AI in Software Development
Your engineering team shipping more, with AI built into how they work.
Engineering throughput
Your engineers are using AI in pockets and you want it working across the whole delivery process, with the quality, security, and review standards that hold as output goes up.
I help engineering organizations put AI to work across the software lifecycle, from planning and coding to review, testing, and delivery, so the team ships more with the quality bar held.
What you get
- A clear baseline of how your engineers build, review, test, and ship today
- AI coding, review, and testing patterns adopted by your teams, with guardrails
- Agentic workflows for the repetitive parts of delivery
- Quality, security, and review standards that hold as output goes up
- Throughput, quality, and adoption metrics your leadership can see
Best for: VPs of Engineering, CTOs, and platform leads who want AI working inside their delivery.
The delivery loop
AI in every stage of how you ship.
Plan, build, review, test, ship, operate, observe. I bring AI into each stage of the loop, and what the team observes in production feeds straight back into planning. Select a stage to see how it changes and the metric it moves.
The loop runs clockwise and closes. What you observe in production returns to planning.
Selected stage
Plan
I put AI into how the team shapes work, and every cycle starts from what the last loop observed in production, so the metrics and incidents Observe surfaced become the evidence behind the next set of specs. Rough tickets, docs, and threads become clear specs and acceptance criteria the team can build against, with estimates grounded in your own delivery history.
The metric it moves
What shifts, directionally
more throughput per engineer once AI is part of the build and review loop.
of review comments raised by AI before a human opens the pull request.
of engineers adopting the workflow once it is part of how the team builds.
*Illustrative
How the engagement runs
Baseline, roll in, measure and scale.
Baseline how you ship
I look at how your teams plan, build, review, test, and release, and where AI changes the economics of each step.
Roll AI into the workflow
I introduce AI coding, review, and testing patterns and agentic workflows where they fit, with guardrails and standards your teams keep.
Measure and scale
We track throughput, quality, and adoption, and scale what works across more teams.
The guardrails that hold
Output goes up. The bar holds.
As AI raises how much your team ships, these standards stay enforced, so more volume keeps the same quality, security, and review discipline you have today.
- Code review on every change before it merges
- Security and secret scanning in the pipeline
- Test coverage thresholds enforced in CI
- Observability and tracing on everything that ships
- Human sign-off on the critical paths
- An audit trail of what AI wrote and who approved it
The outcome
Engineering ships more, with AI part of how the team works and the quality bar held.
Book an AI Opportunity Review
Book a 30-minute
AI Opportunity Review.
This call is for leaders who want to find where AI can create operational value, what is realistic in their environment, and what to deprioritize now. If we are a fit, I will propose the next step. If we are not, I will tell you directly.
Write to Bruno
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