From idea to a product with paying customers

A founder with a background in recruiting was building a marketplace where companies post hard-to-fill roles and specialist recruiters propose candidates. He wanted to start with clear requirements, to avoid the problems that so often derail a first product. He knew his users and what they wanted. Over three weeks of calls we worked out what that meant in software: each journey through the system for companies, recruiters, and candidates, what goes on each screen, and what data the system needs at each step. He wrote out the details, with AI assistance, and I reviewed them for gaps: a page missing information its users would want, a next step with no direct way to get there. I explained what each technical choice would cost in effort and complexity, so he could weigh the trade-offs and narrow the first release, and showed him how to write user stories that developers can build from.

With the finished requirements, the founder built the platform with AI coding agents and launched it.

Two first-time founders were building a platform for creators to sell their content. They had worked with a developer for two months and wanted the product to take shape faster, with progress they could follow. I looked at what had been built and how the work was planned. The founders had asked from the start for everything to be built right, so it wouldn’t need changing later. The developer took that literally: he spent the two months on foundations a large platform would need one day, while the first goal was a preview and waitlist page. The founders also kept refining the designs, and as a back-end specialist he found the visual details hard to match. I worked with the founders on the requirements, and together we brought in a front-end specialist and a back-end developer. Each week the developers committed to goals they agreed were realistic, and delivered them.

A few weeks later the preview and waitlist page went live, and from then on the founders saw finished work every week instead of just status updates.

The founder was a business owner without a technical background. Using a sophisticated multi-agent AI coding process, he had spent several months building a survey platform for large organizations. Tens of thousands of employees would answer its surveys. Before launch, he wanted to be sure it would hold up: under load, against security and GDPR requirements, and in real-world use. In two weeks I set up and ran the whole system, went through the code, the tests, and the planned infrastructure, and checked what the documentation claimed against what the system actually did.

The platform was in good shape overall. The report listed about 130 findings, a handful critical or high and the majority medium or low, ranked into a plan for what to fix before launch. Typical patterns of AI-built software emerged: components built in isolation that didn’t connect to each other, safeguards that were built but never switched on, and tests that existed but never ran. The founder handed the findings to his AI coding agents to fix straight away.