INTEGRATED
COGNITION.

THE AGENTS FIELD GUIDE

AI agents can act. Judgment still matters.

An agent can use tools and take several steps toward a goal. Its value depends on the task it is given, the information it can access, the actions it may take, and the person responsible for checking the result.

Diagram of an AI agent moving from a goal through a model, selected tools and observations, with human approval at an action boundary
A useful agent is defined as much by its boundaries as by its tools.

THE PRACTICAL TEST

Four questions before an agent acts.

  1. 01Read

    Which documents, systems, and matter data can it access?

  2. 02Decide

    Which next steps can it choose within a task?

  3. 03Change

    May it alter files, records, or work product?

  4. 04Send

    Can it communicate or submit anything outside the firm?

A PATH THROUGH THE SECTION

Understand. Apply. Control. Evaluate.

Begin with the mechanism, then follow an example through the decisions, permissions, and tests that make it usable in legal practice.

  1. 01 / UNDERSTAND

    What is an AI agent?

    Follow the model, tool, and feedback loop. Separate conversation context and stored memory from model training.

    Understand the system
  2. 02 / APPLY

    Agents in legal workflows

    Walk through bounded research, drafting, and review tasks with visible lawyer checkpoints.

    Trace the work
  3. 03 / CONTROL

    Permissions and oversight

    Decide what an agent may read, draft, modify, or send, and when it must stop for approval.

    Set the boundaries
  4. 04 / EVALUATE

    Evaluate an AI agent

    Run a matter-based pilot. Score source support, missed issues, unauthorized actions, and the full time spent on review.

    Use the scorecard

GO DEEPER

Build a fuller mental model.

The four guides above provide the path. These deeper references explain the system underneath it, the ways it can fail, and the decisions involved in adoption.

KEEP EXPLORING

Examples and perspectives, with their limits in view.

Connect the core guides to a bounded prototype, the assistant concept, and a dated prediction reassessed with current evidence.