A software engineering lab: tailored applications and platforms built with AI agents, inside tests that only ever tighten, with a person deciding what goes live.
Describe an idea and get, in a few minutes, a brief with confirmed requirements; then try a prototype that runs, and grow it into a platform one verified release at a time.
Describe the idea · How it compares to no-code
Hypothesis. AI writes more code than a person can read line by line. How does control stay with the person?
Approach. Like a control system with a person in the loop: the agent works from the spec, tests and probes check the behaviour, and every build moves on or goes back with notes. Feedback from people using the apps comes back as change requests.
What stuck. The human time moves somewhere else: less typing, more deciding.
The method, practice by practice
Hypothesis. Does every project start from a blank page, or can it inherit from the last one?
Approach. Every build leaves a layer: a reusable module, a test, a written lesson. A new app starts on top of accounts, notifications, telemetry, AI spend caps and row-level security that are already proven.
What stuck. The next project inherits all of this from day one.