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Re:Show HN: AI agents run my one-person company on Gemini's ... by hkonte on Tuesday March 10, 2026 @08:18AM (#47322205)
The token trick (one focused prompt, all context pre-injected, single response) is smart. The failure mode I've seen with that pattern is prompt drift. When the injected context is flat prose, the model starts blending roles across runs.

Splitting the prompt into named blocks (role, objective, context, constraints, output format) fixes this. Each injection point is explicit. The agent stays on task even after 100+ iterations.

I built flompt for exactly this. Visual prompt builder that decomposes prompts into 12 semantic blocks and compiles to XML. Easy to version and swap components per agent without rewriting everything. github.com/Nyrok/flompt

Re:Show HN: AI agents run my one-person company on Gemini's ... by ppcvote on Tuesday March 10, 2026 @11:28AM (#47324598)
Thanks for the insight on prompt drift. You're right — flat prose breaks down fast across iterations. We ended up with a similar solution: a modular spec system where the engine rules (shared across all brands) and theme files (brand-specific: colors, fonts, narrative structure) are separate named documents. The LLM reads both before generating, so roles never bleed across runs. Essentially named blocks, just at the file level instead of XML tags. Will check out flompt — the visual decomposition could be useful for auditing where drift starts.