Layer 8 · Agents

Systems that pursue a goal over many steps: plan, act with tools, check the result, repeat.

In simple words: AIs that are given a goal and work through the steps themselves: plan, act, check, repeat.

Draft, awaiting expert review, reviewed 2026-10-02

Like: A new employee given a goal instead of a script: they work out the steps, use the office tools and check their own work.
Where it breaks: An employee builds judgement over months. An agent's 'experience' is only what fits in its context and memory, and it can repeat a mistake confidently.

What it gives the layer above

Completed multi-step tasks, not just single answers.

What it needs from the layer below

Tools, retrieval and model calls arranged by Orchestration & Tooling.

Concepts

• The agent loop
  Plan, act with a tool, observe the result, and repeat until the goal is met.
• Agent harnesses
  The program wrapped around a model that turns it into an agent: it runs tools, asks permission, manages context and keeps memory.
• Coding agents
  Agents that work inside a code repository: read files, make edits, run commands and tests, and iterate until the checks pass.
• Computer & browser use
  Agents that operate a screen like a person: look at a screenshot, then click, type and scroll.
• Multi-agent systems
  Several agents with different roles or contexts work together on one task.

Walkthrough

1. A goal, not a script. Someone asks: “fix the failing login test”. The agent loop starts: read the code, choose a step, act, look at the result, repeat.
2. The harness keeps it safe. The harness runs each tool call, asks before risky commands, and trims the context so the long task still fits.
3. A coding agent does the work. Inside the harness, a coding agent edits two files and reruns the tests until they pass.
4. Checking the real page. To be sure, it opens the login page in a browser, takes screenshots and clicks through it, like a person would.
5. Splitting the job. For a bigger change, a lead agent hands tests and review to sub-agents, each running its own loop.

Examples

• Agent harnesses (Claude Code, OpenCode, OpenClaw, Hermes Agent)
• Coding agents
• Computer and browser use
• Research agents
• Multi-agent systems