20 technical concepts that power AI agents, from CoT and RAG to multi-agent orchestration
goyalshaliniuk · x · 2026-11-06
An infographic walkthrough of 20 core concepts behind building AI agents:
- Reasoning frameworks: goal decomposition, Chain-of-Thought, ReAct (think-act-observe loops), Plan-and-Execute architecture.
- Tools & memory: function calling, dynamic tool selection, long-term vs short-term memory (scratchpad).
- Retrieval: RAG and vector embeddings for searching docs, FAQs and knowledge bases.
- Advanced skills: self-reflection, multi-agent collaboration, agent orchestration, LLM selection & routing, state management.
- Safety & deployment: observability/logging, error handling with retry logic, human-in-the-loop, API/UI deployment.
The author's point: prompting alone won't cut it — these concepts separate demos from deployable products.
More from coding & agent
- Adding 80+ biomes to Minecraft: AI-generated specs for ores and textures — Promptmethus · 2026-11-06
- Write decision logs: five lines per decision can save your team a whole meeting — dSebastien · 2026-11-06
- Gemini CLI PR fixes OOM in long agentic sessions with 64KB tool output budget and inlineData eviction — tadipavan · 2026-11-06
- Technical explainer: how the open-source Row-Bot agent handles memory — Acceptable-Object390 · 2026-11-06
- Hygieia: open-source ontology audit tool for AI app health — n0hatr3d0nlyhe4rt · 2026-11-06
- Meta's Kats: an all-in-one Python toolkit for time series analysis — mdancho84 · 2026-11-06