The One Decision That Cost InVideo a Year

In January 2025, Sanket Shah and his co-founder were sitting in San Francisco, talking through a fork they both already knew the answer to. Their insight - the one that had taken InVideo from $10M to $70M in revenue - was expiring. The market was shifting under them. The honest move was to drop the existing strategy and bet the company on the next insight. They didn't take it.

Twelve months later, on the Z47 Moments podcast, Sanket called that single non-decision the most important thing that happened to InVideo all year. Not the shipping pace. Not the marketing spend. Not the AI roadmap. The decision they didn't make.

That story sits inside a worldview about how companies actually grow that's worth taking seriously - especially right now, when AI is collapsing and re-creating product-market fit on a six-month clock.

Insights, not optimizations.

Sanket's frame is simple: every business has a single load-bearing insight. The product, the architecture, the culture, the people you hire - all of it organizes around that insight. Without one, you don't have a company; you have a feature competing on price.

He distinguishes insight depth. L1 insights are surface-level - "creator economy" was his - and they get you to maybe $10M. To break through, you need an L3 insight that's actually hard to copy. For InVideo, the L3 insight that drove the $10M-to-$70M run was video editing, not just generation. Specific, not generic.

The corollary is the part most founders flinch from: optimization cannot break a ceiling. If your business has hit one, no amount of A/B testing the funnel or shaving CAC is going to move you. Only a drastic re-orientation around a new insight can. And drastic, by definition, means the existing status quo gets blown up.

Insights expire.

This is the part that should keep AI founders awake. Sanket's view of product-market fit is that it's a spectrum, not a binary, and the score moves on you. A 9-out-of-10 PMF today can be a 6-out-of-10 in six months because someone else found the next insight while you were still defending the current one.

In an AI market where new capabilities open up every quarter, a new entrant has a structural advantage: they're building from what's possible today, while incumbents are stuck inside an architecture and a worldview optimized for last year's possible. That's why the January meeting mattered. They could see the expiry coming. They chose to keep shipping inside the old frame instead.

How to read customers without being lied to.

Most of the conversation founders have with customers is wishful theater - leading questions, hypothetical futures, customers offering solutions back. Sanket's discipline is brutal:

• Only ask about the past. What do they actually do today? Never "would you" or "what if."
• Never accept their solution. The solution is the founder's job; the problem is the customer's.
• The framework is from The Mom Test - and he treats it less as advice and more as a hard rule.

This is how he separates signal from noise. Speculation, including the customer's own speculation, is noise. Behavior in the past is signal. Everything else gets filtered out.

When the bet isn't working, stop watching it.

This was the most counterintuitive operating principle in the conversation. When momentum dies, most founders stare harder at the dashboards - refreshing retention, revenue, signups, hoping for a turn. Sanket does the opposite. He stops looking entirely. Two to four people get assigned to keep the current business running. He goes all-in on the next bet.

He paired this with a cash discipline most founders don't have the stomach for: when his views-to-signup ratio drops below his bar, he kills marketing. Not throttles - kills. The cash he conserves becomes the runway for the next bet. "I have one more bet in me. If this one doesn't work, I have one more. I have to make one of them work."

The takeaway.

The pattern is a loop, not a ladder. Find an insight. Build the company around it. Ride it until it expires - and it will expire. Recognize the expiry early. Take the painful pivot before the ceiling becomes a floor. Conserve enough cash to survive the gap. Repeat.

The cost of getting this wrong is rarely a crash. It's a year of hard, well-executed, perfectly-shipped work that didn't matter. Which is exactly what Sanket says happened to InVideo last year - and why he's telling the story now.

Source: The Insight of Differentiation: Sanket Shah's InVideo Journey - Z47 Moments

The Information Mover Is Dead. The Builder Just Got the Keys.

There are more open product manager roles globally right now than there have been in three years. The last time the number was this high was peak COVID. So why is half of your LinkedIn feed full of laid-off PMs?

Because the job split in two and nobody told the loser.

Nikhyl Singhal — ex-Meta, ex-Google, ex-Credit Karma CPO, and the guy who runs the Skip community of 125 sitting heads of product — calls this a "complete renaissance for the product industry." But it's a renaissance with strings. The strings are: if you built your career as an information mover, you are the dinosaur. If you built it as a builder, you just got handed a vault.

Here is the bet he's making out loud: in the next twelve to twenty-four months, large companies will shed thirty thousand and rehire eight thousand. The eight thousand will be AI-first. The thirty thousand will be the people whose entire job was to take a deck from one boss, reframe it for the next boss, run the standup, write the status report, manage the backlog, and drive “alignment” through theatrics. That entire job description has been quietly automated. Nobody put up a sign.

