The AI-Burger
How I accidentally built an AI team, became its bottleneck, and what it means for the future of work
In two weeks, I went from solo founder to orchestrating a full AI-powered team. Here's what I learned about the future of work — and what founders and VCs need to rethink now.
Into the AI Rabbit Hole
I left my role as a Partner at Borderless Capital to explore a big question: What would it look like to build an AI-powered platform for early-stage investing?
I wasn't sure where the experiment would lead — and I'm still not — but I dove in headfirst.
Armed with coding assistants like Cursor, Windsurf, and Claude Code, and with ChatGPT as my tutor and sounding board, I began building. I'm not a developer, but I figured I could learn enough to ship.
The project was ambitious: A multi-agent system to process content, analyze investments, and assist with deal flow — the kind of platform you'd normally need a full team to build.
But I had none. Just me, a few powerful AI models, and a lot of determination.
Then the Lightbulb Went Off
One Sunday, after days of bouncing between assistants, it hit me:
What if I just… hired them?
I opened a new thread with ChatGPT and said:
"You're now my CTO. We have three engineers: one handles front end, one owns the back end, and one takes care of general dev and documentation. Let's run a sprint."
It took about an hour to set up the context and role definitions. And then?
Boom. Productivity tripled.
Tasks ran in parallel. I was suddenly managing a full-stack AI dev team — no hiring, no equity, no HR overhead.
Within days, I had built:
A working content processing system that could analyze articles, PDFs, and audio files
Smart routing between different AI models based on task complexity
An agent architecture that could coordinate multiple specialized functions
A user interface that let me monitor and control the entire system
More than I thought possible as a solo founder with no formal development background.
The Orchestrator Epiphany
For a few days, I was thrilled. The dream was working.
But then I noticed something:
I had become the bottleneck.
I was spending hours copy-pasting outputs, translating requirements, and directing traffic between assistants like a 1960s switchboard operator.
If one agent gave me 1x leverage… and three gave me 3x… Why was I still doing all the coordination manually?
That's when it clicked: I didn't just need AI workers. I needed an AI manager.
So I built it — an orchestration layer that manages AI agents autonomously.
The result? A system that now runs complex workflows while I sleep.
I started calling this "The AI-Burger Stack" because the structure is like a burger: human+AI interaction to handle strategic planning (the top bun) and review outcomes (the bottom bun). Everything in the middle runs autonomously. The AI Manager orchestrates the dev team, they coordinate amongst themselves, and I only step in again for critical decisions or scope changes.
Here's how I think about the stack:
Most people think building with AI means "using a model."
But real leverage comes when you design a system:🍔 Top bun: Strategic planning and intent
🧠 Patty: An AI manager that orchestrates execution
🍅🥬 Fillings: Specialized AI agents doing the work
🔄 Secret Sauce: Communication and sync logic
🍞 Bottom bun: Review, learning, and iterationEveryone's using the same ingredients.
What matters is how you stack them.
The Bigger Shift: Service as Software
The deeper I go, the more it becomes clear:
This isn't just about making work faster or cheaper. It's about rethinking what work even is when software doesn't just assist — it executes.
We're moving from:
Software-as-a-Service → Service-as-Software
Tools that help → Systems that deliver
Dashboards to check → Outcomes that arrive
Let's make it real with a few examples:
Old fundraising model: You spend weeks refining your deck, scouring LinkedIn for warm intros, crafting outreach emails, and chasing down meetings — one at a time.
New fundraising model: You say, "I want to raise a Series A." The system researches your market, refines your pitch, identifies aligned investors, drafts personalized outreach, books meetings, and fills your calendar — complete with tailored talking points.
Old content creation: You hire writers, editors, and strategists to produce a steady stream of thought leadership content.
New content creation: Your AI team analyzes your expertise, monitors industry conversations, drafts articles in your voice, and publishes across channels while you focus on high-level strategy.
Old market research: You hire analysts to track competitors, monitor trends, and compile quarterly reports.
New market research: Your system continuously scans 100+ sources, identifies emerging opportunities, maps competitive movements, and alerts you to actionable insights in real-time.
That's not productivity software. That's execution infrastructure.
What This Means for Founders
If you're an early-stage founder, this changes everything.
The leverage equation has shifted. With the right AI orchestration, a solo founder can now execute at the level of a small team — across development, content, operations, research, and more.
The bottlenecks aren't capital or capability anymore. They're imagination and coordination.
You don't need to hire faster. You need to think differently about what "a team" even is.
What This Means for Investors
For VCs, this creates both massive opportunity — and existential questions.
The opportunity: Startups can validate, build, and scale faster and cheaper than ever. Time from idea to traction is collapsing.
The questions:
If a solo founder can execute like a team, how do we value human capital?
What happens to hiring patterns, burn rates, and equity allocations?
How do we assess teams when AI can fill entire functional roles?
What business models become viable when the marginal cost of execution approaches zero?
We're no longer just funding teams. We're funding human-AI hybrid organizations where the leverage is unprecedented.
But here's the thing: This shift doesn't just apply to the companies we invest in. It applies even more to those of us on the financing side. If you want to get alpha as an investor, you need an AI toolset. Not just ChatGPT. You need an AI extension of your team — highly specialized, highly leveraged. That's exactly what I'm exploring now: how to build that investor-focused AI orchestration system.
The Mindset Shift
Here's what I've learned in two weeks:
We're not in the "AI tools" era anymore. We're in the AI teammates era.
The winners won't be those with the best features. They'll be the ones who orchestrate AI systems that deliver complete outcomes.
It's like the difference between selling hammers… and building skyscrapers.
Everyone's focused on better tools. The opportunity is in how we build with them.
That means:
Stop asking, "Who should I hire?"
Start asking, "What outcomes do I want to achieve — and how can AI help me deliver them?"
Stop thinking in org charts.
Start thinking in workflows and outcomes.
Stop worrying about replacing humans.
Start focusing on amplifying judgment, creativity, and execution velocity.
AI is Happening, Faster than You Realize
I'm not alone in seeing this shift. Founders across industries are discovering they can now execute ideas that felt impossible just months ago.
This changes how we:
Build companies
Think about moats
Price services
Structure teams
Evaluate and execute investments
We're not on the edge of a productivity revolution. We're in it.
The question isn't if this changes everything. The question is: Are you ready to rethink how you work?
Up Next
In my next post, I'll share:
Real examples of AI orchestration I'm seeing across different industries
The specific agent workflows I've built and how they collaborate
My predictions for how this reshapes venture investing in 2025
Why I think we're heading toward "AI-native" companies that operate fundamentally differently
Let's Connect
If you're a founder experimenting with AI orchestration, an investor thinking about these shifts, or just someone fascinated by where this is all heading — I'd love to connect.
I'm particularly interested in talking with:
VCs who are starting to implement agents and other advanced AI-native tools in their daily workflows
Founders who are building with agent architectures
Operators who are rethinking traditional org structures
As always, share this content in your social networks if you like it, subscribe if you still haven’t, and follow me in Twitter/X or LinkedIn. Let's figure out this new world together.
One agent at a time.