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Welcome to danieledwards.ai

Thoughts on AI engineering, agentic systems, and Context Engineering — plus the unglamorous production work that separates demos from systems. Here's what you'll find on this site, what I plan to write about, and how to reach me.

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Welcome to danieledwards.ai — Thoughts on AI engineering, agentic systems, and Context Engineering. Four-pillar overview of Context Engineering, Agentic Systems, Production Hardening, and Regulated Industries with a portrait of Daniel Edwards and an agent-architecture diagram.

This site is the home for my writing on AI engineering, agentic systems, and what I've been calling Context Engineering — the discipline of designing the data structures, system boundaries, and information flows that let AI systems operate reliably at scale.

If you're here looking for a quick read on me, the About page is the right starting point. If you want the formal version, the Resume covers eighteen-plus years of progressive technical and leadership work, from agency web through headless commerce and into AI engineering leadership.

What I'll be writing about

I'm planning to publish on a few overlapping themes:

  • Context Engineering in practice — how I think about prompt caching, tool surfaces, memory architectures, and information flow across agent boundaries when shipping AI in production.
  • Agentic systems — multi-agent orchestration patterns, harness engineering, and what actually breaks when you go beyond demos.
  • Production hardening — eval-driven CI, cost management, prompt-injection defenses, and the unglamorous work that turns a demo into a system.
  • Lessons from regulated industries — applying the above in healthcare (HL7 / FHIR / HIPAA), commerce (PCI), and B2B (SOC 2) settings, where the eval bar isn't optional.

I'd rather publish less and mean it than churn out generic content. Expect detailed posts with real examples and the occasional opinionated take.

How to reach me

The fastest paths are LinkedIn and the contact form on this site. If you're building something in AI engineering, especially in regulated domains, I'd genuinely like to hear about it.

— Daniel