Your manager asked for a presentation. You built it. Good one, too. Then you moved on.

Two weeks later he pings you. All good with that presentation? We’re running out of time.

And you think: is he stupid? I did it.

No. You built it and you never said so, so for fourteen days that presentation did not exist. Not to him. He carried it around, chased it, planned around not having it.

You delivered. You still cost him two weeks.

Sit with that. Being good at your job is not the defense you think it is.

Day one at the naval academy. Before a weapon, before a chart, before they let us near a ship.

You do the task. You go back and you say it’s done. Done for you and done for the person in command.

Done done.

Then you reach a bridge and learn the shape of it.

An order is four sentences. Left standard rudder. Left standard rudder, aye. Sir, my rudder is left standard. Very well.

Four legs. Miss one and the ship does not turn.

The sailor owes the third. Out loud, when it’s true. Not built. Not finished. Said.

The person in command owes the fourth. Two words, and the loop is shut.

Twenty years in tech and counting. Everybody drops a leg and blames the other side for it.

I spent thirteen years on the sending end of that protocol, and I sit on the receiving end now, where the discipline is identical and the cost is higher, because there are far more of them than there are of me and every report I leave unanswered teaches somebody that reporting is optional.

The higher you climb, the more people wait on your two words. The tax compounds upward. Nobody sends the invoice up there.

So I count it. Jar on the desk. Names, dates. Communication taxation.

There are people you tell once who hand back five. People you remind five times for one. Some of the worst offenders are excellent at the actual job. That’s what makes them expensive. Very expensive.

There’s no tool coming for this. Nobody’s building a platform for very well.

Simple things offer nowhere to hide.

Two questions. What did you finish this month and never announce. What did your people send you that you never answered.

Whichever number is higher, that’s your ceiling.

#Leadership #Management #Entrepreneurship #CTO #CEO

Two kinds. External and internal.

External is easy. A customer asks for your manager because they want to feel heard. Usually they do, and it’s settled. Simple.

Internal is where careers quietly stall. And here’s the trap most people walk straight into.

They run the internal one like it’s external. They march into their manager’s office acting like the customer, demanding a referee, expecting the boss to step in and rule in their favor.

That’s not escalation. That’s ego.

It says you see yourself as the most important thing in the room, more important than the team, the call, the company. No empathy for the person you just dumped it on. Do it enough and it fails you miserably one day. I’ve watched it happen.

Because nobody above you can make a good call on a bare problem. They need a proposal sitting next to it. “Let’s solve this together” or “I need your help getting to a solution” beats “that’s the problem, you handle it” every single time.

I spent thousands of hours of my career writing plans that got rejected. Took me years to see that a rejected plan is already a win. You moved the thinking. Enforcing your idea was never the job. Proposing it was.

People get promoted on exactly that. Bringing solutions, pushing progress, even when half get reshaped or killed. That’s the engine.

It got brutally clear after I became a CEO, even of a small team. The ones who only handed me problems lost my trust fastest. I hated it. Every leader I know hates it. We don’t get paid to admire problems.

You don’t need the title to work this way. Think like a small CEO from wherever you sit. Manage up. Bring the solution with the problem. Every time.

Drama kills orgs. Solutions feed them.

The organizations that stop moving forward die. So do the careers inside them.

#leadership #CTO #CEO #management

I came out of the Navy with no network and no safety net. Married, two daughters at 26, building from zero. So I raised my hand for the work nobody else wanted.

I’ll run that pilot nobody wants to spend time dealing with.

I’ll push that new initiative myself and get back to you in a week.

I’ll lead the security audit that demands studying what people want to avoid.

I’ll fly to the customer. The US, Australia, Europe, wherever the deal sits.

I’ll take the conference, even if it means flying out the same day and back the morning after the third.

I’ll run the partner calls after midnight, from a quiet kitchen so I don’t wake the house.

I’ll be the PM on that delivery to ensure our success. Months of it. Deliverables matrix, people to keep honest, conflicts to firefight every day.

I’ll lead the department upskilling. Mentoring, coaching, whatever moves people forward.

Every yes was a rep. Every rep forced me to get better. Harder to replace at first, extremely impactful eventually.

