Posts
All the articles I've posted.
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MarkyMarkov - Markov Chain-Based Code Guidance for LLM Agents and Humans Alike
MarkyMarkov uses Markov chains to learn patterns from your codebase and provide fast, explainable code guidance that complements LLM agents.
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Building Smarter AI Agents With Ideas From Philosophy
Updated:Philosophically informed AI agent design — modeling belief, knowledge, and epistemic norms — makes agent behavior more reliable and inspectable.
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Markov chains and LLMs - hybrid architectures for smarter agents
Combine Markov chains with LLMs to build structured, interpretable agents — Markov chains enforce predictable state; LLMs provide semantic flexibility.
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AI Agents in Business Processes: Temporal, FSMs, and MCP
Updated:How to pair agentic workflows with Temporal for durability, finite state machines for structure, and MCP servers to scale from pilot to production.
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Context Management for AI Agents: Why MINDMAP Changes Everything
Context is the most underrated lever in AI agent design — this post makes the case for MINDMAP-style context objects as a first-class agent primitive.
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Cloud LLMs in Production: The Hidden Trust Boundary You’re Already Crossing
Infra teams quietly feed logs, configs, and schemas to cloud LLMs when troubleshooting — extending the trust boundary into a black box they don’t control.
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Software Development Opinions: LLMs, Agentic Tooling, and What Actually Changes
Opinionated notes on software development in the age of agentic tooling — where LLMs genuinely change how we work and where the hype outpaces the reality.
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Using casq for Content-Addressable Storage in CI Pipelines
casq brings content-addressable storage to CI pipelines, eliminating redundant builds and test runs by identifying identical inputs with a git-style hash.