Bekah is a writer, community builder, and developer advocate. She founded Virtual Coffee, has worked across open source, developer education, and technical content, and brings a humanities-first lens to how people learn, build, and work with new technology.
bekahhw.com ↗Your team keeps paying for the same solved problem, and because the tickets all close, nobody sees it happening. Repetition is evidence of a missing team capability, and standup is the detection layer that's been announcing it all along.
Read more →Before companies use AI cost overruns to justify cutting people, they should terminate the agent workflows that consume money without producing reliable outcomes.
Read more →One session, $100.66, 91% Fable 5 — for confirming rollout steps. Multiply that across 200 engineers and you have a budget conversation nobody is ready for. The paper console makes the numbers visible.
Read more →Evidence gets a skill written. Evaluation keeps it worth keeping. A skill that isn't measured can silently make your agent worse, and, because skills execute, a wrong one does more damage than a wrong doc ever could. Here's why every skill needs an eval, and what a real one looks like.
Read more →Skills are about to become part of the AI engineering stack. If they don't carry provenance, we're just rebuilding prompt libraries with nicer names. A prompt starts with intention. A skill should start with evidence.
Read more →Frontier labs are paying a billion dollars a year for the same kind of session reasoning your team generates and deletes every night. The asset isn't the code the agent produced. It's the path the agent took.
Read more →AI agent workflows are no longer single requests. They are stateful, branching systems that mutate their own context over time. Request logs, traces, transcripts, and bills flatten that structure. Teams need telemetry primitives that preserve session lineage, cache topology, and prompt shape.
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