Apr 27, 2026 Apr 27, 2026 2026-04-27

Sam Altman, the CEO of OpenAI, recently said we are 1–2 years away from the first one-person unicorn — a $1,000,000,000 valuation company run by a single person. The implied amplifier, of course, is AI. What we’re really talking about is a one-billion-dollar AI-enhanced company. (There was even some news about a company that already did this, but in hindsight, it was just a PR stunt, it wasn’t really a one person unicorn).

Now, in order to create something like that — a large collection of predictable processes capable of consistently generating a unicorn-level valuation — you need to put together many scattered skills across many verticals. And AI is genuinely good at this: it can write code, write content, automate marketing, and perform all these things at a very high level of quality.

What is missing from the big picture — and where the friction is hardest — is orchestration.

Not just doing the work predictably, but doing it with very little energy, while maintaining the vision of the company. It all boils down to:

• How easily you can create your agentic flows
• How frictionless the process is of understanding what needs to be built next
• How you promote it, what you discard, where you insist
• How you cut costs, where you double down

This is the core challenge. And this is where AIGernon comes in.

Those four orchestration challenges map directly to what AIGernon does. Agentic flows live in Schedules — natural-language prompts that run on their own cadence. Knowing what to build next is what Projects solve, with the ADD shell forcing every task to declare which realm it’s in. Promotion, discarding, doubling down — that’s what the daily 7 AM status is for: it tells me where I’m stuck in Assess, what’s ready to ship, what to cut. Four bottlenecks, one orchestration layer.

A Week With AIGernon

If you follow my blog, you already know about AIGernon, it’s my personal AI assistant. The core agent is open source, and there is even a UI I wrote (mostly for myself) available here.

For the last week, I gave it more and more access to my projects, and the experience was… well, let’s describe the experience, and you’ll be the judge.

The main entry point is a familiar chat window. If you ever used ChatGPT, you’ll recognize it. Here, you can interact with your agent, that in turn talks to an LLM you configure yourself. I am using MiniMax for my daily work (while saving Claude Code for serious coding tasks). From this chat I orchestrate, in natural language, everything around my workflows. I can ask for project updates, I can ask to analyze a specific project repo and get feedback, or I can do research on whatever topic I find interesting.

Projects

I added a bunch of projects to my AIGernon instance, each of them with its own github repo. The projects section follows a strict Assess – Decide – Do pattern: if there is any task that is still not marked as clearly defined, the project stays in Assess. If all the tasks are clear, I can move it to Decide, where each task is getting a green light. Once all the tasks in the project are ready to do, I can move the entire project to Do.

And here’s where the magic comes: I can start a task myself, and at the end of it mark it as done, OR ask AIGernon to do it. Once done, I review it and if it’s ok, I mark it as done.

Having this ADD shell around the project changes everything, and with that let’s segue into Schedules.

Schedules

These are recurring tasks that can be run every day or every hour, and are completely delegated to AIGernon. There is a separate section in the UI where you can add as many schedules as you want, edit them, or discard them.

One of the schedules I added and it’s running every day at 7 AM is a project status. Here’s the prompt: “Give me an update on all my projects, with the yesterday X-ray (how much Assess, Decide and Do) and an overall X-ray (how much Assess, Decide, Do in general). Be concise and helpful, suggest the best way of work.“

So, every day at 7AM I receive a status, and here’s an actual excerpt from a daily update:

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 Suggested Way of Work

Immediate priorities:

1. AIGernon App — Keep DOing (4 tasks left: Backup, BYOK, Credits, WS streaming)
   – You’re in Execute mode. Stay there. Don’t re-assess.

2. Flight Lens / AppCharts.app — DECIDE or Archive
   – You’ve been in Assess for ~2+ days each. That’s a signal.
   – Either: commit to a decision and move to Do, or explicitly archive.

3. Start tracking daily — The missing yesterday data means you can’t see patterns.
   – 2-minute daily log: what realm did you operate in? What got done?

Meta-pattern: Your flow is Assess-heavy. Consider setting a “max Assess time” per project (e.g., 4h) before forcing a Decide moment.

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Coaching

This is a module that 100% I wrote for myself. I am coaching for more than 10 years, with some customers going back as far as 8 years. I had a very simple setup for keeping track of what happens in each session, but lately I moved everything to this dedicated module. What I get: complete ADD shell on top of the process, and, most importantly, direct integration with the customer. Meaning they can message me via Telegram and AIGernon receives that, processes it and decides whether or not to just store it and it to the next session, or ping me in case we’re facing an emergency. We never faced an emergency yet, but it’s a good option to have.

Where To Go From Here

After a week, the concrete result: I caught two projects drifting in Assess for days I wouldn’t have noticed otherwise, and the Coaching module absorbed the message-juggling overhead I used to do by hand. Not a unicorn yet. But the friction is measurably lower, and that’s the whole game.

If you want to try it, the agent is open source and the app is live. Fork it, run it, break it — or sponsor the work if you want to see where it goes next. Maybe one of us actually reaches that billion. Maybe it’s you.