How I Fired My Entire Team and Replaced Them with 12 AI Agents

The Punchline First

I'm jokingly saying I fired all my employees.

The truth is more nuanced, more interesting, and involves a lot more failure than a LinkedIn headline would suggest. But the end state is real: SyncTech operates with AI agents handling the majority of development, operations, marketing, and sales work — all orchestrated by an AI system called Thursday that I built (with AI, naturally) to run like a CTO who never sleeps.

Here's how we got here.

Act I: Successfully Failing at Launching Startups Since 2013

I started SyncTech to build my own products. That was the dream — engineer turns entrepreneur, builds the next big thing, rings the NASDAQ bell, retires to a beach.

Slight problem: I could build anything, but I couldn't sell anything.

Last Minute Bouquet. StatBreaks. FastKoin. AstroStork. I built them all. They were technically solid. And they all taught me the same lesson: being a great engineer doesn't make you a great salesman.

But while I was failing at my own startups, I noticed something. My friends — founders, entrepreneurs, people with actual business ideas and actual customers — were spending $150K, $200K, sometimes more on development. And getting garbage in return. Offshore teams that disappeared. Agencies that billed for meetings about meetings. Beautiful mockups that didn't work.

Software engineering isn't what I do. It's who I am. And I was watching people get fleeced by shops that treated it as just another service.

Act II: The Pivot to Service

So SyncTech pivoted. Instead of building my own products, I'd build other people's products — the way they deserved to be built.

The early deals were rough. StatBreaks was an equity-only arrangement. Diet Menu was equity plus some cash. I was learning the business side by living it, and the lesson was painful: founders with $40K budgets want $400K worth of product.

That tension is real, and I felt it on both sides. I wanted the little guys to win. I wanted the founder with a great idea and limited capital to have the same Silicon Valley experience that funded startups get. Our team — collectively — had processed tens of billions of dollars at companies like Google, Meta, Gusto, Ultimate Software, and Microsoft. We weren't some bootcamp operation. We were senior engineers who chose to work with startups.

But math is math. You can't deliver $400K of engineering for $40K without someone getting hurt.

Act III: Moving Upmarket (Without Abandoning the Mission)

We moved upmarket. Well-funded startups like UpWaste became our bread and butter — clients with real budgets building real products that serve real customers.

But I never stopped giving free advice to anyone who asked. Got a question about architecture? Call me. Need help thinking through your tech stack? I'm here. I only charge when there's actual work to do. The mission never changed — I just got smarter about sustaining it.

Act IV: The Mercenary Army

At peak capacity, SyncTech was running 5-6 contractors per project. An army of mercenaries from Google, Meta, Gusto, Microsoft. All senior. All exceptional. All expensive.

And I was playing every role simultaneously. Architect. Developer. Project manager. Customer service rep. Code reviewer. The person who answers the 11 PM Slack message because the client is anxious about a launch.

We were building greenfield MLPs — Minimum Lovable Products — from scratch. The work was great. The products were great. The operational overhead of wrangling that many humans was... not great.

Every contractor needed context. Every one had opinions (rightfully so). Every project required me to be the translation layer between what the client wanted and what the engineers were building. I was the bottleneck, and no amount of hiring could fix that because the bottleneck was me.

Act V: AI Enters the Chat

The first AI tool that mattered was GitHub Copilot. Smarter autocomplete, basically. Nice, but not transformative.

Then Claude Code dropped, and everything changed.

Suddenly I had an AI that didn't just complete my lines — it wrote entire functions. Entire files. I could describe what I needed and get working code back. Not perfect code, but working code that I could refine.

I started experimenting. What if GitHub issues could be automatically picked up by an AI agent? What if PRs could be generated without a human writing the code?

It worked. Sort of. The early versions had environment issues, quality gaps, and a tendency to make confidently wrong decisions. But the trajectory was clear: this was going to replace the way software gets built.

