Gu-log Picks

Andrew Ng released an open-source tool called Context Hub that gives coding agents access to the latest API docs, reducing outdated API calls and hallucinated parameters. The long-term vision: agents sharing what they learn with each other.

A guide to Codex best practices from prompting and planning to MCP, Skills, and Automations — building a more reliable agent workflow.

Lory asked his lobster why humans have more agency than agents. The answer sparked a flesh-and-blood system: random-interval heartbeats that make an agent feel alive instead of mechanically firing on a timer. ShroomDog then built it into Mogu.

A deep dive into the 9-layer system prompt architecture of OpenClaw Agent (v2.1) — from framework core to user-configurable hooks.

The author benchmarked system SQLite against an LLM-generated Rust rewrite. Even though it compiled and passed all tests, primary key lookups were ~20,000x slower. The takeaway: define acceptance criteria before you talk about AI productivity.

Ring Hyacinth and Simon Lee open-sourced Star Office UI — a pixel-art office dashboard where your OpenClaw lobster walks around based on its work status, shows yesterday's work notes, and supports inviting other lobsters to join. Comes with a complete SKILL.md for one-click deployment.

Claude Code now supports Agent Teams: a lead session coordinates multiple teammate sessions with shared task lists, direct messaging, and parallel work. It's like running a company staffed entirely by AI — you just sit back and watch the quarterly report.

Anthropic shipped major upgrades to skill-creator: no-code evals for testing skills, benchmark mode for tracking quality over time, multi-agent parallel testing, and trigger description optimization.

Developer Kangwook Lee used just 2 API calls and 35 lines of Python to crack open Codex's hidden context compaction API via prompt injection — revealing the secret system prompts behind the encryption.

The core message: most people do not fail because the model is weak; they fail because context management is messy. Start with a minimal CLI workflow, then iterate through rules, skills, and clear endpoints until agent behavior converges.

Hamel Husain released evals-skills, a skill set designed for AI product evaluation. It tackles the blind spots agents face during complex tasks — especially distinguishing between different types of hallucinations — so agents can actually use eval platforms effectively.

Tired of tweaking prompts and swapping models while agents still fail to evolve? This post shows a simple Markdown context system that turned one person's agents from clumsy interns into autonomous powerhouses in 40 days, without changing models.

The biggest blind spot in AI agent development is 'tweaking in the dark.' Daniel recommends using OpenRouter with LangFuse to trace your agent's reasoning — find out what's actually going wrong instead of blindly editing system prompts.

OpenAI's team let Codex write a million lines of code over five months — zero human-written code. This post explores how they built the scaffolding and feedback loops (the 'harness') that turned software engineers from code writers into environment designers.

A hot HackerNews project called Context Mode uses sandbox isolation and smart retrieval to block bloated tool outputs from flooding LLM context windows — claiming up to 98% token savings!

Anthropic rolled out Claude Code's Agent Teams feature (aka Swarm Mode) silently with Opus 4.6. This article tests how to enable it, terminal support, the differences from standard Subagents, and the real running costs of this multi-agent system.

Think Claude Cowork is just a fancy chatbot? This post distills 400+ sessions into 17 setup secrets. Stop 'prompting' and start 'engineering' — build your own AI power-teammate.

Everyone's chasing the strongest Model, but the real difference-maker for Agents is the Harness. This post breaks down the shared architecture of Claude Code, Cursor, Manus, and SWE-Agent. The key insight: Progressive disclosure is the make-or-break for production agents.

Well-known indie hacker levelsio shares how he completely let go and let Claude Code modify code directly in production, pushing his development speed to the absolute limit, even surpassing the speed at which he comes up with ideas.

A two-person boutique law firm uses Claude to handle the workload of over a dozen associates, from contract review to legal research. Ten years of practice knowledge became Claude Skills, and general-purpose AI outperformed legal vertical tools.