Independent buy-side technical due diligence
Most engineers who can assess an AI-built codebase have never sat on the buy side. I've done both — five AI-capability acquisitions at Amazon, and production software shipped solo this year.
Typically two to four weeks, run on your deal timeline. One assessor, close to the code.
The same assessment, run before a process starts — so the findings are yours to fix, not the buyer's to discount.
For portfolio companies, after the deal — where the engineering risk actually gets managed.
The Framework
A public rubric for AI-assisted codebases. Each criterion becomes a rated finding in the register you hand your investment committee.
A Spain relocation planner — getcamino.app. Empty repo to live product in under a week: ~13,700 lines of TypeScript, five languages, iOS shipped. The build log documents how it was engineered.
Distributed file infrastructure, in progress — silthq.com.
Source available for the projects above on request, or on GitHub — engineered to the standard the framework describes.
Nearly thirty years in engineering leadership — CTO, VP Engineering, and principal-level roles. Principal, M&A Technology and Engineering Integration at Amazon, leading five strategic AI-capability acquisitions for AWS, buy-side. CTO at Woot.com. Engineering leadership at Twitch. AI-first SaaS transformation at Valdera. Computer Engineering, USC. Based in southern Spain; work is remote — deal timelines are the constraint, not geography.
Selective advisory and fractional engagements are taken by referral.