AI Delivery System Audit

AI coding tools are already inside the engineering workflow. The harder question is whether the system around them can absorb more generated work without creating review bottlenecks, weak proof standards, delivery risk, or fake ROI stories.

The AI Delivery System Audit is a compact advisory engagement for engineering leaders who want a practical second opinion before expanding AI usage or standardizing new team practices.

Best Fit

• Your team is already using or piloting AI coding tools.
• Developers feel faster, but delivery does not feel more predictable.
• Review load, PR quality, rollout confidence, or measurement is getting messy.
• You need a grounded 30-day path, not a giant transformation program.

What We Look At

• Where the current bottleneck sits: specification, implementation, review, QA, release, or production follow-up.
• Whether AI-assisted PRs carry enough proof for reviewers to trust them.
• Whether your metrics distinguish adoption from real delivery impact.
• Whether agent access, credentials, MCP config, or workflow permissions have clear ownership.
• Which lightweight operating changes would create the most leverage next.

Format

• A short intake on team size, tools, workflow, and known friction.
• A 90-minute working session with the relevant engineering leader and owners.
• A recommendation memo with the main bottlenecks, risks, and next 30-day changes.

The Output

You leave with a clear diagnosis of where AI is helping, where it is moving the bottleneck, and what to change next in the delivery system.

If this is live for your team, send me a note and we can compare notes.