct for beneficial technology. 

It lacks clear positive use cases. It enables obvious harms. It undermines consent, intellectual property, and our shared ability to trust what we see.

I'm not against AI. I'm against this AI. And I think more people in my industry should have the honesty to say the same.

## Read more
- [I Built Software Wrong for 7 Years. You Shouldn’t Do The Same.](https://videotranslator.ai/blog/i-built-software-wrong-for-7-years-you-shouldnt-do-the-same/)
- [You Sound Like ChatGPT Now](https://videotranslator.ai/blog/you-sound-like-chatgpt-now/)
- [I Rested. Then Shipped An App in 72 Hours. A Story about TrustPRR](https://videotranslator.ai/blog/i-rested-then-shipped-an-app-in-72-hours/)


We crossed a line when faces became interchangeable. 

This AI Should Never Have Been Built

For nearly a decade, I approached every project like an architect designing a skyscraper. 

Grand blueprints. Comprehensive feature lists. Meticulous upfront planning. Everything mapped out before a single line of code was written.

It felt professional. It felt thorough. It felt right.

It was also completely wrong.

After more than 7 years in this field, I've come to realise something that fundamentally changed how I build software: 

**We're not architects. We're gardeners.**

## The Architect's Trap
![Photo by Wiktor Karkocha on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/716aae23434dd3ace952660ff7a82728af007f0050de1857e22f944439c555b5.webp)

The architecture metaphor has dominated software development for decades. We even borrowed the terminology: *software architects*, *system architecture*, *architectural patterns*.

 The influence runs so deep that it shapes how we think about building products.

Here's how the architectural approach typically works: you gather all requirements upfront, design the entire system, create detailed specifications, then hand it over for construction. 

Once the building is complete, the architect's job is done. The structure is fixed, permanent, unchanging.

This made sense when software development was closer to hardware, when programmes were written in machine code for specific mainframe architectures in the 1950s and 1960s. 

Once in production, changes were painful and rare. If the company bought new hardware, you rewrote everything from scratch. That actually resembles building construction.

But ***modern software***? It's nothing like that.

Software is *soft*. Buildings are hard. 

As Andy Hunt and Dave Thomas (2019) observe in The Pragmatic Programmer, rather than construction, software is more organic than concrete. It changes constantly, influenced by user requirements, business needs, market pressures, and technological evolution.

My last project taught me this lesson the expensive way. I approached it like an architect: gathered every possible requirement, defined the architecture upfront, planned for every eventuality. 

![Our previous multilingual video call app, packed with "every feature" (apparently).](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/87a22a83ae7cebb8fcb59b754739980dbd1d91b106923b30a1c224ad0f3a1c39.webp)
_(Our previous multilingual video call app, packed with "every feature" (apparently)._

The result? A big, unwieldy monster plagued by performance issues and technical debt. 

We'd built a skyscraper when we needed a garden.

## The Gardening Mindset
![Photo by Jonathan Kemper on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/33b9a6593514342f74bacbb1805063d174517d18fef1e11821d286f9d0e2e5e9.webp)

So what does it mean to think like a gardener instead of an architect?

**A garden is never finished. It's constantly growing, changing, evolving.** 

You don't plant a garden once and walk away. You tend it continuously, adapting to seasons, weather, and what the plants themselves tell you they need.

The most important aspect of the gardening metaphor is *constant change*. 

Different from a house where an engineer walks away once construction is finished, a garden needs continuous care.

Here's what changed for me when I adopted the gardening mindset:

### 1\. Focus on One Plant at a Time
![Photo by Igor Son on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/36a132fa695d0b68f8c04e6a0552be7f491af5e231f02dda258c60eee136c9a6.webp)

In gardening, you don't try to grow everything simultaneously. You focus on nurturing one plant, making sure it's healthy before expanding to the next.

In software, this means **building one piece of functionality properly**. Not a massive feature set. Not enterprise-grade everything. One thing that works, that users actually need, that you can deploy and observe.

When you deploy this single functionality, it begins to grow and attract attention. Users engage with it. They tell you what they need next. Just like deciding which plants to cultivate based on which ones thrive in your soil and climate.

This is fundamentally different from the architectural approach, where you try to anticipate every need upfront. 

The garden approach lets users guide your growth through real usage, not theoretical requirements.

