Plain-language field notes on software, AI, ecommerce, automation and the decisions that make technology produce a real return.
AI Engineering
A practical architecture for moving AI agents beyond impressive demos into controlled workflows that teams can trust, monitor and improve.
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AI Engineering
What MCP changes for enterprise integrations, where it fits, and the security decisions teams should make before exposing tools to an AI application.
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AI Engineering
A decision framework for choosing retrieval, large context windows, fine-tuning—or a deliberate combination—for a production AI application.
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AI Engineering
A practical evaluation system for turning subjective AI demos into measurable product quality gates before and after launch.
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AI Engineering
When specialised AI agents improve a workflow, when one well-designed agent is enough, and how to test the difference objectively.
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