Saying no doesn’t make you strategic. It makes you comfortable. And comfort has never grown anyone.

Carrying the water is unglamorous. Nobody claps when you close a partner call at 1 AM. But you walk out with what this industry can’t fake in a room of talkers. Proof you can do the work.

That’s the disease. Tech is crowded with people who talk plenty and ship almost nothing. The impactful ones do both. A doer who can lead. A leader who still does.

You don’t earn that by saying no. And most execs never will. They’re afraid of the risk, so they reach for the most common excuse on earth: “I have too much work to do”. But every bit of real progress comes from people who operate differently. They don’t hide. They get things done.

Tech never settles. Business never settles. Life never settles.

Carry the water nobody wants to touch, long after it stops being fun, until it’s just who you are.

Be that one.

#leadership #CTO #CEO #careers #entrepreneurship

Last Thursday, the CEO of ClickUp, Zeb Evans, cut 22% of the company and framed the cuts as a strategy, not a cost decision. He deployed 3,000 internal AI agents to do the work the laid-off humans were doing. He promised million-dollar salary bands to the ones who stay. He named the play out loud. “100x org.” Not a cost-cutting exercise, he said. A radical bet on AI.

This is the most explicit version of the AI layoff cycle the industry has produced yet. It is also the cleanest test case of whether the framing is prophecy or wish. We will know in a year.

The Pattern Around the Edge Case

ClickUp is the loud version of a quiet pattern. Same month, three other CEOs ran the same playbook. Cloudflare’s Matthew Prince. 1,100 people, 20% of the company. Coinbase’s Brian Armstrong. Around 700 people, 14%. Upwork’s Hayden Brown. 24%. Same month. 113,000 tech jobs gone YTD across 179 companies. Layoffs.fyi counts roughly half explicitly attributed to AI. The framing converged faster than the math did. That is the tell. We have seen this movie before. Five years ago it was called COVID.

The Press Release and the Spreadsheet Do Not Match

If the cycle is familiar, the scale is new. The AI layoff narrative has become so valuable to share prices that profitable companies are cutting anyway. Cloudflare posted record quarterly revenue on the same day it announced 1,100 cuts. $639.8M, up 34% year over year, best quarter in company history. That is not a company in distress. The market right now pays more for an AI-attributed cut than for the people being cut. Prince and his board are doing what the system rewards. The cost gets paid in trust with the team that stays.

Mark Zuckerberg said the quiet part at the Meta town hall on April 30. “Getting everyone internally to use AI tools is not the thing driving layoffs.” Then he said the louder part. “We basically have two major cost centers in the company: compute infrastructure and people-oriented things. If we’re investing more in one area, then we have less capital to allocate to the other. So that means we do need to take down the size of the company somewhat.” He told 80,000 employees that they are funding the GPU bill. He absorbed the market hit instead of taking the easy reward.

Some days ago, Jensen Huang said it harder. The CEO of NVIDIA, the company benefiting more than any other from AI capex, went on Channel NewsAsia and called out the framing directly. “I think the narrative that connects AI to job loss for many of the CEOs that are doing it, it is just too lazy.” Then the timing argument that breaks the whole story. “AI has just arrived. How is it possible they’re already losing jobs? How is it possible that AI became productive and useful only six months ago, and they were somehow laying people off two years ago because of AI? It doesn’t make any sense. It was just a way for them to sound smart, and I really hate that.” When the man selling the picks and shovels says the gold rush narrative is a cover story, the cover story is over. The system is the problem. Not the people inside it.

Productivity Yes. Unit Economics No. Worldwide.

Gartner ran the audit three weeks ago. 350 global executives at companies with $1B+ in revenue, all piloting or deploying autonomous AI. 80% reported workforce reductions tied to their AI initiatives. Zero correlation between the size of the cuts and the size of the returns. Helen Poitevin, Distinguished VP Analyst at Gartner, said it cleanly. “Workforce reductions may create budget room, but they do not create return.” That is the financial verdict on the AI layoff narrative, stamped by the most cited industry analyst on the planet, in writing, four weeks before ClickUp doubled down on the bet.

