Thoughts on software, AI, and building things that matter
In this podcast discussion, we explore how enterprise software must evolve to treat AI agents as first-class users, requiring structured interfaces, intentional design, and built-in governance alongside human workflows.
Enterprise software is entering a new era where it must support not just human users, but agents that can participate directly in work.
A reflection on AI literacy from the AI Agent & Copilot Summit, focusing on the shift from using generative AI tools to structuring work, defining accountability, and understanding where human judgment belongs.
A different lens on LLM reasoning. Intelligence may scale with internal computation depth, not just longer chains of thought.
Presented on the evolution of AI literacy at the Community Summit Roadshow: access is no longer the differentiator, structure is.
When tokens get cheap, competition shifts from production economics to systems thinking.
A practical mental model for leaders trying to understand how AI may show up in the broader economy over time.
For technology leaders: why AI coding agents demand a new engineering control model and how specification-driven development enables scale.
Great conversation at Microsoft’s Americas Enterprise Partner Accelerate on what it really takes to drive AI ROI. The organizations seeing results are focused less on technology choices and more on changing how people work with AI agents. Adoption, effectiveness, and trust matter more than demos.
Analyst-Agent Pair for modern teams: practical patterns for agentic workflows with evaluations, observability, and guardrails.
Memory Design for AI Agents: a practical guide to working, episodic, semantic, procedural, and preference memory—with patterns and evaluation tips.
This episode focused on what it really takes to move AI from pilots into production, with an emphasis on AI literacy, data quality, and disciplined execution. We discussed why metrics, guardrails, and thoughtful workflow design matter as much as the models themselves when operationalizing AI at scale.
Most modern, business-focused software systems rely on high-quality data to function effectively. As artificial intelligence continues to shape these systems that support knowledge work, the demand for high-quality, diverse, and reliable data has never been greater.
I recently had the opportunity to join a GovExec webinar focused on how generative AI can help government agencies meet rising public expectations for service quality, responsiveness, and trust.
Explore how AI uses embeddings to understand and retrieve knowledge across different media, enhancing the accuracy of semantic search and boosting productivity for knowledge workers.