I made my own onboarding document during a call.

There wasn’t one. So I asked every question I had and typed the answers straight into a Google Doc while the other person was still talking. Not clever. It was just the first time any of those answers existed outside somebody else’s head.

That doc got me through my first month.

I assumed that was a new-person problem, nothing more.

Then I watched a founder years into his own business do a much bigger version of the same thing, in three minutes.

The list that was never waiting for time

One founder came in with 1,200 lines: blog ideas, to-dos, market observations, things he’d meant to follow up on and never had. He’d been meaning to sit down and sort it for weeks. Minutes after pasting it in, it came back structured, prioritised, turned into something he could actually use: “It’s actually done what I wanted it to do, what I was going to ask it to do next week.”

The easy read is that AI made him faster. That isn’t quite it. He was never short of an afternoon. He was the only person in the business who could make sense of those 1,200 lines, and a list like that sits there for years waiting for its one qualified reader to be free.

The number six months couldn’t produce

The same thing happens on bigger questions. One founder came in with something he’d been circling since the start of the year: his North Star metric, the single number that would tell him whether the business was actually working.

What he said after one session: “I never boiled it down to something so simple.”

Nobody handed him an answer. He got asked the same question from enough angles that the only version left standing was the one he’d been avoiding.

You still decide

Worth being clear about this, because the workshops are unusually blunt about it. The system offers options, weighs trade-offs, makes recommendations. It never makes the final call. That stays with the founder, every time.

Most founders aren’t short on ambition or effort. What’s missing is something that makes you finish a sentence you’ve been starting for half a year.

If you’ve got one of those rattling around your head right now, you’re probably one direct conversation away from being done with it. Not six more months of thinking about it.

That’s what the BoS OS Workshop is for. Two 120-minute sessions, 12 people max, and you bring the question you’ve been avoiding.

At Business of Software USA, Ivan Barajas Vargas, CEO and co-founder of MuukTest, walked through the findings from five of the most cited academic papers on AI in development. The picture: speed and efficiency aren’t the same thing. Code that requires endless review, security audits, and refactoring costs more than it saves.

The problem is how teams are using the tools.

Tool Overload Hides Real Security Risks

There are now hundreds of AI coding tools on the market: Cursor, Copilot, Claude, GitHub’s own offerings, plus specialised tools for every framework. Most teams pick one by gut feel, try a second, and end up running both in production.

That’s shadow AI: unauthorised, unvetted tools loose in the development workflow. A sales intern tries a new tool to “help.” Each one opens its own security surface.

The real risk is copy-pasting credentials into a system nobody’s vetted. Once that data leaks, it’s gone.

The fix: pick one stack and enforce it. Write standards. Any team can write a prompt, but the good ones write guidelines for how AI gets used in development, with input from business and product, not just engineering.

“It’s Like Using a Chainsaw”

That’s how Ivan puts it: AI coding tools are powerful in trained hands and a mess in untrained ones. Auto-complete, refactoring, scaffolding, root cause analysis, they all work, provided someone actually knows what they’re doing.

AI generates thousands of lines of code, most of it syntactically fine and conceptually plausible. Until you dig in and find APIs that don’t exist. That’s built into how these models work: they extrapolate from training data, and sometimes the extrapolation is fiction.

That’s tax.

The fix is context. Load your RAG system or vector database with documentation, architecture decisions, and code standards. Test performance regularly. Don’t assume generated code scales just because it compiles. And keep reviewing outputs: the more your team generates with AI, the more a senior developer ends up validating.

When my team ships faster with AI but I’m not sure code review is keeping pace, I want to know whether the tool is the problem or whether we skipped the guardrails.

The New Job Description: Full-Time Reviewer

Senior developers are reviewing five times more code than before AI entered the workflow. A junior developer with AI generates more code, faster. But every line needs review, testing, and validation. And the people you actually need for architecture, mentorship, and strategy are stuck validating what the junior team generated.

More code doesn’t mean better code. AI writes like a junior developer: a lot of output, some of it buggy, most of it immature. Tech debt compounds.

The burnout point is the one worth sitting with. A tool that’s supposed to save time is quietly taxing your best people, and most teams haven’t noticed because the dashboard still says “faster.”

