Four days, 300 speakers, 39 tracks. Five themes carried across all of it: harness engineering and software factories, agent loops, evals and observability, the unsettled argument about agent memory, and the shift from burning tokens to proving value.
Read postRouting requests to the right specialist and executing each as a multi-step agentic task are two different jobs. This reference design treats the responsibilities separately.
Read postA feature-by-feature comparison of LangGraph, LangChain, CrewAI, AWS Strands, Google ADK and deepagents, built as a decision matrix you can weight against your own needs.
Read postRouting only pays off if the application survives the swaps. What it takes to move between models without rewriting logic or shipping silent regressions.
Read postSending each request to the cheapest model that can actually handle it is a potential cost lever — and done well it improves quality at the same time.
Read postA historical qualitative guide to agent libraries, platforms, and runtimes, with corrected portability and product categories.
Read postWhen we talk about AI agents, it helps to think in human terms. A useful agent system needs a skeleton, hands, a mind, a brain, a library, a body, guardrails, and skin.That’s not poetry — it’s the anatomy of every serious agent framework being built today. And the leaders across Anthropic, OpenAI, Google, AWS, Microsoft, …
Read postThis week, I’ve been deeply focused on agentic AI—especially combining the Q Developer CLI with AWS tools. It’s been an intense stretch, pushing toward a milestone and ironing out the complexities of making agentic workflows more seamless. One thing that really stands out: agentic AI is incredibly powerful for troubleshooting. It can iterate over and …
Read postHow orchestration frameworks, model reasoning, coordination, and managed runtimes fit together.
Read postThis is my breakdown of what AI tooling really feels like—part myth-busting, part field manual, and all grounded in lived experience. Spoiler: AI isn’t a magic wand. It’s a fleet of brilliant but forgetful minions. 🧩 Myth 1: “AI is a computer with a natural language interface.” False. This might be the most dangerous misconception …
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