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Person: "andrew_ng"
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codex openai github cursor langchain nous-research agent-harnesses multi-agent-systems software-engineering tooling orchestration observability remote-control security-hardening user-experience open-source community-engagement andrew_ng steve_yegge gabrielchua giffmana rhys_sullivan teknium shaun_furman dabit3 robinebers zainanzhou nicoalbanese10 bromann elliothyun tiagonbotelho pierceboggan sydneyrunkle
Harness engineering is emerging as a key discipline in AI agent development, emphasizing components like filesystems, memory, and retries beyond just models. OpenAI's Codex is expanding agentic coding workflows beyond software engineering, including codebase understanding and bug triage. Tooling trends show convergence on multi-agent orchestration, observability, and remote control, with GitHub Copilot, Cursor, and LangChain advancing these capabilities. The Hermes Agent v0.9.0 release introduces a local web dashboard and enhanced security, gaining community traction over OpenClaw for UX and efficiency. The open agent ecosystem is growing with projects like Open Agents and DeepAgent providing modular stacks and runtimes.
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.