# agent

Jarrod Watts looked inside Codex Goals and found that it solves early stopping, not long-run drift. The real long-running agent stack needs upfront clarification, multi-agent review, and memory outside the context window.

A context window is a model's day: how many lessons, messages, tool results, and task events Ryland can experience before sleep, compression, or collapse.

Anthropic's Claude Dreams is not just summarization. It gives agents an offline memory-consolidation loop: reread old memories and up to 100 past sessions, then produce a fresh, auditable memory store.

OpenClaw's automation docs put scheduled work, background tasks, Heartbeat, Hooks, Standing Orders, Task Flow, and related mechanisms on the same map. Task Flow is the layer for multi-step flow state, sync, and revision tracking; this piece reads those boundaries conservatively.

Anthropic accidentally shipped the full TypeScript source code of Claude Code CLI inside an npm source map. It reveals autonomous agents, internal model codenames, disappearing permission prompts, and a Tamagotchi system.

A Tsinghua Shenzhen team proposes Natural-Language Agent Harnesses: move agent control logic from code into structured language executed by an IHR runtime. Harnesses can reshape behavior, but more structure does not always mean better results.

Artificial Analysis launches AA-AgentPerf, a hardware benchmark that uses real coding agent trajectories instead of synthetic queries. It allows production optimizations, measures per-accelerator/per-kW/per-dollar efficiency, and scales from single cards to full racks.

Anthropic launches Claude Code Channels with native Telegram and Discord support, turning Claude Code into a 24/7 always-on AI agent. VentureBeat calls it the OpenClaw killer.

Claude Computer Use sparked huge excitement, with many claiming AI will fully replace human workers. But the original author points out that while AI can handle technical operations, it can't replace human judgement and cultural context. The real moat is still deep domain knowledge.

Andrew Ng partners with Oracle on a new course teaching you how to build persistent cross-session memory systems for AI Agents, solving the frustrating problem of agents 'forgetting everything' after each conversation.

Andrew Ng announces a new course on A2A (Agent2Agent Protocol). With IBM's ACP merging in, A2A is becoming the industry standard for agent-to-agent communication, letting you connect Google ADK and LangGraph agents seamlessly.