I burned all my tokens researching how to save tokens
quesma.com
July 19, 2026
10 min read
🔥🔥🔥🔥🔥
54/100
Summary
Quesma is researching the economics of AI agents and agentic coding costs. A personal deep research setup burned through the entire limit of the Claude Max 5x plan in 30 minutes, leading to a focus on cost reduction and trust improvement using existing subscriptions.
Key Takeaways
- The initial deep research setup consumed the entire token limit of the Claude Max 5x plan in 30 minutes without yielding results.
- The author optimized research costs by utilizing existing subscriptions (Claude, Codex, and Antigravity) and implementing shared memory among the tools.
- A model-orchestration pattern was developed to use cheaper models for specific tasks, such as Claude Sonnet 5 for searching and Claude Opus 4.8 for verification.
- The research involved adjusting the model setup based on live run performance and weaknesses identified during the process.
Community Sentiment
Positives
- Using a combination of cheaper models for initial exploration and funneling results through powerful models can maximize efficiency and save tokens — this approach is gaining traction.
- Some commenters highlight that cloud AI can significantly outperform local models, especially when cost is considered, making it a smart choice for many developers.
- There's excitement around tools like RemembrallMCP that claim to reduce token usage while improving results, indicating innovation in optimizing AI interactions.
Concerns
- Many users express skepticism that the hype around cloud AI translates to real-world value, with concerns that it's often just a cycle of writing about AI without tangible products.
- Commenters are frustrated with the hardware costs required for local AI models, arguing that it's financially impractical compared to using cloud solutions.
- The persistent issue of hallucinations in AI outputs is a major concern, with some feeling that claims of 'no hallucinations' are unrealistic and misleading.
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