Python 3.15's Hidden Gems: `asyncio.TaskGroup` Cancellation and More

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• #0001

  #0001Agents & toolsr/ClaudeAIyesterday

  A cache miss in `Claude Code` costs 12.5x more than a hit—here are the common triggers

  70radar

  Claude CodeAnthropic's code-centric AI assistant — for terminals/IDEs

  Changing settings like /model or editing CLAUDE.md mid-session in Claude Code busts the cache, making the next turn 12.5x more expensive. Make major changes only at the start of a new session to manage costs effectively.

  • —A cache miss costs 12.5 times more than a cache hit (1.25x base price vs. 0.1x). This quickly adds up in long sessions.
  • —Adding or removing tools (mcp servers) mid-session is the worst offense, invalidating the entire cache from the tool definitions down.
  • —Editing the CLAUDE.md file invalidates the system prompt cache and the entire conversation that follows, forcing an expensive rewrite.
  • —Switching models with /model doesn't migrate the cache; it starts a fresh one. Use separate sessions for different models like Sonnet and Opus.

  Source: www.reddit.com/r/ClaudeAI/comments/1tlzqpl/cache_miss_inRead original →
• #0002

  #0002Agents & toolsr/ClaudeAI3 days ago

  AI agent tool `Get Shit Done` (GSD) abandoned after creator's rug-pull scam; immediate migration required

  100radar

  Get Shit DoneAI-powered CLI automation agent — runs with local shell access

  The creator retains NPM publish rights, posing a critical security risk through malicious updates. Immediately uninstall old packages and migrate to the community fork get-shit-done-redux.

  • —The creator executed a "rug pull" with the associated $GSD crypto token and vanished. Do not trust any repos from this developer.
  • —The original NPM packages (get-shit-done-cc, @gsd-build/sdk) could receive a malicious update at any time, a high-risk vector given the tool's shell access.
  • —The community has forked the project to open-gsd/get-shit-done-redux after a security audit. Uninstall the old packages and reinstall using the new one.

  Source: www.reddit.com/r/ClaudeAI/comments/1tktl4w/if_you_use_thRead original →
• #0003

  #0003Agents & toolsr/LocalLLaMA3 days ago

  BeeLlama v0.2.0 boosts inference speed by up to 4.9x on an RTX 3090

  40radar

  BeeLlamaLocal LLM engine — accelerates token generation via DFlash

  An inference engine that achieves up to a 4.9x token speedup over llama.cpp via DFlash. It makes high-throughput local LLMs more viable on consumer GPUs like the RTX 3090.

  • —Achieves 164 tokens/sec with Qwen 3.6 27B on a single RTX 3090, a 4.4x speedup compared to llama.cpp's 37.2 tps.
  • —DFlash, a form of speculative decoding, accelerates inference using a smaller draft model. While prompt processing speed is similar, token generation is significantly faster.
  • —The update adds full support for Gemma 4 31B and is compatible with the GGUF format, easing integration with the existing local LLM ecosystem.
  • —This makes fast prototyping or running small-scale services on owned hardware more feasible, especially for tasks involving long text generation, without cloud API costs.

  Source: www.reddit.com/r/LocalLLaMA/comments/1tkpz2y/beellama_v0Read original →