Behind the headlines sits the bigger math. $725B in hyperscaler capex this year. JPMorgan: $650B in annual AI revenue needed in perpetuity to deliver a 10% return on what is already committed. PwC surveyed 4,454 CEOs across 95 countries. 56% reported getting nothing measurable back from their AI investments. The gains are real. The profitability is not yet there for most. Even the profitable companies are cutting, because the market pays them more for the haircut than the haircut costs. The market is paying for the press release. Not for the product. Yet.

Three Groups, One Cycle

The math is not uniform across the industry. Three groups of companies are operating in this market right now, and the cycle is hitting each one differently.

Group 1: Foundation Model Labs

Big tech. OpenAI, Anthropic, Google, Meta, NVIDIA on the silicon side. They train and ship the foundational models, funding a circular AI economy where the same dollar gets counted three times. They set the prices everyone else pays. NVIDIA alone is roughly 7% of the S&P 500, larger than the entire energy sector. AI policy in Washington, Brussels, and Beijing is now bent around their cycle. Their layoffs are funding a race they are already winning.

Group 2: SLM Shippers

They train and ship their own models against domain KPIs. Small language models, fine-tuned stacks, bespoke architectures for the workloads that matter to their business. They do not depend on someone else’s API for the work that defines their margin. They protect unit economics religiously because the unit economics IS the moat. Most attempts at this fail. Training infrastructure, data quality, talent, model evaluation, deployment discipline. Every step is a place where Group 2 ambitions collapse back into Group 3 economics. The ones who do it right compound. The ones who do it half-right end up with the worst of both worlds. API costs and bespoke model costs at the same time. Gartner predicts enterprise SLM usage will run 3x LLM usage by 2027. You can spot the real ones by their gross margin.

Group 3: API Wrappers

They call themselves AI-native. They built the product on top of someone else’s API. When the model owner moves a price, their gross margin moves with it. Their moat is someone else’s P&L. Until their roadmap stops depending on someone else’s pricing decisions, they will struggle to make AI profitable while competing with five other companies running the same wrapper. Cursor saw this coming. They were among the largest customers of OpenAI and Anthropic for two years, then shipped Composer 2 in March, a model trained from scratch on their own infrastructure. Call it the migration. The smart Group 3 companies are racing to become Group 2 before the math catches up. Cursor is just the first one with the capital to do it visibly. ClickUp is running a different play. Not training a model, but rebuilding the org around the assumption that the agents do the work. Same direction. Different bet. Same exposure if the productivity does not show up.

The COVID Coin Has a Flipside

Five years ago COVID hit. Zero rates followed. Every spreadsheet looked smart. Hiring went vertical. Companies hired thousands for the cycle, not for the company. Same CFOs running the model. Same compensation committees signing it off. Same incentive loop. Five years later the AI bill is exposing every API wrapper that never had a real moat. Layoffs are going vertical. AI is the biggest technology disruption in modern history. The leadership cycle around it is not. Every major technology shift in the last 150 years produced a labor restructuring followed by a labor expansion at a new layer. The companies that built the bench during the cut survived to staff the next layer. The ones that did not, did not. The disruption is new. The circle is old.

The Two Seats That Owe the Truth

Which means somebody in the room has to name what is actually happening. Two seats can. No others.

The CTO knows the group. Token spend, model dependency, gross margin compression. The CTO is the only person who knows whether the company is shipping its own models or renting them.

The CEO knows the why. The strategy bet, the capex commitment, the market signal the cuts are answering. “We bet on shipping our own models and we ended up renting margin” is harder to say than “AI made you redundant.” It is also the truth the team is owed.

The ROI Returns When You Return to the Problem

And once the truth is named, the question shifts from who to cut to what to actually build. The 95% with no measurable return is not because AI does not work. It is because most companies are using AI to satisfy the market’s hunger. Not to solve a problem the user actually has. The ROI shows up when the technology gets pointed at a real workflow, a real friction, a real cost that real customers feel every day.

