All tags
Topic: "context-engineering"
not much happened today
gpt-5.1 sonnet-4.5 opus-4.1 gemini-3 openai anthropic langchain-ai google-deepmind adaptive-reasoning developer-tools prompt-optimization json-schema agent-workflows context-engineering structured-outputs model-release benchmarking swyx allisontam_ gdb sama alexalbert__ simonw omarsar0 abacaj scaling01 amandaaskell
OpenAI launched GPT-5.1 featuring "adaptive reasoning" and developer-focused API improvements, including prompt caching and a reasoning_effort toggle for latency/cost tradeoffs. Independent analysis shows a minor intelligence bump with significant gains in agentic coding benchmarks. Anthropic's Claude models introduced structured outputs with JSON schema compliance in public beta for Sonnet 4.5 and Opus 4.1, enhancing tooling and code execution workflows. Rumors of an Opus 4.5 release were debunked. LangChain released a "Deep Agents" package and context-engineering playbook to optimize agent workflows. The community is eagerly anticipating Google DeepMind's Gemini 3 model, hinted at in social media and upcoming AIE CODE events. "Tickets are sold out, but side events and volunteering opportunities are available."
minor updates to GPT 5.1 and SIMA 2
gpt-5.1 gpt-5.1-codex gpt-5.1-codex-mini sima-2 gemini openai google-deepmind github microsoft cursor_ai perplexity-ai weaviate llamaindex adaptive-reasoning agentic-coding tool-use context-engineering memory-architecture self-improvement retrieval-augmentation database-query-planning chart-parsing robotics sama allisontam_ cline cognition demishassabis omarsar0 helloiamleonie
OpenAI released GPT-5.1 family models including 5.1-Codex and 5.1-Codex-Mini with improved steerability, faster responses, and new tools like apply_patch and shell command execution. Pricing remains unchanged from 5.0. Immediate integrations include GitHub Copilot, VS Code, Cursor, and Perplexity adopting GPT-5.1 models. Google DeepMind announced SIMA 2, a Gemini-powered agent capable of language instruction following, planning, and self-improvement without human feedback, targeting robotics applications. New research on context engineering and agentic tool use patterns was published, with contributions from Weaviate and LlamaIndex on database query planning and chart parsing respectively. "Adaptive reasoning" and agentic coding improvements are highlighted in GPT-5.1- Instant.
not much happened today
trillium gemini-2.5-pro gemini-deepthink google huawei epoch-ai deutsche-telekom nvidia anthropic reka-ai weaviate deepmind energy-efficiency datacenters mcp context-engineering instruction-following embedding-models math-reasoning benchmarking code-execution sundarpichai yuchenj_uw teortaxestex epochairesearch scaling01 _avichawla rekaailabs anthropicai douwekiela omarsar0 nityeshaga goodside iscienceluvr lmthang
Google's Project Suncatcher prototypes scalable ML compute systems in orbit using solar energy with Trillium-generation TPUs surviving radiation, aiming for prototype satellites by 2027. China's 50% electricity subsidies for datacenters may offset chip efficiency gaps, with Huawei planning gigawatt-scale SuperPoDs for DeepSeek by 2027. Epoch launched an open data center tracking hub, and Deutsche Telekom and NVIDIA announced a $1.1B Munich facility with 10k GPUs. In agent stacks, MCP (Model-Compute-Platform) tools gain traction with implementations like LitServe, Claude Desktop, and Reka's MCP server for VS Code. Anthropic emphasizes efficient code execution with MCP. Context engineering shifts focus from prompt writing to model input prioritization, with reports and tools from Weaviate, Anthropic, and practitioners highlighting instruction-following rerankers and embedding approaches. DeepMind's IMO-Bench math reasoning suite shows Gemini DeepThink achieving high scores, with a ProofAutoGrader correlating strongly with human grading. Benchmarks and governance updates include new tasks and eval sharing in lighteval.
Context Engineering: Much More than Prompts
gemini-code openai langchain cognition google-deepmind vercel cloudflare openrouter context-engineering retrieval-augmented-generation tools state-management history-management prompt-engineering software-layer chatgpt-connectors api-integration karpathy walden_yan tobi_lutke hwchase17 rlancemartin kwindla dex_horthy
Context Engineering emerges as a significant trend in AI, highlighted by experts like Andrej Karpathy, Walden Yan from Cognition, and Tobi Lutke. It involves managing an LLM's context window with the right mix of prompts, retrieval, tools, and state to optimize performance, going beyond traditional prompt engineering. LangChain and its tool LangGraph are noted for advancing this approach. Additionally, OpenAI has launched ChatGPT connectors for platforms like Google Drive, Dropbox, SharePoint, and Box, enhancing context integration for Pro users. Other notable news includes the launch of Vercel Sandbox, Cloudflare Containers, the leak and release of Gemini Code by Google DeepMind, and fundraising efforts by OpenRouter.
Cognition vs Anthropic: Don't Build Multi-Agents/How to Build Multi-Agents
claude cognition anthropic langchain huggingface microsoft llamaindex linkedin blackrock multi-agent-systems context-engineering agent-memory model-elicitation ai-evaluation deep-research-workflows framework-migration pydantic-schema walden_yan hwchase17 assaf_elovic sh_reya hamelhusain omarsar0 clefourrier jerryjliu0 akbirkhan
Within the last 24 hours, Cognition's Walden Yan advised "Don't Build Multi-Agents," while Anthropic shared their approach to building multi-agent systems with Claude's multi-agent research architecture. LangChain highlighted advances in context engineering and production AI agents used by LinkedIn and BlackRock. The community is engaging in a debate on multi-agent AI development. Additionally, Hugging Face announced deprecating TensorFlow and Flax support in favor of PyTorch. Research on agent memory and model elicitation techniques from LlamaIndex and Anthropic were also discussed.
not much happened today
seedance-1.0 codex claude-code kling-2.1 veo-3 bytedance morph-labs huggingface deeplearning.ai figure-ai langchain sakana-ai video-generation autoformalization ai-assisted-coding api-design context-engineering reinforcement-learning ai-evals hypernetworks model-fine-tuning foundation-models andrew_ng hwchase17 adcock_brett clementdelangue akhaliq jxmnop hamelhusain sh_reya
Bytedance showcased an impressive state-of-the-art video generation model called Seedance 1.0 without releasing it, while Morph Labs announced Trinity, an autoformalization system for Lean. Huggingface Transformers deprecated Tensorflow/JAX support. Andrew Ng of DeepLearning.AI highlighted the rise of the GenAI Application Engineer role emphasizing skills in AI building blocks and AI-assisted coding tools like Codex and Claude Code. Engineering teams are increasingly testing API designs against LLMs for usability. Figure AI's CEO stressed speed as a key competitive advantage, and LangChain introduced the concept of Context Engineering for AI agents. Reinforcement learning on LLMs shows transformative potential, and the community values AI evals and data work. Sakana AI released Text-to-LoRA, a hypernetwork method for generating task-specific LoRA adapters from natural language, enabling efficient model customization. The video generation race heats up with Bytedance's Seed-based model praised for quality, challenging American labs, alongside models like Kling 2.1 and Veo 3.