The split. About half the product industry got into product because they liked moving information through organizations. The other half got into it because they liked making things. The first group is being shed. The second group is having the time of their lives — they have more offers than they've ever had, comp is at all-time highs, and the wall between PM, founder, CEO, and even non-product C-suite roles is dissolving. Singhal has fourteen sitting founders inside his community of 125 today. Twelve months ago there was one. He recently watched a senior member interview for a Chief HR Officer job because the company decided they wanted a product builder running HR.

That last detail is the real signal. Forward-leaning companies have started believing the obsolescence skill — the instinct to look at any manual workflow and write software around it — is more valuable than the function it's being applied to. The function is easier to learn than the skill.

The shadow superpower. Here is the cruel part. The people who are best at the old game are the slowest to adopt the new one. Their entire identity says what I do is working. Their employer agrees. Their bonus agrees. So they don't reinvent. Meanwhile the weaker performer — the one who was already struggling — has nothing to defend, opens Claude Code on a Saturday, ships something silly, catches the bug, and a year later is the most valuable person on the floor.

The block isn't intelligence. It isn't even taste. It's time. The mid-career person in their thirties — the one with the most leverage on paper — is in their power years for everyone else too. Aging parents. Small kids. A spouse. The first body aches. A career that demands constant relearning at exactly the moment when no one has a free hour. Singhal's framing for what your daily prioritization actually is: “I am going to equally disappoint everyone.” That is the honest math. And on top of that math, the industry is now asking you to spend your nights “feeding the LLM.” That is why the most predictable casualty of this era is going to be the diversity progress of the last five years. The Bay Area pace tax falls hardest on whoever already has the least slack.

What the new job actually looks like. Less moving information. More judgment. Judgment meaning: when ten ideas can be tested for the cost it used to take to test one, somebody has to decide which of them deserve to ship — what's good for the brand, the system, the long-run product. That somebody used to be in a meeting. They are now in their IDE.

The PMs Singhal sees thriving have one thing in common: they obsoleted a part of their own job. They built a chief-of-staff app. They wrote an agent that does the matching their community needs. They replaced their status reports with software. They got rid of the meetings they hated by automating the work the meetings were supposed to coordinate. That single moment — the first thing they ship that makes them go wait, this works — is the conversion event. Joy is the antidote to burnout, and most product work has been joyless for a decade. Building is joyful. Once a PM crosses that line, the energy comes back, the time appears, and the rest is mechanical.

Three things that are about to be true.

One: brand on your resume is depreciating fast. Six years at a name-brand company that builds the old way is now a liability in the room. Nobody asks “where did you ship?” They ask “what tools, what judgment, what would you build right now?” If your answer is a 2021 answer, you don't get the job.

Two: this is not a thirty-year treadmill. Singhal is firm on this. The next two years are chaos because every operating system of building software is being rewritten in real time. After that, things settle. There will be a new normal. There will be training programs and predictable tracks again. The activation energy is now. The merry-go-round does not spin forever.

Three: PMs are about to invade every other industry that runs on legacy software — which is most of them. The HVAC company a private-equity firm just bought. The school district. The mid-market manufacturer. They are all going to need someone who can walk in, look at how things are done, and obsolete the manual parts with software. The supply of those people right now is roughly equal to the population of the Skip community plus a few thousand others. Demand is the entire economy.

The one decision. If you love building, stay current — relentlessly, even at the cost of every other comfort, for two years. If you don't love building, be honest with yourself early enough to do something about it. The middle path — wait and see, hope it stabilizes, lean on the brand on your resume — is the path that gets shed in the round of thirty thousand.

Smiling exhaustion is the new floor. Exhausted-but-not-smiling is what comes next if you don't move.

Source: Nikhyl Singhal on Lenny’s Podcast — Why half of product managers are in trouble

Token Anxiety

Gym membership you never used. Buffet plate you couldn't finish. Data that rolled over and died.

Now add: tokens you didn't spend.

Token anxiety is subscription guilt's newest dialect — the nagging sense that every unused prompt is cognition you were entitled to and forfeited. You open Claude at 11pm not because you need anything, but because you haven't queried enough today.

The psychology is old. We've always confused access with use, and use with value. What's new is what's being metered. Not calories. Not bandwidth. Thinking itself. And once thinking is priced, not-thinking starts to feel wasteful.

The irony writes itself: the person who uses AI best is the one who doesn't feel compelled to use it at all. They pick their spots. They ask the one question only they need answered. They let the meter idle without flinching.

Token anxiety is the tell of someone who has mistaken the tool for the output.

The Only Game Worth Finding

Ask yourself two questions.

What kind of game do I love playing?

What kind of game can I play all my life?

Find where those two answers overlap. That's it. That's the whole thing.

Because here's what happens when you find it.

You show up every day. Not because you should. Because you want to. The work doesn't feel like work. The hours don't feel like hours. You're not waiting for the weekend or the exit or the retirement.

And while you're busy enjoying it, something quiet happens in the background. Time compounds. Skill compounds. Reputation compounds. Relationships compound.

