Lola is the founder of Lunch Pail Labs. She enjoys discussing product, app marketplaces, and running a business. Feel free to connect with her on Twitter or LinkedIn.
Unit tests tell me whether a piece of code behaves. Behavioral agent tests tell me whether a real workflow still makes sense when a person has to use it.
I’m testing Pailflow waitlist pages with agents and learning that the hard part is not generating pages. It is giving the agent taste.
I simplified my stack into clear building blocks so commands, skills, subagents, question gates, and review inboxes work as one system instead of disconnected prompts.
I stopped manually spot-checking skill edits and moved to a fixed eval loop. The result was faster revisions, clearer failures, and more trustworthy agent behavior.
There is a lot of noise around self-flying agent systems right now. I got faster, cleaner leverage by scheduling repeatable work first and reviewing outputs on cadence.
One of the most useful parts of working with AI agents is not just faster execution. It is the ability to review the work after the fact, spot patterns, and turn those patterns into better systems.
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