A self-hosted, MIT-licensed research tool with an agent skill that teaches any AI how to drive it. No rate limits, no credit counters.
I Built My Own Research Engine. Here’s What This Tool Lets You Do.
Raleigh’s Open Data: One Command to Find Anything
Raleigh publishes 178 public datasets. Most citizens never see them. I asked my AI agent to take a look.
AI Evals 101: Stop the Slop
Companies are shipping AI into production with no way to tell if it’s actually working. The slop isn’t a model quality problem, it’s an evaluation problem. Here is the four-rung ladder that turns vibe checks into engineering discipline, with tools you can run today.
What Paul Graham Noticed That HR Didn’t
Paul Graham’s essays describe the ideal startup founder in terms that map almost perfectly onto Autistic and ADHD cognitive patterns. Corporate hiring processes penalize the same traits. The startup ecosystem is functioning as an inadvertent neurodiversity inclusion program.
The Incidents Are the Training Data
There is a structural transformation happening in software operations. The output of production is increasingly training data, training data produces automation, and automation runs production. Site Reliability Engineering is one place this shift becomes visible in concrete terms. Not because SRE has the most data, but because SRE already solved a piece of the governance problem this new model depends on.
What Replaces Money: The Flywheel Y Combinator Describes But Never Names
I had an AI agent extract and analyze all 464 YC Library articles. The word ‘flywheel’ appears exactly once. But the mechanics are everywhere, hiding in plain sight. Y Combinator has described a new economic primitive that replaces capital as the lubricant for startup growth. They just refuse to name it.
The Org Chart in a Box
The Product Manager wanted to ship an MVP. Three phases. Skip the reproducible build. Skip the caching subsystem. Skip the Mermaid diagrams. Ship fast, iterate later.
The Debugger said that path would destroy maintainer trust.
“Non-Deterministic Bug Blindness,” the Debugger said. “Skip the reproduction baseline and the ‘fails on main’ gate? The agent writes a fix, runs the test, it passes, but it was passing BEFORE the fix too because the test is tautological. The trust curve is steep to climb and vertical to fall off.”
Maximize Work Not Done: The Overlooked Agile Principle Behind Nano Unicorn Success
Agile’s 10th principle says to maximize the amount of work not done. It was functionally lost for two decades. Nano unicorns rediscovered it through necessity. Established organizations can apply it to cut OpEx without layoffs.
There Is No Best System
Every PKM methodology is an assembly of principles designed to solve a specific information constraint. There is no best system. There are only bricks. Build your own.
The Escalation Nobody Wins
The tension between enterprise security and the mandate to innovate with AI isn’t new, but AI has compressed it from a manageable chronic condition into an acute crisis where either side losing can kill the company. The problem isn’t the people. It’s the structure.
Natural Ignorance
AI isn’t taking your job. Incompetent leaders using AI as a cover story for cost-cutting they’d do anyway might. And that’s actually good news.
Clanker Technical Architect: First on the Scene with Progressive Disclosure
Part 2 of the Clanker Kanban series. Six software architecture documentation methodologies independently discovered progressive disclosure between 1995 and 2011 without naming it. The artifact pyramid names what they all found. The Technical Architect profile in the Clanker pipeline carries this lineage.
Cat-Herding Clankers: Agile Ceremonies Were Built for Humans. AI Agents Need Something Different.
Part 1 of the Clanker Kanban series. Why sprint ceremonies fail for AI agent coordination and what to build instead. The artifact pyramid, the orchestrator pattern, and four AI-native ceremonies that replace planning meetings with structured handoffs.