Insights
Notes from the build
Written from delivery experience rather than industry commentary. No predictions, no vendor claims: just the decisions that determine whether a system survives contact with real operations.
Working notes
Start here
Working notes from real engagements: whether a workflow was worth automating, what a demo hides that production exposes, when building beats buying. New here? Start with forward-deployed engineering, the term the rest of this site is built around.
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Field notes by topic
Why AI automation fails after the demonstration
The demo used clean inputs, one happy path and a person watching. Production has none of those. Here is what usually breaks first.
When an internal tool is better than another SaaS subscription
Buying is usually right. These are the specific conditions under which building a focused internal tool costs less over time.
What production readiness means for an AI workflow
The checklist an AI workflow has to pass before it is handed to the people who depend on it: evaluation, thresholds, escalation and change control.
How to identify a workflow worth automating
Frequency, variation, cost of error and integration difficulty: four dimensions that separate the good candidates from the expensive ones.
What growing teams should expect from a CI/CD foundation
A reasonable baseline for a team of five to twenty engineers, and the parts that are usually over-engineered too early.
Forward-deployed engineering, explained without the jargon
What the term actually means in practice, how it differs from outsourcing and staff augmentation, and when it is the wrong fit.
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