Stop Picking the "Right" AI Vendor
Why enterprises should optimize for flexibility and reversibility instead of trying to pick the perfect AI vendor in a market that shifts every few months.
Ideas and lessons learned on AI adoption, agentic development, RAG pipelines, and leading technology teams — collected in chronological order.
Why enterprises should optimize for flexibility and reversibility instead of trying to pick the perfect AI vendor in a market that shifts every few months.
The OpenClaw debate isn't really about one tool's security settings. It's exposing a fundamental tension: AI agents need freedom to be effective, but our security frameworks were built for predictability.
Anthropic brings the power of Claude Code to non-technical users with Cowork, and what this means for AI tool companies and enterprise AI strategy.
Ideas on enterprise AI strategy, the return of upfront requirements in an agile world, and why specs have taken the place of code.
Less than 6 months after my original post, not only has the technology improved dramatically, but the market has validated what many of us early adopters suspected: this represents a fundamental shift in how software gets built.
My journey building a RAG pipeline, highlighting lessons learned and best practices for enriching AI responses with relevant enterprise data.
Comparing the shift to AI-assisted coding to the transition from film to digital photography, and what I've learned putting agentic code editors through the paces.
How companies in regulated industries can take an incremental approach to AI adoption, from private chatbots to RAG systems, while managing security and privacy risks.
While automation has brought significant benefits to project management, it is important not to lose sight of the human dimension of this field.