AI-assisted development adoption
I help CTOs, engineering managers, and platform teams set up coding-agent usage: project rules, CI gates, human approval, and measurement. We usually start with a pilot on one squad before expanding.
- 3 to 5 day audit: SDLC, risks, roadmap, and quick wins.
- 2 to 4 week pilot: one squad, one workflow, two metrics.
- Enablement: playbooks, office hours, onboarding.
1. Audit
Map the delivery cycle, tools already in use (including shadow IT), and secret / IP / data-residency risks.
Deliverable: short findings, a draft risk policy, and a targeted pilot proposal. Compact enough to review in one meeting.
2. Pilot
One willing squad, one workflow (PR review assist, test generation, rules + CI check, and similar). Agents open draft PRs; humans merge.
We track two metrics, for example PR cycle time and first-try CI green rate. We skip counts of lines generated by AI.
3. Enablement (and separate product work)
Workshops, office hours, and playbooks so the practice holds after the engagement. Model and tool policy for new hires.
On request: building LLM products for your end users (RAG, Text-to-SQL, business agents). Separate from adoption work.
Let's talk about your eng team
If you are stuck between FOMO and a total ban on coding agents, a paid audit clarifies the next step in under a week.
After a pilot, rules, gates, and playbooks stay in your repos. You keep control of the process without depending on a tool I take away.
Request an audit