Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k

📝 Discussion Summary (Click to expand)

1. Questionable AI testing methodology

“not only is this article AI‑written, but the testing was entirely done by AI, too?” – MallocVoidstar

2. Token inflation and excessive tool usage

“saying ‘Hey’ or ‘commit’ can trigger 30+ tool uses” – goda90

3. Economic incentives driving token consumption

“Anthropic wants to produce the best coding agent possible and doesn’t care (is even incentivized) about high costs.” – piokoch

🚀 Project Ideas

Generating project ideas…

Captures the full system prompt of AI agents once and reuses it through a local proxy, eliminating repeated calibration requests and token waste.
Provides a measurable reduction in token consumption for heavy‑use AI coding agents.

Key	Value
Target Audience	AI developers using agents like Claude Code, Pi, or OpenCode
Core Feature	Persistent prompt proxy that stores and serves the original system prompt
Tech Stack	Node.js/Express, Redis caching, Docker, OpenAPI
Difficulty	Medium
Monetization	Revenue-ready: $5/mo per user

Commenters asked “Why do you need to do calibration requests to figure out how your own gateway is affecting requests?” – this tool answers that directly.
Could generate discussion on reducing token inflation in LLM APIs.

Converts multi‑step static tree‑of‑thought plans into compact single‑pass prompts, cutting token use while preserving reasoning quality.
Helps users avoid the “token flation” problem highlighted by LLM‑token cost concerns.

Key	Value
Target Audience	Power users of reasoning‑heavy LLMs who run multi‑step plans (e.g., Pi, OpenCode)
Core Feature	Context‑pruning and token‑budgeting module that rewrites static ToT trees into minimal prompts
Tech Stack	Python library, spaCy for relevance scoring, JSON schema for plan representation
Difficulty	High
Monetization	Revenue-ready: $0.001 per 1k tokens processed

Referenced discussion on “Tokenflation seems very real” – this tool directly mitigates that.
Open‑source core with optional hosted service could spark community debate.

Visualizes real‑time token usage and cost across multiple AI agents, suggesting cheaper alternatives and limiting over‑use.
Gives users actionable insights to keep token spend in check.

Key	Value
Target Audience	Teams and solo developers managing multiple AI coding agents in production
Core Feature	Real‑time dashboard with per‑agent token metrics, cost alerts, and optimization tips
Tech Stack	React front‑end, GraphQL backend, PostgreSQL, Docker
Difficulty	Medium
Monetization	Revenue-ready: Tiered SaaS $10/mo basic, $30/mo pro

Commenters lamented “Why is your own gateway screwing with your testing?” – this dashboard would surface such inefficiencies.
Likely to spark discussion on cost‑aware LLM usage.