LATEST INVESTIGATIONS
A practical review of Andrej Karpathy’s LLM Wiki idea, including persistent knowledge compilation, wiki maintenance loops, Obsidian workflows, and why agent-maintained markdown may beat repeated re...
A practical breakdown of Claw Dev, a multi-provider coding assistant launcher that keeps a Claude Code–style terminal workflow while routing requests to Anthropic, OpenAI, Gemini, Groq, OpenRouter,...
Engineering Discipline is an open-source harness for AI coding agents that adds clarification, complexity routing, worker-validator separation, checkpoint recovery, implementation guardrails, and A...
A practical review of Qwen3.6-Plus covering its 1M-token context window, agentic coding strengths, multimodal reasoning, benchmark signals, and why it matters for real AI agent workflows.
A practical review of PrismML’s 1-bit Bonsai models, intelligence density, on-device throughput, energy efficiency, and why 1-bit LLMs matter for edge AI, robotics, and persistent local agents.
A practical breakdown of Claude Code’s agentic loop from official docs, including tools, permissions, checkpoints, session forking, and leak-risk lessons for real engineering teams.
NVIDIA NemoClaw adds policy-based privacy and security guardrails to OpenClaw, enabling always-on autonomous agents through a one-command install and guided onboarding with OpenShell and OpenClaw i...
Codex subagents let you split complex tasks into specialized agents with their own model, sandbox, and tool settings. Here’s a practical guide for shipping safer, faster, and more controllable AI w...
A step-by-step guide to run each NanoClaw agent in isolated Docker Sandboxes, with hardening checks and real operational patterns for small teams and production rollouts.
Why orchestration beats model upgrades in production—and how a better harness can flip benchmarks without changing the model.
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