From Prototype to Strict Typing: Rebuilding an AI Prototype in Bun & Hono
How a fast product experiment became a production TypeScript service without discarding the validated product loop.
Rapid prototypes answer one question well: is this workflow worth building? They usually answer questions about failure recovery, observability, and long-term data ownership badly.
Keep the proof, replace the assumptions
The prototype established the core loop. A user could connect training data, see a readiness result, and act on it. That product proof was valuable, so the rewrite preserved the request and response contracts while replacing hidden mutable state and loosely typed payloads.
const AnalysisRequest = z.object({
sessionId: z.string().min(1),
includeHistory: z.boolean().default(true),
});
app.post('/analysis', async (context) => {
const input = AnalysisRequest.parse(await context.req.json());
return context.json(await analyzeSession(input));
});The important improvement was not adding more layers. It was making the boundary explicit and keeping one validated path into the domain logic.
What changed
- TypeScript strict mode became non-negotiable.
- Hono routes validate untrusted payloads before calling application code.
- Durable jobs own work that can outlive one HTTP request.
- Structured logs carry request and job identifiers.
- Mobile screens consume stable response shapes instead of database records.
What did not change
The validated interaction stayed recognizable. A rewrite that improves internal purity while forcing users through a different workflow has confused architecture with product development.
Prototype the uncertain product decision quickly. Engineer the proven path carefully.