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Love Playwright? Keep it. agent-qa is for the tests you're tired of maintaining, and it remembers.

Playwright is a superb browser automation engine you program in TypeScript, Python, or Java. agent-qa operates a layer above: you state intent in plain English and the runtime plans, executes, adapts, and remembers.

Try agent-qa, the source-available AI layer that turns test intent into runs that remember.

agent-qa vs Playwright

Capabilityagent-qaPlaywrightDetails
Plain-English authoringPlaywright tests are code, powerful, but every flow is programming work. agent-qa tests state user intent in natural-language YAML that anyone on the team can read and review.
Survives UI changesPlaywright selectors and assertions break when the UI shifts, and a human fixes them. agent-qa re-plans from intent, caches the corrected plan, and records the change in memory.
Execution memoryPlaywright starts every run stateless. agent-qa accumulates file-backed behavioral memory, making later runs faster and more reliable.
Source accessPlaywright is open source; agent-qa is source available under FSL-1.1-ALv2. Both keep tests in the repo with no required platform or seats.
Local and CI executionBoth run from a laptop, CI job, or automation pipeline with source-controlled commands.
Mobile app testingPlaywright targets browsers (with experimental Android support). agent-qa covers native Android and iOS flows with the same YAML contract as web.
Coding-agent nativePlaywright has MCP-based browser control for agents; agent-qa ships a full agent QA loop, MCP tools, Skills, run artifacts, failure classification, and memory.
Selector maintenanceagent-qa eliminates the selector-upkeep tax that consumes most Playwright suite maintenance time. 'Yes' here means no selectors to maintain.

Why teams add agent-qa alongside Playwright

Stop paying the selector tax

Mature Playwright suites spend more engineering time on upkeep than on new coverage, every redesign breaks locators that encoded yesterday's DOM. agent-qa tests encode intent, so the runtime re-derives the steps when the UI moves on.

Coverage at the speed of English

A new Playwright spec is a programming task. A new agent-qa test is a paragraph. Teams cover the long tail of flows, the ones nobody had time to script, because writing them costs minutes, not hours.

Your coding agents get a QA loop, not just a browser

Playwright MCP lets an agent drive a browser; it doesn't give it a testing discipline. agent-qa gives agents the whole loop: author from product context, validate, run, read artifacts, classify failures, and remember, via MCP tools and packaged Skills.

Playwright is a brilliant engine for programmed browser automation. agent-qa is the layer above it, intent in, verified behavior out, memory retained. Most teams need the layer more than another script.

Frequently asked questions

Does agent-qa replace Playwright?

It replaces the hand-written E2E layer for many teams, and complements Playwright for others. If your pain is authoring and maintaining flow tests, agent-qa's natural-language tests with memory remove most of that work. Teams with deep custom automation keep Playwright for it and let agent-qa own the user-flow regression layer.

Is agent-qa licensed like Playwright?

No. Playwright uses the Apache 2.0 open-source license; agent-qa source is available under FSL-1.1-ALv2 and transitions to Apache 2.0 under its future-license terms. Its tests, config, hooks, memory, and artifacts remain files in your repository.

What does agent-qa cost compared to Playwright?

Playwright is free under Apache 2.0. agent-qa has no paid tier or license fee for FSL-permitted use, but it consumes model calls, reduced by its plan cache, from whichever LLM provider you configure. The operating-cost comparison is therefore engineer-hours, LLM tokens, and infrastructure.

Can I migrate my Playwright tests to agent-qa?

Yes, and it's usually simplification: each spec's intent, 'sign in, add item to cart, verify total', becomes a short plain-English YAML test. You delete selector logic rather than porting it.

Is natural language reliable enough for CI?

agent-qa is built for exactly that: deterministic YAML contracts, cached action plans reused across identical runs, file-backed memory reducing exploration, and artifacts plus failure classification for every step. It behaves like a test harness, not a chatbot.

Sources

This page is based on public product and documentation sources. Verify current features and pricing with each vendor before making a purchase decision.

Where agent-qa pulls ahead of Playwright

The parts of agent-qa that answer what Playwright leaves you carrying.

Natural-language tests

Write actions and assertions in plain English; agent-qa resolves them against the live interface.

Learn about natural language tests

Plain-English YAML

Describe the behavior once; it stays as reviewable YAML in your repository.

Learn more

User-facing targets

Name visible controls and labels instead of brittle selectors.

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One format everywhere

Use the same test structure on web, Android, and iOS.

Learn more

Execution memory

Turn successful runs into reviewable, evidence-backed memory that makes every future run faster.

Learn about memory

Reviewable bundles

Every learned fact ships with its evidence as files in your repository.

Learn more

Proven before it is used

New knowledge must pass replay and live evidence before guiding a run.

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Faster warm runs

Reuse proven flows and supersede stale facts instead of rediscovering them.

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Self-healing execution

When an action fails, agent-qa re-observes the screen and finds another route to the same outcome.

Learn about self-healing

Re-observe, then re-plan

After a failed action, agent-qa reads the screen and plans again.

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Same outcome only

Recovery is accepted only when it completes the requested step.

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An honest trace

Every failed, retried, and refused action remains visible.

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Sandboxed hooks

Run Node, Bun, Python, or Bash hooks in isolated containers and pass structured results back into the test.

Learn about hooks

Four runtimes

Write hooks in Node, Bun, Python, or Bash.

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Isolated execution

Read-only containers cap resources and can block network access.

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Structured outputs

Hooks return dotenv values that later steps can reuse.

Learn more

* This comparison is based on publicly available information. Product capabilities and pricing can change; verify details with each vendor before making a purchase decision.