### 2\. Accept That Things Will Change
![Photo by Y M on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/c9b05bf36acfcfc42ffe60ebc3e25fd85d4575c5920b2fc326e2073b245fcd02.webp)

Buildings resist change. Gardens expect it.

Software is influenced by external factors you cannot control: user requirements shift, business priorities change, frameworks update, security vulnerabilities emerge, competitors launch new features. 

Treating software like a fixed structure means fighting against its fundamental nature.

Gardens change with seasons. Some plants thrive and spread. Others struggle and need to be replaced. You prune to encourage healthy growth. You remove what's no longer working.

In software terms: **you refactor constantly**. You remove features that aren't used. You simplify what's become complex. You rebuild components that have rotted. This isn't failure. It's maintenance. It's how healthy systems evolve.

Research shows that leaving a garden unattended leads to rot, weeds, and eventual unusability. The same applies to software. 

When you don't maintain it, security issues emerge, APIs stop working, and technical debt accumulates until you need to tear everything out and start over.

### 3\. Use the Right Tools for Your Garden
![Photo by Lucas de Moura on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/968a5e571866ffc3af22295567ad8288024b27fa52aff0f08960702d3b3e3f14.webp)

Every gardener has tools they love to work with. These don't have to be the fanciest tools, but they need to work for the type of garden you're cultivating.

You can do everything manually, but certain tools enable efficiency without over-engineering. A gardener doesn't buy industrial farming equipment for a small vegetable patch. They choose tools proportional to the garden's scale.

Software development is the same. You don't need enterprise architecture patterns for a startup MVP. You don't need microservices when a well-structured monolith would do. You don't need every framework and library just because they're popular.

Choose tools that help you tend your garden effectively. Nothing more, nothing less.

### 4\. Understand That Growth Takes Time
![Photo by Sushobhan Badhai on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/16d4044be4160709c8e99b90d35261d90e41187c186604f0e895f62aa343488b.webp)

Architects expect buildings to be completed on schedule. Gardeners understand that plants grow at their own pace, influenced by factors you can control (water, sunlight, soil) and factors you can't (weather, pests, seasons).

Software development works the same way. You can create the right conditions, you can use good practices, but you cannot force growth to happen faster than the system naturally allows.

When stakeholders ask, "How long will this take?" the honest answer is closer to "How long will this tree take to grow if you do everything right?" rather than "How long to build this wall?" 

The first acknowledges environmental factors like legacy code quality, team experience, and unexpected challenges. The second assumes fixed, predictable construction.

This doesn't mean lack of accountability. It means realistic expectations based on organic growth rather than industrial manufacturing.

## What This Means for How You Build
![Photo by Fotis Fotopoulos on Unsplash](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/f58d7da43ddb072acb3343c48b6b86dcabe628434a8b94c7150d7cffa17c59bd.webp)

If you're still thinking like an architect, here's how to start thinking like a gardener:

* **Stop trying to design everything upfront.** You cannot anticipate all requirements. You cannot predict how users will actually behave. Build one thing, deploy it, watch what grows.  
* **Embrace continuous refactoring.** This isn't technical debt or poor planning. It's pruning. It's weeding. It's the essential maintenance that keeps your garden healthy.  
* **Choose simple over comprehensive.** Start with the smallest viable thing that solves a real problem. You can always expand later based on what thrives.  
* **Let users guide your growth.** They'll tell you what they need by how they use what you've built. Listen to the garden, not the blueprint.  
* **Expect change and plan for it.** Don't build rigid structures. Build flexible systems that can adapt as requirements evolve.  
* **Focus on quality over quantity.** One well-tended plant is better than a dozen neglected ones. One polished feature beats ten half-finished ones.

## From My Garden

The product I am building now operates on gardening principles. We started with one piece of functionality. We made it work properly. We watched how users responded.

![Agent dock v1](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/c5659a581f3ebe4eb7579e5eb37f5586af2ba62e8f18b3300991a0e3f1715793.webp)
_(The first iteration of VideoTranslatorAI's app - Instant transcription, translation, and meeting summary.)_

What they told us shaped what we grew next. Sometimes their feedback surprised us. Features we thought were essential turned out to be unnecessary. Capabilities we almost skipped became central to the product.