Stop doing GenAI for the sake of GenAI. Take the step back. Ask what the end user is actually paying for. Build the AI around the answer. The companies running this playbook quietly are the ones whose unit economics work. The ones doing AI to be seen doing AI are the ones cutting people to make the math look better. The technology was never the problem. The use case was.

Three Questions for the CEO

If you want to know which group your company is actually in, three questions answer it.

One. Does your core revenue depend on a workflow that runs through someone else’s foundational model API? If yes, you are Group 3 today, regardless of what the deck says.

Two. Has your team trained, fine-tuned, or shipped a model against a specific domain KPI in the last twelve months? If no, the Group 2 transition has not started. If yes, the next question matters more than this one.

Three. Does your gross margin move when OpenAI or Anthropic adjust their pricing tiers? If yes, the SLM work is real but not yet load-bearing. If no, you are Group 2.

Three questions. Five minutes. The honest answer tells you what the next quarter has to be about.

Build for the Jobs That Are Arriving

Same logic applies to the people. Stop mourning the jobs that are leaving. Start building the people for the jobs that are arriving. The same disruption removing roles is creating new ones nobody is qualified for yet. The most valuable hire in 2026 is the token economics analyst who can cut a company’s inference bill by 40% without touching the product. That role did not exist 18 months ago. There are maybe a few hundred people in the world who can do it well. The ClickUp version of this hire gets a million-dollar salary band. The non-ClickUp version gets stock options and a story. Either way, the role is the leverage point. The people getting cut this quarter are not failing. They are funding a transition. The leaders who survive are building the bench. The rest are doing layoff math.

If You Ask Me

AI exposes our deepest weaknesses as builders and as leaders. The companies pointing it at imaginary problems get exposed for not knowing what their users actually need. The companies pointing it at real-life problems, with the guts to take them to the next level, get the unit economics, the customer retention, the moat that holds. The API combiners are racing against the clock. Either they migrate or the model owner absorbs their use case. There is no third path. The big ones are shaping the economy of the world. The middle path is the one that wins, as long as they do it right. The competition is fierce.

Build something that solves a real problem. Ship the model that runs it. Defend the unit economics like your company depends on it. Because it does. ClickUp just bet the company on the version of this that fires humans and trusts the agents. We will know in a year whether that bet was prophecy or wish.

And do not be surprised when a CEO announces they are firing AI agents next, to feed the market’s hunger once again. History and markets run in circles. Nobody escapes. The market will reward that too, for a quarter.

In April 2026, Forrester named Omilia a Leader in The Forrester Wave™: Conversational AI Platforms For Customer Service, Q2 2026. This followed our August 2025 recognition as a Visionary in the Gartner® Magic Quadrant™ for Conversational AI Platforms.

Recognition like this does not happen by accident. It does not happen because of a slide deck. It happens because of how a company operates when the stakes are high.

In conversational AI, the stakes are always high. Customers cannot afford downtime. Regulated industries cannot afford security gaps. Enterprises running mission-critical voice and chat at scale cannot afford accuracy drops or wobbly unit economics. The market moves faster than ever. But the fast ones in our domain are not allowed to sacrifice any of that to keep moving.

This is the story of how we operate when all of it has to be true at the same time.

It starts with a format we call the war room.

When I proposed this format four months ago, I knew the calendar math was brutal. Forty engineers, flown to Athens, off their regular work for three days, four times a year. On paper, an executive should hesitate. I did not. I knew exactly what happens when you put the right people in one physical room with one mission. The numbers on the spreadsheet stop mattering. The output is on a different scale.

Four months. Four war rooms.

Forty engineers each time, flying into Athens from every corner of the world where Omilia operates.

Three days per session. One room. One mission.

This is how we have started shipping in weeks what enterprise software companies typically ship in quarters.

Why we started doing this

Omilia is in a chapter that demands velocity. New products, new capabilities, new integrations, all shipping at a cadence our customers and our market expect from a leader. To sustain that pace, some of the foundations that have served us beautifully for years are being modernized to match the ambition of what is coming next.

Plans like these look great on a slide. They always do.

The real test is what happens after the slide deck closes. That is where the org shows what it is actually made of. That is where DNA reveals itself. Either a company has the get-things-done mentality to turn plans into shipped software at speed, or it does not.

