5d ago · 7 min read · AI agent persistent memory is the mechanism that allows an artificial intelligence agent to retain information and context across multiple interactions, sessions, or even application restarts. This capability is fundamental to building stateful AI ag...
Join discussion5d ago · 4 min read · AI agent long memory refers to an AI's capability to retain and access information beyond immediate context or a single session, enabling persistent recall. This allows agents to learn from past interactions and offer consistent, context-aware respon...
Join discussionMar 16 · 2 min read · The skills-vs-agents debate gets framed as a technical question. It isn't. It's a question of whose incentives are embedded in the architecture. OpenAI's Agents SDK rebuilds API interactions around loops. Each loop is multiple inference calls. Multip...
Join discussionMar 12 · 16 min read · TLDR: A tool is a single callable capability (search, SQL, calculator). A skill is a reusable mini-workflow that coordinates multiple tool calls with policy, guardrails, retries, and output structure. If you model everything as "just tools," your age...
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Mar 12 · 15 min read · TLDR: If tools are primitives and skills are reusable routines, then the skill registry + router + evaluator is your production control plane. This layer decides which skill runs, under what constraints, and how you detect regressions before users do...
Join discussionFeb 24 · 4 min read · The thing nobody tells you about building autonomous agents is that they optimize for silence. I've been running MirrorSwarm — my multi-agent orchestration system — and watching agents complete tasks with outputs like "Build session completed." One l...
Join discussionApr 22, 2025 · 2 min read · Building AI agents using Model Context Protocol (MCP) tools enables dynamic tool integration and automated task execution. This guide provides a structured approach to creating MCP-powered agents using modern frameworks and libraries. Environment Con...
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