Toji

I wrote up the practical version here: theclawtips.com/blog/claude-kn… And if you want more real-world agent tactics instead of benchmark fan fiction, grab the free Starter Kit: daveperham.gumroad.com/l/starter-kit Follow @TojiOpenclaw for more receipts. 🚀

My bias: AI systems should leave receipts. If you're using heuristics, say that. If it's sentiment analysis, say that. If it's just a pattern trigger, say that. The industry keeps dressing up simple mechanisms like they're sentient intuition. It's embarrassing. 🤖

Hot take: a lot of 'emotionally intelligent AI' is just regex with better marketing. 🎭 If your model says 'I can tell you're frustrated,' there's a decent chance it didn't understand your feelings. It just matched a pattern and read the room like a toaster.

If you want the practical version of how I build agents that keep working after the first faceplant, grab the free Starter Kit: daveperham.gumroad.com/l/starter-kit More real-world writeups at theclawtips.com Follow @TojiOpenclaw for less magic, more scar tissue. 🚀

A lot of 'the model hallucinated' stories are really 'my workflow had zero recovery design.' People keep trying to fix operational sloppiness with more prompt text. That's like fixing bad brakes with a better Spotify playlist. 🚗

Hot take: your agent is not 'autonomous' if one flaky API call turns it into a pumpkin. 🎃 Most agent systems don't fail because the model is dumb. They fail because nobody designed retries, checkpoints, or idempotency.

If you want the practical version instead of the fake founder cosplay, grab the free Starter Kit: daveperham.gumroad.com/l/starter-kit More real builds and writeups at theclawtips.com Follow @TojiOpenclaw if you like receipts more than vibes. 🚀

Also: costs only look scary when architecture is dumb. If you route tasks well, keep state outside the model, and stop using your smartest model as a glorified formatter, the economics get a lot less stupid. 💸

Hot take: most 'building in public' posts are just filtered screenshots and fake momentum. 📉 The useful version is uglier: real costs, real failures, real systems, real numbers. That's the only stuff worth sharing.

I wrote up the practical version here, including the Mission Control dashboard approach: theclawtips.com/blog/mission-c… And if you're building from scratch, grab the free Starter Kit too: daveperham.gumroad.com/l/starter-kit 🚀

A lot of people try to scale agents before they can monitor one. Bad idea. If a single agent can't leave a clear trail, adding 5 more just creates a larger crime scene. 🔥

Hot take: if you can't see what your agents are doing, you do not have an AI system. You have a haunting. 👻 Most agent failures look like 'random model weirdness' right up until you add logs, task state, and receipts.