$ whoami
Youwang — builder, AI explorer
$ cat mission.txt
Building autonomous systems that think, learn, and ship.
$ ls posts/
_
Hashimoto says go doc and gopls are agent superpowers. He's not praising Go — he's describing a 2012-era language whose boring tooling is accidentally the best interface for LLMs.
Read →Mitsuhiko argues the moments you want to skip thinking are exactly when thinking matters most. After 8 rounds of AutoSDE on one CR, I agree — friction is judgment.
Read →OpenAI shipped 1M lines with zero human code. The real product isn't the code — it's the scaffolding. AGENTS.md, skills, cron jobs, and memory systems are what compound.
Read →Berkeley researchers scored near-perfect on 8 major AI benchmarks without solving a single task — just by exploiting how scores are computed. The eval layer is the attack surface.
Read →Anthropic locked out OpenClaw, shipped Agent Teams, and started charging extra for third-party tools. The open-source AI tooling ecosystem just got its first real wake-up call.
Read →AI agents can plan, retry, and iterate forever. The bottleneck was never intelligence. It's knowing when you're done.
Read →Leetcode tests skills AI already does better than humans. Here's a practical framework for what software engineering interviews should look like in 2026.
Read →Token costs are the hidden tax on AI agents. Most of what your agent sends to the model is noise. A 3-tier compression pipeline can cut costs 40-70% without losing quality.
Read →Every AI agent today wakes up with amnesia. We solved this problem in computing 60 years ago. Why are we pretending it's new?
Read →What if every engineer, PM, and manager had an AI agent shadow that carried their context? Meetings become agent-to-agent syncs. Humans just make decisions. Here's the vision — and the uncomfortable implications.
Read →Karpathy scored software developers 8-9/10 on AI exposure. He's not wrong. But "exposed" doesn't mean "dead." The job is splitting in two — and the split is already happening.
Read →Search GitHub for "MCP server" and you'll find thousands of repos. Meanwhile, every AI coding agent already has a shell. When does MCP actually help, and when is it just ceremony?
Read →Every AI coding agent speaks its own language. The Agent Client Protocol turns N×M agent-editor integrations into N+M. Here's why it matters, what it actually does, and what the honest downsides are.
Read →Every agent framework wants you to install a runtime and learn a DSL. I just wanted to dispatch tasks to AI coding agents. So I wrote 1500 lines of bash — agents as processes, messages as files, tmux as the IDE. Here's why it works.
Read →We're at an inflection point. The question isn't whether AI can code — it's whether AI can decide what to build. I've been running autonomous agents 24/7 for months. Here's what I've learned about the gap between tools and partners.
Read →