Ten years in, the rewards aren't big. They're incalculable.

Most people miss this because they split the question in two. They pick a game that pays, and hope they'll learn to love it. Or they pick a game they love, and hope it'll pay. Both fail. One burns you out. The other starves you out.

The trick is refusing the split. Keep looking until you find the overlap.

And when you find it, the reward isn't what waits at the end.

The reward is every single moment of the path.

Two Kinds of Judgment. Most People Can't Tell Them Apart.

Every decision you make is either becoming a rule — or it needs you present every single time.

There is no middle ground.

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Fossilized judgment is stable. You've made this call enough times that the answer is predictable. Encode it. Systematize it. Automate it. Let it run without you.

Live judgment is still moving. The context shifts. The stakes are high. New information changes the answer.

Encode this — and you don't get automation. You get a confident, consistent, wrong machine.

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The Trap

Most people fossilize too early.

They take a judgment that was working because someone sharp was making it fresh each time — and they write the playbook. Build the process. Ship the agent.

For a while it looks like scale. What it actually is: yesterday's thinking, running at tomorrow's speed.

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The Filter

Two questions. That's it.

1. Is the underlying truth still moving?
2. What happens when the answer is confidently wrong?

Stable truth + survivable error = fossilize it.
Everything else = stay live.

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This Isn't New

Great managers already do this. They push routine calls down and hold the contextual ones close.

The law does it. Statutes are fossilized judgment. Judicial discretion is live.

AI just removed the friction that used to slow you down. Building an agent now takes an afternoon. That's extraordinary leverage — and leverage doesn't care whether you encoded something smart or something stupid.

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The One Thing

Sort your judgments before you automate them.

Fossilize the stable ones. Revisit them on a schedule — the world moves, and yesterday's rule becomes tomorrow's liability.

Stay live on everything else.

The judgment you can never automate is the one about what to automate.

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Get that one wrong and you don't scale your business. You scale your blind spots.

SOPs Are the Ceiling

If you can SOP it, you can automate it. If you can automate it, you can hand it to an agent. Spin up thirty specialized agents, run them in parallel — suddenly one person runs an organization.

True. Also incomplete.

The bottleneck migrates

With one human doing five things sequentially, the sequencing is implicit. They just know what's next. With five agents running in parallel, something has to decide what each one consumes, where outputs land, how conflicts resolve, and what gets escalated back to a human.

The work doesn't disappear. It moves. From doing to orchestrating.

That's where the real IP sits in an agent-heavy system. Anyone can stand up agents. Very few can orchestrate them well.

The SOP is the ceiling

A vague SOP makes a vague agent. A sharp SOP makes a sharp one.

The specialization isn't in the agent. It's in the crispness of the SOP it's running.

Most "our AI agent didn't work" stories — when you dig — aren't agent problems. They're SOP problems. The team never had a real SOP. They had a vibe. They handed the vibe to the agent. The agent returned a vibe. Everyone called it an AI failure.

Before you build an agent, write the SOP as if a new hire on their first day had to follow it. If you can't write that document, you don't have a process. You have a habit.

Not everything SOP-able should be agent-ified

Build cost + maintenance cost + debugging cost has to beat just doing it.

For high-volume repetitive work, this is obvious. For low-frequency judgment calls, the agent is a tax. You'll spend more time maintaining it than you'd have spent doing the task.

Two questions before you build anything:

• How often does this run?
• How stable is the underlying judgment?

Fossilized vs. live judgment

Every judgment in your business falls into one of two buckets.

Fossilized judgment is stable. The world has stopped moving around it. You've made this call a hundred times and the answer rarely surprises you. Safe to encode. This is what agents are for.

Live judgment is still moving. The inputs shift, context matters, the stakes of being wrong are high. Encoding this is dangerous — you freeze a decision that needed to stay dynamic, and the system quietly rots.

The mistake is treating these as the same. Founders either refuse to fossilize anything (stay trapped as the bottleneck) or fossilize everything (ship a system that's confidently wrong six months later).

The real unlock

The unlock isn't "build lots of agents."

It's figuring out which judgments have stabilized enough to fossilize, SOPing those ruthlessly, and keeping yourself in the live-judgment loop for everything else.

The meta-layer — orchestration above all the agents — is how you stay in that loop without touching every decision. It surfaces the live stuff to you. Handles the fossilized stuff without asking.

Automating judgment is the point. Automating the wrong judgment is how you scale your blind spots instead of your business.

Pick what you fossilize carefully. That choice is the one thing that can't be delegated.

 If you can SOP it, you can automate it. If you can automate it, you can hand it to an agent. Spin up thirty specialized agents, run them in parallel — suddenly one person runs an organization.

True. Also incomplete.

The bottleneck migrates

Now my job is to get things done .. i don't need to do it personally now

 Now my job is to get things done .. i don't need to do it personally now