Gary Davidson · Savviety AI Lab
Software engineering experience, applied to AI.
I'm a software engineer, architect, and technology leader. I've built platforms and led engineering teams in startups and enterprises, with responsibility for getting the software delivered.
That's the experience I bring to AI. I decide what to build and how the system should fit together, then work through implementation and check that it does what it needs to. The code and decisions are in my public projects.
The experience behind the work
- 6 startups
- Four exits during my operating career
- Since 2016
- Fractional CTO practice at Savviety
- Applied AI
- Hands-on engineering, architecture, and delivery
I built and scaled Interclick's ad-targeting platform and led Kroger's first cloud implementation. I also held an engineering leadership role at Magic Leap. I draw on that work when building AI systems today.
What that looks like in my AI projects
Software engineering
I want code that's easy to maintain and tests that catch failures. That starts with deciding what correct means. In savviety-instinct, independent checks found three bugs the original tests missed.
Architecture
What should each part of the system do, and what happens when a dependency fails? In kb, I separated local note capture from retrieval that needs a network connection.
Delivery
An uncertain goal needs a defined scope and a way to check the result. For opening-dojo, I directed the work from requirements through review, using AI to help build the application.
Tell me what you need the software to do and what constraints you're working with.