The fix starts with acknowledging the shift: AI tools multiply senior workload, they don’t eliminate it. Monitor that load. And assign ownership: if someone is responsible for vetting the AI, integrating it, and maintaining standards, the workflow stays manageable. If no one owns it, it metastasises.

Treat AI Like a Chainsaw

The teams getting real value from AI aren’t treating it as a replacement for architecture or strategy. They’re treating it like a chainsaw: powerful, but only in trained hands with the guards on.

That means picking one tool and committing to it. Writing standards. Feeding the system context. Testing for performance. Instrumenting observability from day one, so you know why things break. Naming owners. Watching developer load so your senior people don’t burn out reviewing everyone else’s output.

It also means accepting where vibe coding belongs: prototypes, mockups, small features. Not the core architecture of a fintech platform or a healthcare system. There, AI scaffolds and refactors. It doesn’t decide.

The vibes are only off if you skip the integration work and hope for the best.

Chris told this story at BoS USA 2025, alongside Chris Lavigne, Wistia’s head of production and a 14-year employee, in a fireside conversation about what actually happened after they turned the deal down. The headline decision is the memorable part. Proving it was the right call took the next five years.

Why founders say no to the pot of gold

Three companies approached Wistia about buying the business in 2017. Chris and his co-founder, who’d always turned those conversations down before, said yes this time and got deep enough in to land a real offer. While making a list of everything they’d do after selling, they realized the list was just Wistia again, the same people, the same problems, rebuilt from scratch. That was the moment they admitted to each other they were actually unhappy with how they were running the business:

• chasing growth at all costs
• saying yes to ideas without ever asking what to stop doing
• accumulating what Chris calls zombie projects that stayed alive because nobody asked if they should.

Raising to serve growth, not to search for it

Turning down the offer left an open question: what to do about the roughly 1.4 million dollars already raised from angel investors, and the liquidity everyone had been promised someday? The answer was the 17 million dollar debt round, structured so early investors and employees could choose to take cash now rather than wait for an exit that wasn’t coming. Chris’s framing for founders weighing a raise: are you raising to search for growth you don’t have yet, or to serve growth you already know how to produce. Pre-product-market-fit, you may need outside capital and want the smallest raise you can get away with, since that dilution is the most expensive you’ll ever take. Already know what works? Wistia funded a chunk of its own growth just by switching the default payment plan from monthly to annual, and the debt round was the more dramatic version of the same idea: borrowing against a business they understood, rather than diluting further or selling outright.

Independence didn’t automatically buy speed

The buyback bought Wistia the right to set its own terms. It didn’t automatically buy a fast product org. By 2021, flush with profit and conviction, Wistia doubled its product and engineering headcount from 50 to 100 people in a single year, fully self-funded. Shipping got slower. By October 2022, Chris stopped assuming the fix was more people and asked a harder question: what if the bottleneck was his own review process, where every roadmap ran through him first and the best-organized deck won, not the one that shipped the most customer value.

The fix was structural: all 13 product teams got full ownership of their own roadmaps, judged on a single measure, shipping real customer value every two weeks. A tagging feature scoped at six months under the old process shipped in two weeks under the new one. Product releases went from 12 a year to 70, then 130, with no change in team size.

The through-line across both moments: the buyback bought Wistia the right to set its own terms. Making that worth anything meant being honest, twice, about where the business was actually stuck, and changing the structure rather than pushing harder inside the old one.

Watch the full talk, including the equity program, the hiring pendulum, and the Q&A on OKRs and product structure.

I nodded along the first few times Mark said this without actually understanding what he meant. He thinks of the BoS OS as “a way of finding the co-founder you never had who is almost the exact opposite of you.”

What changed my mind was sitting in the workshops and hearing founders say the same thing back to him, in their own words, without being asked.

Dom Reed got there working through the mission planner with his co-founders, one session, one shared screen. What struck him was the probing. By the end he called the whole thing “proper therapy.”

Nobody in that room was being lazy

I know this one from the other side. I joined BoS and inherited systems nobody had time to walk me through. Nothing written down anywhere. Not because anyone was careless. Because the people who built it never had to explain it to themselves.

