RUNLOCALAIv38
->Will it run?Best GPUCompareTroubleshootStartLearnPulseModelsHardwareToolsBench
Run check
RUNLOCALAI

Independently operated catalog for local-AI hardware and software. Hand-written verdicts. Source-cited claims. Reproducible commands when we have them.

OP·Fredoline Eruo
DIR
  • Models
  • Hardware
  • Tools
  • Benchmarks
TOOLS
  • Will it run?
  • Compare hardware
  • Cost vs cloud
  • Choose my GPU
  • Prompting kits
  • Quick answers
REF
  • All buyer guides
  • Learn local AI
  • Methodology
  • Glossary
  • Errors KB
  • Trust
EDITOR
  • About
  • Author
  • How we make money
  • Editorial policy
  • Contact
LEGAL
  • Privacy
  • Terms
  • Sitemap
MAIL · MONTHLY DIGEST
Get monthly local AI changes
Monthly recap. No spam.
DISCLOSURE

Some links on this site are affiliate links (Amazon Associates and other first-class retailers). When you buy through them, we earn a small commission at no extra cost to you. Affiliate links do not influence our verdicts — there are cards we rate highly that we don't have affiliate relationships with, and cards that sell well that we refuse to recommend. Read more →

© 2026 runlocalai.coIndependently operated
RUNLOCALAI · v38
Glossary / Agents & agentic AI / AI Agent
Agents & agentic AI

AI Agent

An AI agent is software that uses an LLM to decide what to do, takes actions, observes results, and iterates toward a goal. Unlike a chatbot that just generates text, an agent has tools, memory, and a loop.

Anatomy: a planning step (LLM generates next action), a tool layer (executes that action — read file, run shell command, search web), an observation step (feeds result back into LLM context), and termination logic (when does the loop stop?). The simplest agent is "ReAct" — Reasoning + Acting in alternation.

Examples: Coding agents like Claude Code, Cursor's agent mode, Aider, Cline, Codex. Browser agents that operate web pages. Workflow agents like Devin or Replit Agent 3 that run for hours on tasks. For local-only agents: Open Interpreter, Aider with a local Ollama backend, Continue.dev with local models. The agent quality scales hard with model quality — a 7B local agent is meaningfully worse than Claude Sonnet on multi-step tasks.

Related terms

Function Calling / Tool UseMCP (Model Context Protocol)

See also

tool: claude-codetool: cursortool: aidertool: clinetool: opencode
Buyer guides
  • Best GPU for local AI →
  • Best laptop for local AI →
  • Best Mac for local AI →
When it doesn't work
  • CUDA out of memory →
  • Ollama running slowly →
  • ROCm not detected →