We have been at this for over 20 years. That does not happen by accident. It happens because a company decides, again and again, that ambition will not die in committee.

How the format works

Simple on paper. Ruthless in execution.

A clearly defined challenge worth three days of the company’s best people. Groups with named leaders. Regular check-ins so momentum stays honest. A tight frame, ambitious goals, and full freedom to move fast inside both.

Every engineer in this room is equipped with the best AI tooling available, top to bottom. Not as a novelty. As an extension of their craft. The capability ceiling in a room like this is genuinely hard to find.

Not a hackathon. Not a competition. Not pizza and trophies.

A war room.

What gets shipped

The output speaks for itself. Recent sessions rebuilt parts of our SDLC end-to-end. Shift-left automation where AI now handles code review, drafts release notes, and scans for security risks. Human attention reserved for the decisions that genuinely require it. Time to market on enterprise-grade work that used to be measured in months.

Other sessions tackled core platform services that needed to be reimagined for the next decade of scale. The kind of work that under normal conditions gets pushed quarter after quarter because something more urgent is always in the way.

When one of our enterprise commitments demanded a capability on a timeline the industry would have called unrealistic, the team had it production-ready out of a single session. No drama. No escalations. Just a room, a challenge, and the right people to deliver it.

In a war room, the urgent and the important finally sit at the same table.

The decisions that move faster than the code

This is the part I care about most as a CTO.

The biggest unlock is not in the lines of code. It is in the decisions.

Impediments that would normally take weeks of async threads, alignment meetings, and escalation cycles get resolved in a single afternoon. Trade-offs that would normally generate a dozen Slack debates get settled with a whiteboard and thirty minutes of honest conversation.

Velocity of decisions is the multiplier nobody puts in their roadmap. It is also the one that matters most.

The gap that decides this cycle

In conversational AI, the difference between vendors is no longer foundation model quality. Everyone has access to the same frontier models. The real difference is integration depth, security posture, regulated-environment readiness, and the speed at which new capabilities reach production for enterprises that cannot afford downtime or guesswork.

That is the gap that defines who wins this cycle.

War rooms are how we keep widening it.

It is also how a Forrester Leader and Gartner Visionary keeps earning those positions instead of resting on them.

What happens to a global team in 72 hours

There is a second outcome we underestimated when we started.

When a global team that mostly meets through video tiles ends up shoulder to shoulder for three days, something shifts. People who collaborated remotely for a year finally share a coffee, a whiteboard, and a few stories. During the last session, a teammate had his birthday. Cake, candles, the whole crew singing in the middle of a sprint. Then straight back to the work.

And the work is only half of it. The dinners, the drinks, the late conversations that have nothing to do with the sprint. That is where people stop being Slack handles and start being humans to each other. You learn who has a newborn at home. Who lived in three countries before this one. Who actually laughs at your jokes. The interpersonal wiring that takes months to build over video calls gets soldered in a couple of nights.

Moments like that do not show up in release notes. They compound in everything that comes after.

Watching that happen is part of why I keep pushing for this format. As a leader, my job is not to run the meetings that already exist. It is to create the conditions where the work actually gets done. War rooms are among the boldest and highest-leverage moves I’ve made as a tech leader.

War rooms are part of how we operate now

We started this as an experiment. Four months in, the verdict is in. War rooms are not a monthly stunt at Omilia. They are part of how we run.

As we keep growing, we will keep pulling our best engineers physically together, handing them hard problems, and watching them deliver outcomes the rest of the industry assumes take a year.

The takeaway

Plans are easy. Execution is the moat. Urgency is the differentiator.

The companies winning this AI cycle are the ones that move when others meet. The ones that ship when others align. The ones whose DNA carries a warrior mentality from the executive team all the way down to the engineer writing the next line of code.

That is the company Omilia is building. Forrester and Gartner have started to notice. We have noticed too. And we are not slowing down.

More war rooms ahead. More challenges worth solving. More proof that velocity, in a market this hot, is the only honest signal of quality.

Proud of every engineer who showed up, traveled, sweated, and delivered.

This is what an Omilia chapter looks like. The next one is already being written.