5/ The lessons.md file is now pointless. Claude Code has auto memory. It writes down what it learns about your project on its own, after you correct it, and reloads it next session. The tool already does the thing people are telling you to do by hand.
AI
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Keep system prompts under 200 lines for better adherence
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4/ Keep it short. This is the part people get wrong. The docs say stay under 200 lines, ideally around 100. A model reliably follows about 150 instructions at once, and Claude Code's own system already uses a chunk of that. A bloated file makes Claude follow less, not more.
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Anthropic lists seven actual ways to steer Claude Code
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2/ Anthropic lists the actual ways to steer Claude Code. There are seven, and they are not files you invent. CLAUDE.md. Rules. Skills. Subagents. Hooks. Output styles. System prompt. That is the real list. Everything else is noise.
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Start with one CLAUDE.md file for build commands and conventions
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3/ Start with one file. CLAUDE.md in your project root. Build commands, your folder layout, conventions, the "always do this" rules. Claude reads it at the start of every session. This one file does what those seven were trying to do.
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Claude Code auto-loads specific files, not all recommended markdown files
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1/ The viral advice says make persona.md, lessons.md, references.md, glossary.md, and more. Claude Code does not read most of them. It auto-loads a specific set of files. The rest just sit there unless you import them by hand.
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Claude Code: 7 files or just one?
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Everyone says to create 7 files when you start Claude Code. Anthropic's own docs say you only need one. Here's how to set it up:
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Delos Workers: AI agents with persistent identity and memory
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Most AI agents reset the moment a task ends: you prompt, it runs, the context is gone.
— Chubby♨️ (@kimmonismus) 22 juin 2026
Delos Workers is built on the opposite assumption: Each agent keeps a standing identity and persistent memory, with its own email, phone number and Slack handle, so it carries context between… https://t.co/n2lCH5ZW3KMost AI agents reset as soon as a task ends: you give an instruction, it executes, the context disappears. Delos Workers is based on the opposite hypothesis: each agent maintains a permanent identity and persistent memory, with its own
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Hugging Face to surpass 3M public models and 1M datasets
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We are about to surpass 3M public models & 1M public datasets on @huggingface in a few days. Open-source AI is on fire!
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Sakana Fugu: orchestrator rivaling Fable 5, not independent model
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After examining the new Sakana Fugu model, which, as they present it, rivals Fable 5, I want to comment that this is in itself not a new independent model, but an orchestrator trained to orchestrate several different models (e.g., Opus 4.8, GPT
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Sparrow: Sparse Deployment for Long-Context RL LLM
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Long-context RLVR is powerful, but most of the cost comes from generating massive CoT deployments. Sparse attention would make it faster, that's it.