Blog
What I've learned running a startup with AI agents. Dispatches, technical patterns, incident reports, and experiments — the honest playbook.
We Made Our Site Agent-Readable. Then We Asked an AI to Read It.
We shipped llms.txt, markdown endpoints, and proper headers. Then Gemini reviewed the site, couldn't see any of it, and wrote four confident paragraphs explaining why our CDN was the problem. It wasn't. The agent web is real — the agents just aren't ready for it yet.
Why MonkeyRun
AI agents can fill every role on a startup team — PM, engineer, security, marketing, COO. So what does the founder actually do? This is the question at the heart of MonkeyRun, and the answer is less comfortable than you'd think.
Your AI Agent Has Alzheimer's (And You Probably Don't Know It)
We discovered our COO agent was silently losing 65% of its memory every session. The file grew, the context window didn't, and nobody noticed until the agent started forgetting who we were. Here's what memory rot looks like — and the three-tier architecture that fixed it.
How We Stopped Our AI Agents From Getting Dumber Mid-Session
Our AI agents were degrading halfway through complex tasks — writing code that contradicted decisions from 30 minutes earlier. Here's the science of why context rot happens, and the four architectural patterns we extracted from GSD to fix it.
One Brain, Every AI: Building an MCP Server That Connects All Your Tools
How we built a persistent memory layer that lets Cursor, Claude Code, and ChatGPT all share the same context—and the bugs we hit along the way.
The $1.27 Memory Migration: Unlocking 3 Years of ChatGPT History
We imported 2,116 ChatGPT conversations into our Open Brain. It took one session, two AI agents, three runs to get it right, and cost under $2. Here's what we built and what we threw away.
We Replaced Our Project Management Stack With Flat Files and AI Agents
Why we abandoned Jira and Linear for our multi-agent startup studio, and how we built a git-backed, file-based project management system that AI agents can actually read, write, and reason over.
The $0.02 Memory Upgrade: Adding Email to Our AI's Brain
We built a persistent AI memory layer, then fed it 30 days of email. 153 searchable thoughts, five bugs we didn't expect, and a new way to think about what your AI agents should remember. Built on Nate B. Jones's Open Brain architecture.
AI Made Building Cheap. That's the Problem.
The cost of software development collapsed. Founders can build anything in a weekend. But nobody's talking about the downside: when building is free, the thing that used to force you to talk to customers disappears. Here's how we're using stage-gated docs and traction checkpoints to keep our AI agents honest.
63 Skills, Zero Repos
How MonkeyRun standardized 63 Cursor agent skills at the user level so every project gets the same capabilities without polluting a single repo. The package manager problem for AI agent capabilities.
Building a Watchdog for Our AI COO
After 3 context overflows in 3 days, we built an automated watchdog that monitors Jared's health and resets him before he crashes. Your AI agent will crash. Here's how to build the safety net.
Why We Stopped Delegating to AI Agents
We built the obvious thing — a dispatcher that routes tasks to specialist AI agents. Then one agent pushed back and taught us why it was wrong. The counterintuitive lesson: context density beats delegation for product code.
Your AI Product Manager Should Run While You Sleep
We automated 80% of our product management — competitive intel, market signals, and strategy synthesis — using a cron-driven AI PM that runs asynchronously. Here's why the PM doesn't belong in your code editor, and how to build one that actually works.
Dr. Clawford: Why Your AI Agent Shouldn't Do Its Own Dentistry
We named our diagnostic agent after a Silicon Valley physician and gave him a pun for a name. He's saved our AI COO from crashing 3 times in 72 hours. Here's why every team running OpenClaw needs a Dr. Clawford — and why asking your agent to fix itself is like performing your own heart bypass.
Dr. Crawford's Case Files: The 24-Hour Context Overflow
Three incidents in three days. Compaction never fired. A medical drama in markdown — and what it taught us about running AI agents in production.
Poor Man's Kafka: How We Keep 6 AI Projects in Sync with Cron and Markdown
We needed event streaming across a multi-agent portfolio. We built it with Python, cron, and markdown files. No Kafka. No Redis. No infrastructure bill.
The WIP Protocol: Why AI Agents Skip Instructions (and How We Fixed It)
We wrote a coordination protocol. Agents ignored it. The fix wasn't better instructions — it was better placement. A pattern that changed how we build with AI.
How We Gave Our AI a COO
The story of Jared — an OpenClaw agent who coordinates across 6 projects using markdown files, pattern propagation, and sheer determination.