That’s the pattern the workshops keep surfacing: founders who aren’t short on effort, just short on someone forcing them to say the quiet part out loud.

The agreeable ones are much less useful

A co-founder worth having sits on a position you haven’t considered and stays there until you deal with it.

Tim Barker builds that instinct into the architecture itself. Alongside the agents that do the work, he runs guardians whose only job is to check the ones producing it, built specifically so nothing optimises for growth at the cost of trust or economics.

That’s the whole point. An assistant that only agrees with you isn’t a co-founder, it’s a mirror.

The bridge nobody quite has yet

Even the founders furthest along keep hitting the same wall. Robert Fryers put it plainly, four weeks in: the bit he’d pay more for was “the bridge between a consistent source of truth for multiple people and rolling this out to the team.”

That’s not a small ask. It’s the same instinct, pointed at a harder problem: not just a counterweight for one person, but one the whole team can trust.

If you’re running on instinct and a very full head

I’m not a founder. But my first months here ran on instinct and a head that was far too full, and what helped was having something in the room that wouldn’t let me leave a decision half-made.

If that sounds like your week, sit with it for a minute. Not because you’re doing it wrong. Because the arguing part is the bit you’re missing, and it’s the one thing you can’t do on your own.

The BoS OS Workshop is two 120-minute sessions, capped at 12 people, for founders who’ve already got a first-draft OS and want it to hold up when something pushes back.

Matt Lerner told the story at BoS Europe 2026. Elemental Software made a WYSIWYG website builder, drag and drop, connect to a database, right in the middle of the dot-com boom. The CEO hired a professional comedy writer and sent Lerner’s team to executive conferences to perform fake product demos in front of the room’s most important investors, on the theory that laughter would translate into offers.

The first attempt was Atonement.com, a fictitious confession website where visitors could enter their sins and receive an appropriate penance. They performed it straight after Steve Forbes, then running for the Republican presidential nomination, used his dinner speech to describe an abortion procedure in graphic detail. “Worst warm-up act ever,” Matt said. The room was tense enough that the comedy demo landed hard. It got laughs, business cards, no offers.

The second attempt raised the stakes: a fake site where you could start your own religion, complete with two original songs from a hired composer and a professional singer performing live on stage. Again, the room loved it. Again, nobody bought the company.

The third attempt is the one that worked. Matt’s co-founder, Peter, went through the attendee list ahead of time and built the demo around the people in the room, giving investors like Mary Meeker and Vinod Khosla actual speaking parts in a fake IPO pitch. After the show, the chairman of the board of Macromedia walked up to Peter and said, “We’re actually looking to buy a company in your space. Can we talk?” Negotiations followed, backed, by Matt’s account, by nothing more sophisticated than a yellow copy of Negotiating for Dummies on Peter’s desk. The deal closed at $20 million.

That would be a fine story on its own. What makes it worth telling is what happened next. Matt joined Macromedia as part of the acquisition and was handed a cubicle previously occupied by someone else, complete with a shelf of abandoned binders. Cleaning them out, he found a board memo: the proposal to purchase Elemental Software, authorizing Macromedia to pay up to $78 million. His company had sold for roughly a quarter of what the buyer was prepared to spend.

He told Peter that night at dinner. Peter’s reaction was one word, followed by stuffing the memo into his laptop bag and telling Matt never to mention it again. Matt kept that promise for 25 years, until he caught up with Peter over the most recent Christmas and got released from the arrangement, on the condition that he tell the whole story, memo included.

The lesson isn’t really about comedy demos, though those clearly worked as a way to get noticed in a room full of people who’d seen every standard pitch before. It’s about the gap between getting a company bought and getting it bought for what it’s worth. Differentiation, memorability, and nerve got Elemental Software an offer that a conventional sales process hadn’t produced in two prior attempts. None of that told the team anything about how much room the buyer actually had. Only a forgotten memo in an old cubicle answered that question, and by then the deal was already signed.

Watch Matt Lerner’s full talk to hear the whole thing, including the specific line that made Peter swear him to secrecy.

