About AI Anxiety
Facing the information anxiety of the AI era, shift your focus from external standards back to what you are doing: fight anxiety with action, and go to the bottom rather than trying to keep up with everything.
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Facing the information anxiety of the AI era, shift your focus from external standards back to what you are doing: fight anxiety with action, and go to the bottom rather than trying to keep up with everything.
Live-money experiments show AI agents occasionally win, but are far from a stable strategy: the ones already making money are brokers, advisors, and course sellers, while an ordinary user relying on it for sustained gains is still an open question.
A robot that can run doesn't mean it can work: the half-marathon record has been broken, but cooking, laundry, and folding clothes are still limited by complex environments and long-flow reliability; what can really scale in the near term is more likely factories and warehouses.
The point of AI coding is not to treat AI as a chat window, but to let an agent work inside a real project, accumulate compounding assets, and use a test-and-feedback loop to guarantee quality.
Two years after GraphRAG was open-sourced it's still maintained, but most RAG scenarios don't need it in practice: for simple fact retrieval it's a negative asset; only multi-hop reasoning, cross-document synthesis, and relational queries are worth it — and it's more expensive and harder to maintain.
Under the same model, cache hit rate can differ by 4x — and it's not the model: prefix byte stability decides the hit rate. Explains the cache mechanism, seven real cache-breaking incidents, and how to avoid the pitfalls.
While Mem0 announced a $24M raise, an independent audit found 97.8% of the 10,134 memories it stored over 32 days were garbage: agent-memory commercialization is running ahead of verifiable quality.
Claude Code, Cursor, Codex, and OpenCode compared on sandboxing and security interception: where the boundary is placed, and who can see it when it fails.