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The learn layer of the AgentsKit ecosystem

AI Summary Hub

Open AI knowledge wiki — concise, source-cited summaries on modern AI engineering.

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# 290+ source-cited AI summaries, agent-ready
290+
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50+
Categories
EN / pt-BR
Languages
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Browse by topic

Hand-curated summaries linking to primary sources.

Fundamentals

Core ideas behind learning, representation, and generalization.

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Prompt Engineering

Patterns and parameters that make LLM outputs predictable and useful.

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AI Agents

Systems that perceive, reason, and act toward goals.

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Retrieval & RAG

Grounding LLMs in trusted, retrievable knowledge.

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MLOps

Reliable training, deployment, and monitoring of ML systems.

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Claude Code

Anthropic CLI, agent SDK, MCP, skills, and context management.

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01

Source-cited

Every summary links to primary papers, docs, or repos — no hand-wavy claims.

02

LLM-friendly

Dense, structured pages designed to drop straight into an agent context window.

03

No paywall

Fully open knowledge. Read it, share it, fork it, translate it.

Part of the AgentsKit ecosystem

Learn the concepts here, then take them to production.

  1. 01LearnYou are here

    Concepts, cited — right here

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  2. 02Build

    Agents in JavaScript with AgentsKit

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  3. 03Ship

    Orchestrate in production with AKOS

Build

AgentsKit

Ship AI agents in JavaScript without gluing 8 libraries together. Chat UI, runtime, tools, memory, RAG, and guardrails in one ecosystem.

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Ship

AKOS

The AgentsKit control plane — orchestration, governance, and observability for running agents in production at scale.

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Built for engineers who want to learn AI deeply.

No paywalls, no fluff — just concise, cited summaries.

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