Senior engineers, AI-multiplied: judgement scales, throughput follows.
Workshops, paired sessions, and a playbook that survives the trainer leaving. AI-first development becomes a team capability, not an individual skill.
Why this engagement exists.
Sending engineers to a one-day course produces inconsistent results. Real AI-first proficiency comes from working on real code with senior practitioners alongside. Our training is structured around the workflows your team actually runs, and it ends with a playbook your team owns.
Deliverables, not promises.
Every engagement ships these artefacts. Nothing here is fluff. Each item is something your team will hold in their hands at the end.
Entry skill assessment
Baseline per developer so the gains we report later are anchored to real starting points.
Workshop series
3-5 sessions covering setup, workflow patterns, prompt design, code review, the discipline.
Paired coding sessions
Working on real PRs alongside senior practitioners, the highest-leverage part of the engagement.
Code review + insights
AI-aware code review on your team's actual PRs, with patterns documented as they emerge.
Playbook + prompt library
Living playbook + a shared prompt library curated from what your team actually uses.
Exit + 30-day assessment
Skill assessment at exit and again 30 days later, so we know the proficiency held.
The process, step by step.
No mystery, no consultant theatre. This is how the work actually flows from kickoff to handover.
- Step 1
Baseline assessment
Per-developer skill mapping so coaching is tailored, not generic.
- Step 2
Workshop series
Live or recorded: 3-5 sessions covering the technique + the discipline.
- Step 3
Paired sessions on real work
Working alongside senior practitioners on real PRs. This is where most of the proficiency forms.
- Step 4
Playbook capture
Document the patterns your team is converging on. The playbook is a living artefact, not a static doc.
- Step 5
Exit + 30-day check-in
Skill assessment + a follow-up so we know the change held when we stopped showing up.
Most effective for 5-50 engineers, but it scales to org-wide rollouts: larger teams run a cohort, train-the-trainer model. They train one cohort, then have that cohort train the next. Compounds faster than centralised training. Pair it with Adoption Measurement to put a number on the throughput gain.
Measure the ROI with Adoption MeasurementThe questions that actually come up.
Best for 5-50 engineers. Larger teams use a cohort approach, typically 2-3 cohorts of 15-20 engineers each.
Related services
All servicesTooling Setup
Cursor, Claude Code, Copilot, set up correctly with your codebase context, your style guide, and your security boundary. Every engineer productive from week one.
Adoption Measurement
Track AI usage, throughput delta, defect rate, time-to-merge. The dashboard you wish your VP of Engineering had.
AI Strategy & Roadmap
A 4-6 week engagement that takes you from "we should do AI" to a roadmap, an architecture, and a team plan you can defend in the next board meeting.
Ready to scope Team Training?
A 30-minute call. We map your situation against the engagement, give you a real estimate, and tell you honestly whether we are the right team for this.