Results for “context engineering”

…on large codebase modernization from Theo [@theo, @theo]. Context: Mythos, release tempo, and what Opus 4.7 means A lot of the discussion only makes sense in the context of Claude Mythos Preview, Anthropic’s more restricted, stronger model …

…3 Opus, best of 4 runs. We are working on clustering and flow engineering with Haiku. GPT-4o Release by OpenAI Key Features: @sama noted GPT-4o is half the price and twice as fast as GPT-4-turbo, with 5x rate limits. @AlphaSignalAI…

…and full sort remain a practical baseline. 4. Long-Context Engineering: Kimi’s Linear Attention Push Linear Lift-Off: Kimi’s Context Costs Go Linear: MoonshotAI published the Kimi Linear Attention technical report, cutting quadratic…

…Pro more practical for demanding tasks @OpenAI. Pricing, context, infra, and practical behavior: API pricing was reported at $5/$30 per 1M input/output tokens for GPT-5.5 and $30/$180 for Pro @scaling01, with Sam Altman noting a 1M context …

…3 Opus, best of 4 runs. We are working on clustering and flow engineering with Haiku. AI and Machine Learning Research Mamba-2 State Space Model: @_albertgu and @tri_dao introduced Mamba-2, a state space model (SSM) that outperforms Mamba…

…66 tokens/sec using Llama 3.1 on a 7900XTX GPU at a 10k context length, showcasing hardware synergy. This emphasizes the importance of aligning powerful hardware with large models for optimal results. Cooling Systems Cause Noise Issues:…

…and Agentic courses on Hugging Face Learn to grasp prompting, context management, and roles. They suggested that one can evaluate their prompting skills by asking ChatGPT to rate the prompt engineering and provide feedback, which is key to …

…cannot be run on consumer grade GPUs. The claimed 10m token context is almost certainly far above what the "real" context is when trained with 256k tokens (still impressive! but not 10m!) There was a special "experimental" version used for …

…parity with GRPO while avoiding diversity collapse. “1M context” ≈ “64K” in practice: A widely shared critique from @giffmana argues that multi-100K/1M context marketing often masks effective windows nearer to ~64K, due to retrieval…

…deployment claims, not controlled productivity measurements (engineering results). Physical-task demonstration: DeepMind researchers describe Argon deriving a cornhole simulation from human video, performing system identification and…

…and Mistral, particularly "lost in the middle" issue with long contexts, were also discussed. Details on handling markdown in prompts and troubleshooting with tools like GuardrailsAI and Instructor were exchanged. Model Hosting and…

…argue for non‑reasoning coders by default—reasoning can exhaust context in agent loops (@nrehiew_; @Teknium1). Early Cline tests found v3.1 “makes assumptions” in planning; tracking diff edit failure rate as more data comes in (@cline).…