Field Notes
Articles
Practical thinking on applied AI systems, LLM visibility, and what it takes to deploy AI that produces outcomes.
These are working notes from someone who builds and deploys AI systems, written for operators and founders who want mechanics, not headlines.
Applied AI Systems
How to scope, build, and deploy AI systems that produce measurable outcomes in real workflows.
LLM Discoverability
How organizations become findable, retrievable, and recommendable by language models.
The Operator Perspective
What six years of running real digital operations taught me about building AI systems that work.
Start Here
Not sure where to begin? These three articles cover the foundations.
- What Is an Applied AI System? - the clearest definition of what this work actually is.
- What LLM Discoverability Actually Means - why visibility and discoverability are not the same thing.
- Why Operators Build Better AI Than Engineers - the case for outcome-first thinking.
Ready to Build?
If you want practical, outcome-first guidance on applied AI systems and LLM strategy, let's talk.
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