![Agent dock latest and greatest](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/824e631de03fc3ebe5b68be08c6b1a1cf73f8ceb8e70776b8f6962b6500bcd74.webp)
_(The latest version of VideoTranslatorAI's app - We added summary customisation capability.)_

The codebase stays manageable because we only grow what we need. Performance remains solid because we do not carry the weight of unused features. 

The team stays focused because our priorities emerge from reality, not speculation.

## The Builder’s Choice

You can construct software or cultivate it. Both approaches produce products. But they produce different kinds of products.

Constructed software impresses in demos. It has features for every conceivable use case. It looks complete.

Cultivated software delights in use. It does fewer things, but it does them exceptionally well. It grows with its users rather than guessing at their future needs.

After 7 years of building software, I have stopped trying to be an architect. The blueprints were beautiful. The reality was not.

Now I am a *gardener*. The work is slower. The results are better. And my products actually survive contact with the real world.

Start with one seed. Nurture it properly. Let your users tell you what to grow next.

That is the lesson it took me 7 years to learn. I hope it takes you less.

## Read more
- [You Sound Like ChatGPT Now](https://videotranslator.ai/blog/you-sound-like-chatgpt-now/)
- [I Rested. Then Shipped An App in 72 Hours. A Story about TrustPRR](https://videotranslator.ai/blog/i-rested-then-shipped-an-app-in-72-hours/)
- [A Doctor Told Me Something Haunting](https://videotranslator.ai/blog/a-doctor-told-me-something-haunting/)


the gardening approach to software development

Most engineers think like architects. That’s the mistake. 

I Built Software Wrong for 7 Years. You Shouldn’t Do The Same.

[51 percent](https://english.elpais.com/technology/2024-10-24/humans-are-already-repeating-words-learned-from-chatgpt-such-as-delve-and-meticulous.html).

That's how much more frequently academics started using the word "delve" after ChatGPT launched. Not in their writing, but in their *speech*. On camera. In lectures. In presentations they'd given the same way for years.

"Meticulous." "Adept." "Nuanced." "Realm."

These ChatGPT-favoured words surged across nearly 280,000 YouTube videos from academic institutions. Meanwhile, words the AI uses less, like "bolster," "unearth," and "nuance" as a verb, quietly faded from our vocabulary.

The Max Planck Institute for Human Development documented this. [Researchers](https://www.fastcompany.com/91398460/ai-is-quietly-reshaping-the-way-we-talk) called it the "seep-in effect."

But let's call it what it really is: **reverse training.**

## We are Optimising Ourselves

We like to think we're in control of our tools. We pick them up, use them, put them down. They serve us. We're the ones giving commands.

But here's the uncomfortable truth: 

Every time you rephrase a thought so your AI transcriber catches it cleanly, you've been trained.

Every time you announce "I have three points" before speaking, you've been trained.

Every time you kill a joke because the meeting summariser won't get it, you've been trained.

We've spent years asking how to make AI align with human values. The researchers at Max Planck suggest we've had it backwards: "While intensive research focuses on machines' alignment with human behaviour, our study suggests that the reverse may also be occurring." ([Lopez et al](https://arxiv.org/html/2409.01754v1)., 2024). 

We are aligning ourselves with the machine.

And we're doing it *voluntarily*, *unconsciously*, one optimised sentence at a time.

## How Language Flattening Works

This isn't just about vocabulary. It's about the systematic compression of human expression into machine-readable formats.

UNESCO warns that language flattening is a real phenomenon, where AI-generated content strips away linguistic richness, regional accents, and cultural variations. 

When we optimise our speech for machines, we don't just change our words. We change what we're able to express.

Let me break down how this happens:

### 1\. The Search Engine Effect

![The Search Engine Effect](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/5e7196214412bbaacf9264c2e2cc5ac5d221ffbb06203de5e533fb482b168ab3.webp)

Remember when you learned to search Google? You didn't type "What's the weather like in Sydney today?" You typed "weather London." Two words. No articles. No pleasantries. Pure information retrieval.

You trained yourself to speak Google's language.

Now the same thing is happening with AI tools. You've learned to speak in clear declarations. To announce your intent before expressing it. To avoid the tangential thinking that makes meetings human.

"I want to flag a risk" has replaced "I'm a bit worried about something, and I'm not sure if it's a real issue, but..."

