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Glossary · Concepts

RPA vs agentic automation

RPA follows brittle, hand-recorded scripts; agentic automation has a model plan against the live page — then compiles the result so it can replay cheaply.

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What is rpa vs agentic automation?

Robotic process automation (RPA) executes pre-recorded, rule-based scripts tied to specific UI coordinates or selectors, which break when a page changes. Agentic automation uses a language model to perceive the page and plan actions toward a goal, adapting to layout changes. Twin’s model compiles a successful agentic run into a skill, so you get RPA-like cheap repeatability without RPA-like brittleness.

Why it matters

Pure RPA is cheap to run but expensive to maintain; pure agentic automation adapts but pays the model every run. Compile-once-then-replay is the synthesis: a model figures the flow out, and a deterministic skill runs it — the wedge for teams replacing legacy RPA.

See it in context: read how Twin compiles and replays a run, follow the cost-cutting guide, or browse use cases and comparisons.

Related terms

Skill compilation

Turning a successful agent run into a reusable, replayable skill — a compact program of indexed actions you can call again without re-planning.

Deterministic replay

Re-running a compiled skill as a fixed sequence of indexed actions, with zero LLM calls, so the same goal produces the same path every time.

Human-in-the-loop handoff

Pausing a run at a step that needs a person — an approval or an MFA prompt on an authorized flow — then resuming automatically once it’s cleared.

Browser execution layer

The infrastructure that turns an agent’s goal into deterministic, replayable browser action — the layer between your LLM and a real browser.

Back to the full glossary

Run your first skill

Give an LLM agent a real browser, compile the workflow once, and watch the marginal cost fall as the cache takes over.

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