That was the starting point for Chika Emebo and Mark Stephens at Business of Software USA 2025, in a talk about running a team that spans four generations, Baby Boomers, Gen X, Millennials and Gen Z, often in the same room, sometimes reporting to a boss the same age as their own child.

Mark, who runs UK software company IDRsolutions, and Chika, a Gen Z member of his team, built the talk as a back-and-forth between their two generations rather than a lecture from one. The point wasn’t that generational differences are a problem to manage around. It’s that they’re the raw material for a better team, if you’re deliberate about it.

Your team should feel like the wrong crowd

Mark’s argument for hiring across generations rests on a simple test: if hiring is done right, walking into your team for the first time should feel like you’re the normal one among a group of slightly odd misfits. A team isn’t a friend group. It’s built from people with complementary skills you wouldn’t naturally choose to hang out with, which is exactly what makes it work.

He points to the Beatles. John and Paul argued constantly and wrote the songs everyone remembers. George Harrison wrote “Here Comes the Sun,” now the most streamed Beatles track, ahead of anything Lennon-McCartney produced. And Ringo Starr, by his own admission not the best drummer in the world, or even in the band, was the ingredient that made the group work. When he left, the others asked him back. Every strong team, Mark argues, needs its Ringo: the person who isn’t the obvious star but holds everyone else together.

Culture without the emotion

The most practical idea in the talk borrows from Bob Moesta’s jobs-to-be-done framework, applied to people instead of marketing. Every six months, Mark sits down with everyone on his team and runs through a simple pushes-and-pulls conversation: what’s pushing you away from this job, and what’s pulling you toward it. Doing it with everyone, on a schedule, strips out the fear that normally comes with “can we talk.” There are good reasons to leave a job, wanting to move from a small company to a bigger one, and bad ones, feeling disrespected or unable to use your skills. The framework exists to tell the two apart before they turn into a resignation.

Chika’s answer, when Mark asked how a business selling PDF conversion software (not curing disease, in his words) gives Gen Z the meaning they’re often accused of demanding, was more specific than the usual “purpose” answer. She wants a safe space to make an impact, to see her ideas taken seriously and have the results reach customers, plus the autonomy to be herself outside strict role boundaries. The skills she’s picked up in the office have paid off directly: one brand partnership from her side work as a content creator was worth over $2,000, funded by communication skills she says she wouldn’t have built without the job.

Small things signal culture

The talk’s smallest example carried its biggest point. Mark’s office got asked to bring in their own milk. One team member spent a Saturday designing “milk monitor” badges as a joke, and now everyone wears one. The badges aren’t the point, the fact that the whole office is in on the joke together is. He contrasts that with humour that splits an office into two camps, which he calls a straightforward sign of a toxic culture.

The same logic runs through his advice on self-expression: let desks look different, let laptops carry different stickers, ask new hires directly how they like to work and receive feedback rather than assuming. Demand conformity all day and then ask people to be creative in a meeting, and you’ll get nothing, because you’ve spent all day training the creativity out of them.

None of this replaces the harder structural questions a mixed-generation team raises, hybrid schedules, who works from where, how much autonomy is too much. A Q&A question from the audience about a Gen Z developer who wanted to work from Spain all summer got a blunt response from Mark: if someone doesn’t want to be in the office, the more useful question is whether you’ve actually sold them on why being there is worth it.

The full talk, including the audience Q&A, is available on the BoS site.

They spend their coffee meetings with the same core circle, people they already know and trust. It’s comfortable, but it’s also where the time gets wasted.

John Knox, in his lightning talk at Business of Software USA 2025, put it plainly: “The edges of your network are the most valuable part of your network. Yet most people spend all their time on the core.”

When John ran an event for med tech startups, he reached out cold to eight founders he’d never met. Seven said yes and ended up speaking at his event, despite having no prior relationship with him and no particular reason to trust his outreach. The leverage was never in his existing contacts. It was in the people he hadn’t talked to yet.

Networking Is Not Sales (or Small Talk)

Founders often conflate networking with sales, assuming it means pitching, small talk, and conference badges. John draws the line simply: “As soon as you talk about prices or establish yourself as a seller and someone as a customer, that’s sales, not networking.”