The second version is how people actually think. The first is what an AI transcriber tool captures cleanly.

### 2\. The Loss of Nuance 
![The Loss of Nuance](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/261600bbc4fc5190586a5cb29ae701b0c5b2b987a2648f7b88d87c53b0893def.webp)

When you speak for the machine's benefit, you pay a tax in texture.

Sarcasm becomes risky. The AI might log your joke as a serious statement. ("Meeting notes: Tathagat suggested we abandon the project and go home.")

Cultural idioms become friction. Your "she'll be right" doesn't translate for a globally-trained model.

Emotional subtext becomes invisible. The sentiment analysis sees words, not the pause before them.

[Karelia Vázquez](https://english.elpais.com/technology/2025-11-01/the-chatgpt-effect-weve-all-started-talking-like-robots.html) (2025) put it starkly: "Robotic verbiage erases vulnerability, humour, and everything that makes us human."

What we're left with is communication that's efficient, clear, and utterly sanitised. It's language optimised for machine understanding, not human connection.

### 3\. The Standardisation Trap
![The Standardisation Trap](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/6905d09a98d2fd3bd9087af6f8001d11478a3390e1744d25e6a1eff18b5b7e12.webp)

A [Cornell study](https://news.cornell.edu/stories/2025/04/ai-suggestions-make-writing-more-generic-western) found that Indian English speakers are shifting toward American English patterns when using AI tools. Regional dialects, the linguistic fingerprints of culture and community, are being smoothed away.

This isn't accidental. It's architectural. AI models are trained predominantly on Standard American English. They don't just prefer it. They actively struggle with alternatives.

[The Verge](https://www.theverge.com/openai/686748/chatgpt-linguistic-impact-common-word-usage) documented cases of ChatGPT repeating non-standard English prompts back to users with exaggerated, almost mocking versions of their dialect. One Singaporean user described the AI's response as "super exaggerated Singlish" that was "slightly cringeworthy."

The message is clear: **speak Standard American English, or be misunderstood.**

So people adapt. And the diversity of human expression contracts.

### 4\. The Prompt Engineering of Daily Life
![Prompt Engineer Everyday](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/44b9f4ded6cd93962b63027e00ccc437b7286b3070661c41daf2c537b7880ac2.webp)

Nobody warned us about this, but we're all becoming prompt engineers, not just for ChatGPT or other LLMs. **We're prompt engineering our own thoughts.**

You're in a meeting. You have a complex idea with multiple layers, some uncertainty, and a few contradictory elements. In a purely human conversation, you'd think out loud. You'd explore the idea verbally, circle back, and refine as you go.

But now there's an AI meeting notetaker around you. And you know from experience that if you think out loud, the summary will be a mess. The AI will pick up your half-formed thoughts as if they were conclusions. Your verbal processing will look like indecision in the notes.

So you don't think out loud anymore. You formulate the idea internally first. Then you deliver it clearly, as if reading from a script you just wrote in your head.

You've optimised yourself. But you've also killed the collaborative thinking process that makes meetings valuable.

### 5\. The Empathy Erosion
![The Empathy Erosion](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/2c9c4502d6ee4bbb914d375a1234997eeeb5615453345f71235906d2cdcd4803.webp)

Perhaps most troubling is what happens to emotional intelligence in this new paradigm.

Research from [Cornell University](https://news.cornell.edu/stories/2023/04/study-uncovers-social-cost-using-ai-conversations#:~:text=The%20study's%20lead%20author%2C%20Jess%20Hohenstein%2C%20says,with%20smart%20replies%20were%20evaluated%20more%20negatively) shows that communications suspected of using AI assistance are judged as less cooperative and less affiliative by recipients. 

But here's the paradox: to make AI tools work well, we communicate in ways that trigger exactly this perception.

When you speak in clear, structured sentences with proper grammar and no emotional variance, you sound professional. You also sound like you might be using AI. And increasingly, that makes you sound less trustworthy, less collaborative, less human.

We're trapped in a bizarre loop: optimising our communication for machines makes us seem more like machines to other humans.

## The Cultural Implications

This isn't just about individual behaviour. It's about culture-wide linguistic shift.

The proliferation of AI-generated text is staggering, with vast amounts of content produced daily by algorithms and fed back into systems as training data. 

