Results for “context engineering”

…a first-class product surface: LangChain released an Eval Engineering Skill that uses repo context and trace data to bootstrap task/eval creation with Harbor, described by @LangChain and @hwchase17. Prime Intellect pushed further on…

…used its model to train a competing AI. Without further context or details provided in the post, the implications or evidence supporting this claim remain unspecified. Many commenters highlight the irony in OpenAI's complaint, pointing out …

…9B V2 (reasoning small model): A hybrid Mamba‑Transformer, 128k context model trained by NVIDIA (not Llama-derived), released under the NVIDIA Open Model License (no Llama restrictions). Supports reasoning/non-reasoning modes (system…

**Agent Engineering is all you need.** AI News for 2/20/2025-2/21/2025. We checked 7 subreddits, 433 Twitters and 29 Discords (212 channels, and 6493 messages) for you. Estimated reading time saved (at 200wpm): 663 minutes. You can now tag …

…supports Matryoshka embeddings (output dims 768→128), 2k context, and EdgeTPU latency <15ms in some settings. Immediate ecosystem support across Hugging Face Sentence Transformers, Ollama, MLX, llama.cpp, LlamaIndex, LangChain, Weaviate,…

…You can opt in/out of email frequencies!AI Twitter RecapHarness Engineering, Agent Orchestration, and the Shift from Models to Context PipelinesThe harness is becoming the product boundary: A recurring theme across the day was that model…

…prompt design in GPT4All, highlighting complexities in prompt engineering. Context Length Constraints Raise Eyebrows: Contributors confirmed GPT4All enforces about 2048 tokens for conversation recall, truncating text if it exceeds that…

…Edge-ready models (single-card deploy) with 256K context, tool/agent skills, and multi-framework support (SGLang, vLLM, TensorRT-LLM). Repos and HF weights linked by @TencentHunyuan. Large yet affordable VLMs: StepFun’s Step‑3 (321B MoE)…

…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 …