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Building intelligent agent systems, LLMs, and AI architectures
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An introduction to reinforcement learning
Published: at 10:00 AMThe orientation for working engineers before the rest of the series goes into algorithm internals. What RL is, the vocabulary, the Bellman idea, when to reach for it, and a map of the five posts.
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Inside the Bellman loop: how value actually propagates
Published: at 07:00 PMBellman equations are usually introduced recursively, and the recursion misleads programmers. The runtime is closer to iterative graph relaxation — value sweeping backward through a state graph until it stops moving.
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Inside Microsoft Agent Framework Harness Providers
Published: at 11:00 AMAn LLM in a loop is not enough for production work. This post breaks down the six problems every agent harness must solve — working memory, shared file access, plan/execute modes, task tracking, parallel sub-agents, and tool approval — and how the Microsoft Agents Framework implements them.
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Securing MCP Pipelines with Agent Governance
Published: at 04:00 PMHow to secure Model Context Protocol (MCP) tool usage in sequential agent workflows using Supply Chain Validation and Least-Privilege Sandboxing.