Prototype-First Software Design With Agents (serce.me)

Sergey Tselovalnikov argues for a "prototype-first" approach to software design amplified by AI coding agents: build a throwaway working prototype early to validate feasibility, uncover unknowns, refine estimates, and communicate design intent more effectively than documents alone. The piece emphasizes that AI agents make prototyping faster, but only if codebases and engineering workflows are optimised to support rapid exploration and iteration; otherwise agents flail or produce misleading results. He gives concrete, actionable engineering guidance: make code searchable (monorepos + text-to-file-path linkages like PR searches) so agents can find relevant APIs; solve third-party-source access (mount sources with jnr-fuse or leverage IntelliJ indexes); prioritise integration tests and realistic test scaffolding over brittle unit tests; and enable fast end-to-end developer environments using tools like Testcontainers, AWS LocalStack, and Miniflare so prototypes can be launched and iterated against realistic dependencies. The net implication for AI/ML teams and platform engineers is clear: invest in observability, searchable indexes, test infrastructure, and dev sandboxes to unlock reliable agent-driven prototyping—while avoiding overuse of prototypes for trivial tasks.