This creates a recursive loop where AI learns from AI-influenced human speech, which then influences more humans, who produce more AI-influenced speech.

The impact of language models on language flattening may be inversely related to the number of native speakers, meaning smaller languages and cultural groups face even greater pressure to conform to AI-optimised communication patterns.

Think about what we're losing:

* **Regional varieties** that carry centuries of cultural identity  
* **Informal registers** that build social bonds  
* **Creative language play** that drives linguistic innovation  
* **Ambiguity and poetry** that make communication interesting  
* **The mess** that makes us human

In exchange, we get efficiency. Clarity. Machine-readable communication.

Is that really a fair trade?

## A Better Way Forward 
![A Better Way Forward.webp](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/4f31f43e436462b7c9e5646c45b9346a170876d74cb71629ef0113d7c2b33401.webp)

I'm not suggesting we abandon AI tools. I build them myself. Our [meeting agent](https://agent.videotranslator.ai/) transcribes, translates, and summarises conversations in real-time, and it genuinely makes global collaboration easier.

But there's a difference between **using AI as a tool** and **letting AI dictate** how we communicate.

Here's what I've started doing in my own meetings:

**I speak naturally first, optimise never.** If the AI misses something, that's feedback for improving the tool, not a signal that I should change how I talk.

**I flag machine-friendly moments.** When I need something captured perfectly, I'll say "for the record" and then give a clean statement. The rest of the time, I'm human.

**I preserve the mess.** Those tangents, half-formed thoughts, and verbal exploration? They're features, not bugs. If the AI can't handle them, we need better AI, not more robotic humans.

**I check the transcript critically.** When the AI summary misses nuance or context, I add it manually. Yes, it takes time. That time is worth preserving the richness of what was actually said.

The goal isn't perfect transcripts. **It's human communication that happens to be transcribed**.

![Italian-English Agent Interpreter.gif](https://storage.googleapis.com/vtai-web-media-prod/cms/originals/blog-inline/722aaaea7b6fd89c483167339c915daba98848cb5ed5bfa4386d81201d88718f.gif)

## The Script We're Writing

AI is rewriting the human script. Not through force, but through subtle pressure to optimise, clarify, and standardise.

Every time we simplify our language for a voice assistant, we train ourselves to think in simpler patterns. 

Every time we avoid idioms in a transcribed meeting, we lose a bit of cultural expression. 

Every time we speak in "prompts" instead of naturally, we become a little more like the machines we're trying to control.

As AI models become embedded in the architecture of modern life, the very nature of human interaction is being reprogrammed, with our conversations, political debates, and emotional lives being subtly but profoundly reshaped.

The costs of this transformation aren't measured in productivity metrics. They're measured in empathy, human connection, and the shared understanding that underpins society.

Can you see it now?

Listen to yourself in your next meeting. Notice when you're speaking for the humans in the room versus speaking for the AI in the corner. Notice when you catch yourself simplifying, clarifying, standardising.

And then ask yourself: *is this the script you want to follow?*

Because we're writing it, line by line, conversation by conversation. And once it's written, it'll be very hard to unwrite.

The machines are learning from us. But we're learning from them too. And that's a far more profound change than any algorithm.

---
_**Want to use AI meeting tools without letting them flatten your communication?** 
[VideoTranslatorAI](https://agent.videotranslator.ai/) transcribes, translates, and summarises in real-time whilst preserving the nuance of natural conversation. It's built on the principle that AI should adapt to humans, not the other way around. Because the best tools amplify what makes us human rather than training us to sound like machines._

## Read more
- [I Rested. Then Shipped An App in 72 Hours. A Story about TrustPRR](https://videotranslator.ai/blog/i-rested-then-shipped-an-app-in-72-hours/)
- [A Doctor Told Me Something Haunting](https://videotranslator.ai/blog/a-doctor-told-me-something-haunting/)
- [If Translation Is Now Free, Why Pay at All?](https://videotranslator.ai/blog/if-translation-is-now-free-why-pay-at-all/)

AI isn't just changing how we write. It's rewriting how we think, speak, and connect with each other. 

You Sound Like ChatGPT Now 

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Elephant Stripes is a consulting firm that designs, builds, and ships AI products and delivery systems.