IdeaWell

Project ideas from Hacker News discussions.

Claude: System Prompts

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

Theme 1 – System prompts dominate context and affect performance

"the system prompt is the most important part of the instruction you can give the model" – tosh
"These are just free $ for them, unnecessary bloating the context" – epolanski

Theme 2 – Ambiguity around Opus 5’s prompt and its impact on perceived capability

"It'd be ironic if the 'Opus 5 nerf' effect is from telling Opus that it sits a tier down from Fable and Mythos" – eterm
"the Opus 5 system prompt has instructions that explain to Opus that it might be handling a request that was intended for Fable 5" – tosh

Theme 3 – Caching, cost, and flexibility of system prompts

"They are cached, the inference cost is paid once per model, does not scale linearly per user" – TZubiri
"System prompts don't affect the API, they are cached token rates" – simonw

🚀 Project Ideas

Generating project ideas…

PromptCutter

Summary

  • Cuts token waste by compressing system prompts while preserving intended behavior.
  • Saves compute costs for API users who currently pay for large prompts.

Details

Key Value
Target Audience LLM API developers and platform operators
Core Feature Automatic compression and token‑budget optimization of system prompts
Tech Stack Python, HuggingFace summarization API, FastAPI backend, Docker
Difficulty Medium
Monetization Revenue-ready: Subscription SaaS per TB

Notes

  • HN users repeatedly note that system prompts consume precious token budget and increase energy costs; PromptCutter directly addresses this.
  • Provides a clear cost‑saving metric that can attract API‑heavy customers wanting to maximize model usage per dollar.

SPVersion

Summary

  • Offers version‑controlled, searchable history of system prompts for popular LLM front‑ends.
  • Enables users to track changes, compare editions, and avoid duplicated prompt reconstruction.

Details

Key Value
Target Audience AI researchers, product managers, and power users
Core Feature Diff‑aware UI with Git‑style commit history and impact analysis of prompt changes
Tech Stack React frontend, Node.js backend, Git database, PostgreSQL
Difficulty Low
Monetization Hobby

Notes

  • Comments like “I rebuild these as a git commit history” and “they omit the tool definitions” show strong demand for a public changelog.
  • Users want to avoid extra friction and risks of hallucinations when reconstructing prompts manually.

ContextVault

Summary

  • Centralized, token‑efficient repository of system prompts and hidden tool definitions for Claude‑family models.
  • Allows developers to query capabilities without repeatedly paying for duplicated prompts.

Details

Key Value
Target Audience Application developers building agents on Claude/Opus APIs
Core Feature Cache‑backed API that serves pre‑cached prompt + tool payloads on demand
Tech Stack GraphQL + Redis cache, serverless functions
Difficulty High
Monetization Revenue-ready: Pay‑per‑request with volume discounts

Notes

  • Discussion mentions “they omit the tool definitions… extra friction and risks hallucinations,” indicating a clear need for a clean cached interface.
  • Addresses the contradiction‑induced performance drop noted when prompting directly for tool access.

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