QA for the agentic era.
I use AI agents to generate, run, and triage tests at scale — then apply human judgment where it counts. Fewer escaped bugs, faster releases.
The Problem: QA Can't Keep Pace
Shipping fast is the easy part. Shipping fast and tested is where teams stall — coverage lags, triage piles up, and flaky tests quietly erode trust in every release.
Coverage You Can't Close Fast Enough
Features ship faster than a manual QA process can cover them. The untested paths are exactly where the next production bug is hiding — and agents can close that gap in days, not quarters.
Triage Eating Your Engineering Hours
Every red build pulls an engineer off real work to dig through logs and reproduce failures by hand. That's exactly the repetitive, pattern-matching work agents do in minutes instead of hours.
Flake Nobody Can Pin Down
Tests that pass locally and fail in CI erode trust until a red run means nothing. Root-causing flakiness by hand is a time sink — and the kind of needle-in-a-haystack hunt AI is genuinely good at.
What “AI-augmented” actually means
No buzzwords. Here's the exact loop I run on every engagement — and what the agents hand back at each step.
Generate
Agents read your app and draft E2E coverage for the flows that matter — dozens of tests in the time a manual pass writes one.
Run
The suite runs across browsers and devices in CI on every push, capturing traces, screenshots, and video on any failure.
Triage
Agents cluster failures, separate real regressions from flakes, and pinpoint the likely root cause before a human looks.
Review
I review every diff and every triage call. Agents do the volume; human judgment decides what actually ships.
Representative example — the workflow, not a specific client
import { test, expect } from '@playwright/test'; // Drafted by an agent from the live checkout flow.test('guest checks out with a saved card', async ({ page }) => { await page.goto('/cart'); await page.getByRole('button', { name: 'Checkout' }).click(); await page.getByLabel('Email').fill('buyer@example.com'); await page.getByRole('button', { name: 'Use saved card' }).click(); await page.getByRole('button', { name: 'Place order' }).click(); await expect( page.getByRole('heading', { name: 'Order confirmed' }), ).toBeVisible(); await expect(page).toHaveURL(/\/orders\/[a-z0-9]+/);});When the “Use saved card” button renders before the card list finishes loading, the agent flags it as a race condition — not a real regression — adds an explicit wait, re-runs the suite green, and posts the trace to the PR. No engineering hours spent reproducing it.
Want to watch this run against your app? Book a free QA audit
What I Do
Specialized automation for the flows that matter most — web, mobile, and the pipeline that ties them together.
QA Foundation
A fixed-scope QA setup that takes you from zero to a trustworthy automated suite — running in your pipeline in two to three weeks.
- QA audit of your current state
- Core E2E suite for your top user flows
- CI integration with PR-gated runs
- Handoff docs + a live walkthrough
Sam Adams
QA Engineer, Experior QA· Salt Lake City, Utah
I'm a quality engineer who builds test automation for teams that ship fast. Experior QA is just me — which means you work directly with the person writing your tests, not an account manager.
My approach is AI-augmented: I lean on agents to draft coverage and chase down flakiness at a pace a traditional QA hire can't match, then apply hands-on judgment to make sure the suite tests what actually matters. The result is broad, reliable coverage delivered in days, not quarters.
Get Your Free QA Audit
Drop your email and a note about your app — I'll get back to you with where to start.