COMPUTER USE / HUB

The computer-use field guide.

Understand the category, choose the architecture and evaluate the evidence.

A practical definition of AI that observes interfaces, chooses actions, and checks what happened.

Choose an adaptive agent, a deterministic browser script, or a hybrid based on the part of the workflow that changes.

Separate adaptive interface reasoning from the orchestration and operating model of robotic process automation.

Prefer a supported structured integration where it covers the job; use interfaces deliberately for the remaining gap.

MCP connects an AI application to capabilities. Computer use is one capability that a connected tool may expose.

Choose the execution surface first: a web-only job needs different controls from a workflow spanning the desktop.

Follow a single task through observation, planning, execution, validation, and recovery.

Shortlist by environment and operating constraints, then test on a task with a checkable result.

Model, orchestration, controller, runtime, identity, and evaluation each answer a different part of the job.

Count the whole run, including failed attempts, browser time, model use, and human review.

Read the version, task set, harness, and metric before comparing the score.

Native application tasks need an environment-specific benchmark and a result that can be checked outside the agent.

Use a compatibility checklist before putting two published scores in the same ranking.

A higher success rate and a lower per-run price describe different parts of the decision.

Identify who designed, executed, scored, and published the evaluation before interpreting the result.