Phase 0 / Preparation
Prepare
Select the pod and representative backlog. Agree on scope, access, safeguards, and a starting baseline before the first change.
Read the Prepare chapterOptional expert support
Build capability through real engineering work.
The coached AI Engineering Capability Program combines preparation with four working weeks. Follow a public curriculum, apply it to real work, and review the evidence with your coach before moving forward.
Five phases
A focused pilot.
A repeatable practice.
Work through Prepare, Execute, Guardrails, Trust, and Scale. The calendar guides the cohort; demonstrated practice determines readiness. Staffing, protected working time, and scope are agreed before kickoff.
Phase 1 / Week 1
Execute
Pair on the problem, document intended behavior, then generate and validate a bounded change on real work.
Read the Execute chapterPhase 2 / Week 2
Guardrails
Strengthen reviewable changes, quality checks, and reusable workflows. Essential safeguards apply from the first change.
Read the Guardrails chapterPhase 3 / Week 3
Trust
Trace unfamiliar behavior, verify explanations, and investigate failures using source evidence and tests.
Read the Trust chapterPhase 4 / Week 4
Scale
Create a playbook, coach a receiving pod, review the pilot evidence, and plan a bounded rollout wave.
Read the Scale chapterMeasure the change
Keep the baseline in the conversation.
Review practice adoption and engineering outcomes weekly. At the end, compare the selected evidence with the starting baseline, retaining work context, source coverage, and limitations.
The program is optional expert support alongside the platform. Program fees, scope, and participation are agreed separately from the software trial.
Start with your engineering evidence
A clearer picture.
A better next move.
Connect your GitHub repositories and start understanding the patterns behind your engineering outcomes.