Ship an MVP with AI agents as a solo founder

What should an AI-built MVP include?

One user, one problem and one core action, end to end. “End to end” means a real person can sign up, do the thing your product exists for, and see the result, on a real URL.

Everything else is a candidate for the cut list. AI agents make adding features cheap, which is exactly why scope is now your main risk. Each feature you add is something you must read, test, secure and explain to a customer.

The plan below is a template for about two weeks of full-time work. It is not a promise. Your scope sets the schedule, so adjust the days and keep the order.

Days 1 and 2: what goes in the one-page spec?

Write the spec yourself before any agent writes code. One page is enough: who it is for, the problem in their words, the core action as a verb and an object, the three to five screens, the data you need to store, and at least five things you are not building.

Finish with acceptance checks in plain sentences. “A new visitor can sign up, create a project and see it in a list.” These become your tests later.

Save it in the repository, for example as docs/spec.md, and point your agents’ instructions file at it. AGENTS.md is an open format for exactly this kind of agent-facing context.

Then use an agent as a sparring partner, not a builder. Anthropic’s best practices describe plan mode for this: the agent reads your files and proposes an approach without making changes. Ask it to list your assumptions, the riskiest parts and what you could cut. Argue with the answer.

Choose boring tools: a language and framework you can read, hosted login, a managed database and a host that can deploy a preview of every branch.

Days 3 to 5: how do you build the thinnest slice?

Deploy something on day three. A page, a sign-in and one database table, with your checks running in CI. Shipping from the start means that deployment never becomes a surprise at the end.

Then build the thinnest path through the core action. It can be ugly. Ask for one small change at a time, and end every prompt with the check that proves it, such as npm test. Commit after each green step, so any mistake is one revert away.

Work with one agent at first. Once you have a rhythm, start a second agent on an unrelated task in its own git worktree, so the two never edit the same files.

Days 6 to 9: how do you add the core action and a safety net?

Now make the core action solid. Handle the empty state, the error state and the slow state. Write three smoke tests for the path that matters, and ask your agent to draft them, then read them yourself.

If you charge money, use a hosted checkout and treat webhooks as the source of truth. Stripe’s fulfillment guide says you cannot rely on the landing page alone, because there is no guarantee a customer visits it.

Add one analytics event for the core action. Without it, you will argue from feelings after launch. Then go through our security checklist. It takes an afternoon and covers the risks that OWASP ranks highest for web apps.

Days 10 to 12: how do you test it with real people?

Use it yourself for a full day, on real data. Then ask three people from your target group to try it while you watch, without helping. Note where they stall. You are looking for the places where your assumptions were wrong, not for compliments.

Fix the top three problems and nothing else. For each reported bug, ask the agent to reproduce it with a failing test first, then fix it. Resist new features. Every feature you add now resets this testing.

Days 13 and 14: what must be true before you launch?

A short gate. The checks pass on the main branch. Production configuration is separate from development, and no secret is in the repository. A database backup exists and you know how to restore it. You have practiced a rollback. Errors reach you by email or chat. People can contact you. And you know the one number that tells you whether this is working.

Launch to a small list first. A quiet first week with ten users is easier to learn from than a loud first day with a hundred strangers and a bug.

Where do agents slow a solo founder down?

When tasks are too big to review, when nothing checks the result, and when you accept code you cannot read. You will own every bug it contains, and you will be the one fixing it at night.

They also tempt you to keep rewriting prompts instead of deciding what you are building. When a task keeps failing, the cause is often a vague spec, not a weak agent.

Run the plan as a process

A SwarmPane Workflow chains plan, build, check and review steps, each result moving to the next agent, with approval steps where you want to decide. Teammates are agents with a job, instructions, skills and long-term memory, and Overnight Autopilot (Beta) can run a queue of tasks unattended.

SwarmPane runs the agent CLIs and accounts you already have. Start with a 7-day trial for $1 and build your first slice with a net under it.