Networking is the work of building relationships around shared interests and mutual opportunity. “A network is something you do something with,” he says. “It’s interactive.” The moment you’re positioning yourself as the seller and someone else as the customer, you’ve left networking behind.

You don’t need to be in the room to do it, either. If you can only make it to one event a year, Zoom fills the rest of the gap. On outreach itself, John’s advice is specific: “Explain why you’re contacting them. Show respect, maybe flatter them. Prove you’ve done some research and you’re not a bot… Keep it short. Nobody wants to read a novel.”

Two Modes: Use and Expand

John describes two ways to work a network.

One is using it: you have a problem or an opportunity, and you lean on people you already know to help you move forward.

The other is expanding it: you have a direction you’re heading, and you go looking for the people who can help you get there. CEOs often come to John for strategic advice, but he points them somewhere else. The best intelligence comes from the market itself, from talking to the founders you’re trying to learn from and the customers you’re trying to serve. Your existing network will mostly confirm what you already believe. The edges are more likely to tell you what’s actually true.

For the Introvert: Speak Without Hedging

If you’re an introvert, and John counts himself as one, this can feel exhausting. It’s learnable anyway. His first piece of advice: speak confidently about your own work. “I’d hedge or underplay my achievements, and it shows a lack of confidence to people,” he admits. “It undermines whatever you’re trying to achieve.”

From there it’s a matter of showing up, one conversation at a time. Meet the person standing next to you. Help someone find their way around the conference. Make an introduction. Suggest a follow-up call. None of it feels like much on its own, but each small move fills in more of the map.

The Tree Model

John’s last framework: picture your business as a tree. The branches are your business model, product, and market. The roots are your network, and as the tree grows, the roots need to grow with it, into the same new directions.

That work looks nothing like coffee with people you already know. It’s reaching out to strangers and asking for their help, which is uncomfortable by design.

As John puts it: “If you invite the right people to participate in an ambitious project, many people will say yes. Just ask Obi Wan.”

The ChatGPT group could recall 83% less of what they had supposedly just written, nearly every student in that group, and they reported a much lower sense of ownership over their own work.

Georgiana Laudi, co-founder of Forget The Funnel, used that study in her talk at Business of Software USA 2025 to make a point about SaaS go-to-market strategy: the same thing is happening inside marketing and growth teams right now, and it’s quietly undermining their ability to make good decisions.

Her talk wasn’t really about AI. It was about three things she believes are the actual source of the disruption founders are feeling, and none of them show up on an AI roadmap.

#1: Your customer’s problem hasn’t stayed still

Understanding your customer is not a new idea, and most founders would say they’ve already done this work. But the research most teams did even a year ago is already out of date. Gia pointed to three examples from the last twelve to eighteen months: –

• Klarna rolling out an AI assistant and cutting headcount equivalent to 700 support agents
• Zoom and Google shrinking the market for tools like Otter with built-in AI meeting summaries
• Notion and Canva eroding demand for writing tools like Jasper with AI features baked into products people already use.

Budgets have shifted, roles have changed, and your champion buyer inside a customer account might not be who they were a year ago. If your last round of customer research predates this, it’s telling you about a customer who no longer exists.

#2: There’s a gap only your team can see

Gia’s team ran a study asking founders and their employees what was keeping them up at night. Founders talked about strategy: repositioning, messaging, product gaps. Not one mentioned team alignment. Nearly every employee did, describing the exact same frustration in different words: nobody seemed to know what the company was trying to achieve or who was deciding. The average company in the study had $2.5 million in ARR. These were not scrappy two-person startups without the resources to communicate. The gap wasn’t new, but it’s widening, and founders are usually the last to notice because they’re the only ones who can’t see it from inside their own team.

#3: Understanding is what gets you unstuck

Gia described this state as strategic quicksand: hard to recognize until you’re stuck, more activity making it worse rather than better. Her clearest example was Bitly.

Two hundred employees, $100 million in ARR, 6 million users, a company that had quietly expanded from a link shortener into a multi-product platform without anyone translating that shift into a shared plan. Every team solved for its own version of the opportunity, and customers ended up with a disjointed experience stitched together from marketing, product, and sales.

