Tag: agents
All the articles with the tag "agents".
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Currying agents
How one can leverage partial application of agents - borrowing from the functional programming paradigm.
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Linear Types for Agent Safety - An Approach to Trustworthy AI Systems
Discussing a type system that rejects unsafe code before it ever runs.
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MarkyMarkov - Markov Chain-Based Code Guidance for LLM Agents and Humans Alike
MarkyMarkov - a PoC leveraging Markov chains for coding - shows that small, interpretable probabilistic models add high value to code workflows. By learning patterns from your own codebase, Markymarkov provides fast, explainable guidance that complements existing tools rather than replacing them.
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Building Smarter AI Agents With Ideas From Philosophy
Updated:Philosophically informed agent design means explicitly modeling what an AI believes, how it knows things, and which moral and epistemic norms guide its decisions, so that its behavior becomes more reliable, inspectable, and aligned with human expectations.
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Markov chains and LLMs - hybrid architectures for smarter agents
How to combine Markov chains with large language models to build more structured, interpretable, and efficient agents. Markov chains provide structure and efficiency; LLMs provide semantic understanding and flexibility.
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Notes on agentic applications in business processes
Updated:This post explores how to pair agentic workflows with durable workflow engines (specifically Temporal), add structure using finite state machines, plug in MCP servers for tools, and grow from a small pilot into stable, production-ready workflows.
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Context, context, context
Context—or how I learned to love the MINDMAP
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Cloud LLMs in prod...
Modern infra teams are quietly feeding their most sensitive data—logs, configs, schemas—into cloud LLMs just to get unstuck. It feels like harmless troubleshooting, but in reality it extends your trust boundary into a black box you don’t control or fully understand.