So I kept iterating. And iterating. And iterating.

Act VI: Beyond "AI Writes Code"

The agents got better. Full environment builds, automated testing, end-to-end project execution. An issue goes into the backlog, and a finished PR comes out the other side. Not every time — but most of the time.

Then I realized: if AI can handle code, why stop there?

Sales agents started qualifying leads and drafting outreach. Marketing agents (shoutout to Mark Wiz, the marketing persona) began producing content, running SEO analysis, doing competitive research. Each one specialized, each one operating autonomously within its lane.

The dev shop was becoming something else entirely.

Act VII: The Thursday Ecosystem

This is where it gets wild.

I use Granola to transcribe every meeting. The transcript automatically posts to Slack. Thursday — my central AI orchestrator — reads those transcripts and triages them in real time.

"This sounds like a bug." "This is a future feature request." "This is an action item for next sprint." Thursday categorizes everything and then asks me: "Should I create a task for this?"

If I say yes, it creates a ClickUp task, assigns it to the appropriate project, and spawns a dev agent for that client's codebase. The dev agent picks it up, writes the code, submits a PR. The reviewer agent checks it. The QA agent verifies it. I do the final review.

Every client has their own dev agent and ops agent. They know that codebase. They know that client's patterns and preferences. They're not starting from scratch every time — they're building on accumulated context.

Act VIII: The R&D Council

This one makes people's eyes go wide.

I have 5 AI personas that meet daily to debate SyncTech's strategy. They propose initiatives, argue the merits, poke holes in each other's ideas, and pick winners weekly. It's like having a board of advisors that works for free and never has a scheduling conflict.

Is it perfect? No. Is it better than me sitting alone trying to think strategically while also fixing a CSS bug? Absolutely.

The Real Numbers

Am I going to sit here and tell you AI agents are flawless? No.

85-90% accuracy. That's where we are. Across code generation, review quality, task triage — the system gets it right the vast majority of the time.

The other 10-15% matters. A lot. A wrong architectural decision, a missed edge case, a security vulnerability — these aren't rounding errors. They're the kind of mistakes that cost real money and real trust.

That's why I'm still here. That's why the human in the loop matters. The goal isn't to eliminate that 10% of review — it's to teach the system enough that the 10% shrinks to 5%, then 3%, then 1%. Every correction is training data. Every override is a lesson.

We're getting there.

Act IX: The Vision

Right now, I tell people "I have 10 employees." They're all behind Thursday. They're all AI agents operating within a system I've built, refined, and continue to teach every single day.

But here's the thing — this shouldn't be just for me.

Every small business, every startup, every solo founder should have access to this kind of operational leverage. A system that handles the grunt work. That coordinates the pieces. That lets you focus on the decisions that actually need a human brain.

That's what the Thursday desktop app is about. It's powered by OpenClaw — the same infrastructure running my agents right now — packaged into something any business can use.

The founder with a 5-person company shouldn't have to choose between hiring a project manager and hiring a developer. Thursday can be both. And the marketing intern. And the sales coordinator. And the ops manager who keeps the trains running.

The Honest Ending

Did I really fire my entire team and replace them with AI agents?

Kind of. The contractors who used to do the bulk of the coding work — I don't need as many of them anymore. The agents handle it. When I do bring in human engineers, they're AI-forward enthusiasts who work with the agents, not despite them. The team got smaller and more capable simultaneously.

Is the AI as good as the best human engineer on my old team? On the best day, yes. On the worst day, not even close. But the best day is becoming more frequent, and the worst day is becoming less catastrophic.

I've been successfully failing at launching startups since 2013. Building products nobody bought. Running a dev shop where I was the bottleneck. Hiring brilliant people I couldn't afford to keep.

Every failure taught me something. And all of those lessons are now encoded in Thursday — an AI system that runs SyncTech better than I ever could alone.

We make the complex simple and the simple scalable. Turns out, that applies to running a company too.