Knowledge Hub
What real projects teach us
What we learn scaling systems, modernizing legacy, and teaching teams to build with AI — written down while it is still fresh.
The Boring Architecture Decision: What Fewer Parts Cost
Choose familiar components when their limits are visible, because every extra boundary turns a local change into shared operational work.
Earned vs. Performed Confidence in Hard Decisions
Earned confidence makes uncertainty visible, bounds the decision, and creates a next step the room can rely on.
When Cloud Spend Outruns Workload, Trace the Work
A rising cloud bill can expose multiplied work in the request path, even when traffic and unit prices look under control.
Code Review Is a Claim Check, Not a Typing Audit
A consequential PR is ready to merge when its behaviour, evidence, and escape route can be explained—not when the tool or person that produced the diff can be identified.
Which AI Coding Workflows Should Become Team Practices?
Adopt AI workflows whose results engineers can check independently, and keep those that shift hidden work into review and maintenance out of the team standard.
Before You Hire, Find the Queue Slowing Delivery
Delivery delays often come from how work waits between teams, not from a lack of capable people.
Put Capacity Planning on the Product Calendar
A capacity calendar turns commercial forecasts into explicit engineering assumptions, review dates, and reversible choices.
When to refactor a codebase nobody wants to change
Choose between leaving code alone, bounded refactoring and a rewrite by comparing delivery costs, hidden behavior and the evidence needed to contain change risk.