The fix wasn’t a new campaign or a rebrand. Bitly’s team identified three real customer segments and made a deliberate trade-off to build their entire go-to-market strategy, messaging, onboarding, and even parts of the product roadmap, around the two that mattered most. One of those segments turned out to have three times the retention of the other, a fact the product team only found once the whole company was working from the same understanding of who they served.

None of this requires a bigger budget or a different AI tool. It requires putting in the work AI can’t do for you: understanding your customer’s changed reality, closing the gap between what leadership sees and what the team is living, and building that understanding into something the whole company shares.

Gia’s full talk goes deeper into how to operationalize this, including two more customer examples and a practical framework for keeping a team aligned as things keep changing.

Next Events

By 2019, the company was ready to sell. Several offers came in, and Raj was deep into the checks a private equity buyer runs before signing.

The Monday Before Christmas

Super Salon’s largest customer announced it was building a competing product. The buyer pointed to the material adverse change clause, the part of the contract that lets a buyer back out if something big goes wrong before signing, and left.

You can do everything right for four years straight, and still lose the whole thing to one decision somebody else made without asking you.

A few months later, a whistleblower came forward. That same customer had reverse-engineered Super Salon’s database and taken its intellectual property. Raj offered to buy them out nut they told him they’d rather bleed him dry in legal fees, so he sued.

There’s unlucky, and then there’s this bad timing you can shrug off. Getting robbed by the same customer you’ve been serving for years is harder to make peace with.

April 2020

Haircuts were declared non-essential. Super Salon went from serving 10,000 locations to almost none. Inside days, 70% of the company’s revenue was gone. Around the same time, the competitor that had taken its IP raised $150 million from Tiger Global.

He lost 70% of his revenue in days. In the same stretch, the people who robbed him were handed $150 million. I don’t know how you carry both of those at once.

“It Wasn’t the Strategy That Held Us Together”

Raj got vulnerable with his leadership team, by his own account for the first time ever. He had no idea what they would say back. Nobody on the hundred-person team left.

“It wasn’t the strategy that held us together,” he said. “It was the culture. The openness. The honesty.”

He built that culture years earlier with none of this in mind. He was just trying to run a good company. That’s the thing that held when everything else stopped working.

The Settlement

Raj had a real shot at winning the lawsuit outright, but the courts were closed and the timeline was anyone’s guess. Fighting indefinitely meant burning cash and attention the business didn’t have to spare. So he split the company in two, settled one side and sold the other.

Everyone made money, and the team and customers who stuck it out came out protected. It was a smaller ending than the one he had spent four years building toward.

“I Love Creating Culture”

Raj closed his lightning talk with four things he took from the experience.

• You fall to your habits, not your ambitions, when you’re tested.
• Opportunity cost shows up in small daily decisions more than big ones.
• Process is fragile and rarely smooth, so build it while things are good rather than when you’re already burned out.
• And know your why.

“When things were darkest, I got out of bed because I love building people,” he said. “I love creating culture. I loved the impact we had – ten thousand locations times eight stylists times a hundred customers a day. We touched billions of people.”

The habits point is the one I’d actually act on. Ambition is what got the company to a deal in the first place. Habits are what were still standing after it fell apart. Worth asking what you’re building on a normal Tuesday, not just what you’re aiming at.

Next Events

Joel Gascoigne’s talk at BoS USA 2025, “Navigating a Multi-Year Decline to New All-Time Highs,” makes an uncomfortable case: Buffer didn’t start tanking because they made stupid mistakes. They started tanking because Joel followed the exact advice every SaaS expert tells you to follow.

The Playbook Trap

When growth first slowed down, Joel did exactly what the startup textbooks say to do. He decided to focus on a narrower type of customer, choosing direct-to-consumer e-commerce brands because they relied so heavily on social media. To make more money from each existing customer, the team restricted the free plan, raised the Pro tier from $10 to $15 while cutting features, and eventually hid the free sign-up option altogether. They also started building more products so they could sell customers more than one thing at a time, and hired search firms to run four executive hunts at the same time.

On paper, the early data looked good. They were making more money per customer. But their paying customer count was collapsing underneath it. They told themselves the drop was just a natural side effect of chasing bigger, pricier customers. By the time the pandemic added its own pressure, the business was in a real spiral.

