Results for “context engineering”

…with SQL query engines, Azure BadRequestError puzzles, prompt engineering tips for AWS context, complexities of Pydantic JSON structures, and RouterQueryEngine filter applications. Hail the Claude Calling Agent: LlamaIndex's latest, the…

…Claude Sonnet and Opus to it (@hrishioa). The Rise of "Context Engineering": A significant discussion, amplified by a viral tweet from @karpathy, centers on replacing the term "prompt engineering" with "context engineering". The new term…

…claiming preserved vision, reasoning, tool use, and 262K context with near-zero refusals. Independent of the rhetoric, this is the clearest thread in the set pointing to a real shift: useful, locally deployable, partially uncensored models …

…users suggesting it can run at 4-5 tokens/second with an 8k context window. Some suggest partial offloading to RAM for improved performance. Gemma 2 27B via Ollama is praised for its performance, especially in non-English languages. One…

…observed that the model handled a 32k token inference (likely context length), noting repeated correct responses during thinking. This points to potential issues with attention patterns, verbosity, or energy usage during long context…

…with 600B total / 27B active parameters, up to 1M token context/output, text+image input, and text output. The model targets repo-scale software engineering, long-horizon tool use, multimodal professional work, and finance-heavy reasoning; …

…find it effective for coding tasks and appreciate its 180k context length. The model's low latency and ease of integration with apps using the OpenAI Python package are noted as significant advantages. The cost-effectiveness of DeepSeek-V3 …

…performance, underlying the importance of rigorous systems engineering and regulatory compliance in applied clinical contexts. 1 year ago GPT-4o was released! (Score: 164, Comments: 49): The image summarizes key facts about the release of…

…of a secret revolutionary technique, attributing success to engineering precision. Quantization Techniques: @danielhanchen detailed the quantization of DeepSeek R1 to 1.58bit, achieving an 80% size reduction while maintaining usability…

…gating) that replaces most global attention to unlock long‑context throughput and stable RL post‑training. A 3:1 KDA:MLA hybrid was picked via ablations; with identical 5.7T tokens and ~3B active params, the team reports markedly better…

…TSMC/CoWoS capacity). Agent Harnesses, Memory Systems, and Eval Engineering Becoming First-ClassHarness quality is increasingly as important as model choice: several papers and launches converged on the same theme: agent performance depends…

…Members struggled with model tokenization and prompt engineering, emphasizing the importance of correctly using template tokens like ### or end-of-text tokens for efficient fine-tuning. This was particularly discussed in the context of…