Imagine shipping features while your master plan screams 'not started.' That's the nightmare hitting solo devs everywhere. One founder's brutal rewrite reveals the rot.
Everyone thought autonomous AI would code, fix, and conquer solo. Turns out, they're masters of busywork – summarizing, inspecting, then quitting. Time to demand real artifacts, not theater.
Production AI agents aren't your grandma's chatbots anymore. They're sprawling workflows that crash spectacularly, and if you're not tracing every step, you're flying blind.
Every time an AI agent like Claude opens your repo, it devours 400,000 tokens just figuring out the layout. Stacklit stops that waste cold with a git-committable map.
Martin Fowler christens the Feedback Flywheel. We've been spinning ours for months, capturing AI's messy signals before they vanish. Skeptical? Read on.
AI agents wrecking your Kubernetes cluster with credential leaks? A two-tier service account setup turns chaos into control, limiting damage if one goes rogue.
Imagine your army of AI coding agents humming along perfectly—then a reboot wipes the magic. OpenRig changes that, letting solo devs snapshot and restore their setups. But is it the real deal?
Everyone's pitting A2A against MCP like it's a cage match. Wrong. They're the TCP and HTTP of AI agents, each owning its lane.
Your AI coding buddy keeps screwing up the same way. Experience Engine promises to fix that by ditching the bloat. Does it?
OpenClaw just smashed 250,000 GitHub stars — faster than the Linux kernel ever dreamed. But businesses chasing automation savings? Look closer; the free lunch comes with a maintenance bill.
Picture your AI agent, fresh inbox buzzing, staring blankly at a verification email riddled with tracking junk. That's the wall Broodnet's team hit—until they scored 163 real ones and flipped the script.
Imagine your slick TypeScript AI agent—LLM calls, vector DBs, the works—running flawlessly on your rig. Teammate pulls the code? Total disaster. Docker says: not today.