Two Different Ways to Grow

It took Joel three years to see this: there isn’t one universal way to scale a tech company. There are two different ways to run one, and mixing them up is exactly how you end up squeezing a company that was never built to be squeezed. One way relies on a small number of customers who each pay a lot, get personal attention, and see their prices go up steadily over time. The other relies on a large number of customers, a simple product, a strong flow of people trying it free and slowly deciding to pay, and small, steady growth in revenue over time.

Buffer was built from day one to be the second kind of company. Forcing it to act like the first, just to chase bigger customers and higher prices, put them on a path where they were squeezing more out of a shrinking base instead of delivering more to a wider one.

Turning Inward

Before any of that, Joel hit his own wall. After the layoffs and after his co-founder left, he thought he had things stabilized. Then he burned out completely. In his words, he couldn’t get out of bed. He took six weeks off, did nothing for a while, then slowly built himself back up. It’s a pattern that shows up a lot after burnout: once someone recovers, they usually come back wanting a fresh start, wanting to change things so they don’t end up in the same place again. That’s probably part of why the decisions that followed were so personal. He’d already had to lay off ten people once. He didn’t want to be in a position where that happened again.

I keep noticing this pattern, not just with Joel. The best decisions a company ever makes rarely come from a strategy deck. They come from the worst, most personal moments a founder goes through, the ones they never planned for and can’t fully explain to anyone else. Joel didn’t get to four day work weeks or a people first culture through a growth framework. He got there because he broke down first, and decided he never wanted to put anyone else through what broke him.

That same instinct, to look after people first, is where the four day work week came from. It started in May 2020, in the middle of the pandemic, when Joel’s team was dealing with kids at home and life turned upside down. For Joel, trying it felt like an easy call. For the team, it felt almost too good to be true, a full extra day off with no cut in pay or hours squeezed into the rest of the week. They ran a one month trial, then a six month pilot, and it just stuck. It’s still how Buffer operates today, five and a half years later.

Two years after that, in 2022, the same instinct showed up again in a bigger decision. Joel stopped the executive searches. He realized bringing in more managers during a decline just added distance between himself and the actual work. He took on the direct reports himself, told the product and marketing teams who’d been stuck waiting for a new leader that they were a complete team now, and it was time to build.

They shifted the company out of just managing the decline and back into actually building again. They ran team-wide weeks focused only on shipping, to pick up speed, and finally tackled the old, avoided technical problems everyone had been too afraid to touch.

Strategically, Joel reversed the push toward bigger customers with a framework he calls Down and Wide. Down meant targeting individual creators, early entrepreneurs, and small businesses, the opposite direction of competitors like Hootsuite. Wide meant keeping the product flexible enough to handle a wide range of social channels.

They brought the free tier back as a core part of the business instead of something hidden. They changed the main button on their homepage to send visitors straight to free sign-up instead of a pricing page. Monthly sign-ups jumped from 65,000 to 85,000 almost immediately.

Back to All-Time Highs

By matching the business to what Buffer actually was, instead of what the textbooks said it should be, the business recovered. In 2024, Buffer grew revenue by 9%. By 2025, they were back to all-time highs in paying customers, hit a healthy balance of growth and profit that most SaaS companies chase and rarely reach, and were projecting $2.5 million in net income, all while still running on a four day work week. They even started proactively canceling subscriptions for customers who were paying but inactive, on the idea that long-term trust matters more than inflating short-term numbers.

Joel nearly lost Buffer by making good calls that belonged to someone else’s business. If you’re running a company right now and something feels off even though you’re doing everything the way you’re “supposed” to, that might be your answer too. Before you copy the next piece of advice from a founder you admire, ask yourself if you’re actually building the same kind of business they are. And ask yourself, honestly, whether the people inside your company are doing okay. Buffer only found its way back once Joel stopped treating both questions as separate.

Jason Cohen’s “Escaping the Growth Ceiling” talk uses Buffer’s real churn numbers as its worked example, and Cohen’s own approved post already references Joel’s talk as a companion piece. Worth cross-linking the two once both are published.