AI Writes the First Draft, Engineers Ship the Test
We use LLMs to generate, maintain, and triage tests faster - then senior SDETs review and harden every output. More coverage, sooner, without the AI-slop test suite.
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AI-augmented test generation uses LLMs to draft, maintain, and triage tests faster - then has senior SDETs review and harden every output. You get more coverage sooner without the AI-slop suite that catches nothing.
Where AI Actually Helps - and Where It Doesn’t
Let’s be honest about the hype. AI is genuinely good at some parts of testing and genuinely dangerous at others. It’s fast at generating first-draft tests, proposing edge cases you’d have missed, healing brittle selectors, and triaging failures. It’s terrible at judgment - it will cheerfully write a hundred assertions that pass no matter what the app does, so you get something that looks like coverage and catches nothing.
The whole method here is to use AI for speed and humans for judgment. AI writes the first draft; an engineer ships the test.
What We Do
Fast generation, hard review - we use LLMs to draft tests for your untested backlog and to suggest edge cases at a pace no human matches. Then our engineers review every one: killing shallow assertions, adding checks that actually mean something, and fixing the subtle wrongness AI loves to produce. What merges is real coverage, not volume.
Self-healing selectors - locators that recover from small UI changes instead of hard-failing on one brittle path. This cuts the routine locator maintenance that quietly eats a chunk of every week. We’re clear about the limits - they won’t survive a full redesign, and we won’t pretend otherwise.
AI-assisted triage - when a test fails, AI helps sort real bug from flake faster, so failures get looked at instead of ignored.
Guardrails - we define what AI is allowed to draft, what a human must sign off, and where we keep AI out entirely. That boundary is what keeps this from becoming an unreviewed AI-slop suite.
How It Fits
AI-assisted generation works best on top of a solid foundation. If your framework needs shape first, start with test automation framework engineering, then let AI accelerate coverage on those clean patterns. And since generation ramps volume fast, our CI/CD test infrastructure work keeps the growing suite fast and reliable to run.
The Honest Pitch
This isn’t about replacing engineers - it’s about making good ones faster. More coverage, sooner, hardened by people who know what a real test looks like.
Engagement Phases
Fit Assessment & Guardrails
We look at your codebase and existing suite and identify where AI genuinely helps - generating first-draft tests for untested code, proposing edge cases, healing brittle selectors, triaging failures. Just as important, we set the guardrails: what AI drafts, what humans must review, and where we deliberately keep it out.
AI-Assisted Generation & Hardening
We use LLMs to generate test drafts and edge cases at speed, then our senior SDETs review, correct, and harden every one - killing shallow assertions, adding meaningful checks, and fixing the subtle wrongness AI produces. We wire in self-healing selectors and AI-assisted triage where they earn their place.
Workflow Integration & Handoff
We fold the AI-assisted workflow into how your team already works - generation prompts, review checklists, and triage helpers - so your engineers get the speed-up without inheriting an unreviewed AI-slop suite. Everything is documented so the practice continues after we leave.
Deliverables
Before & After
| Metric | Before | After |
|---|---|---|
| Coverage Speed | Months to hand-write tests for the untested backlog | First drafts in days, hardened by engineers before merge |
| Test Quality | AI-generated tests that pass no matter what and catch nothing | Every test reviewed and hardened to make real assertions |
| Maintenance Load | Half a day a week fixing selectors and triaging flakes by hand | Self-healing selectors and AI-assisted triage cut the grind |
Tools We Use
Frequently Asked Questions
Isn't AI-generated testing just AI slop?
It is if you ship the raw output, which is exactly what we don't do. AI is great at speed - drafting tests, proposing edge cases, healing selectors - and bad at judgment. It happily writes assertions that pass no matter what. So every generated test is reviewed and hardened by a senior SDET before it lands. AI writes the first draft; an engineer ships the test.
How much does AI-Augmented Test Generation cost?
Book a free call to discuss scope and get a custom quote.
What are self-healing selectors, really?
They're locators that can recover when the UI changes in small ways - matching on several attributes and adapting when one shifts, instead of hard-failing on a single brittle CSS path. They cut the routine locator maintenance that eats a chunk of every week. They're not magic and won't cover a genuine redesign, and we're honest about where the line is.
Will this replace our SDETs?
No, and we'd be suspicious of anyone selling that. AI makes good engineers faster - more coverage sooner, less maintenance grind - but the judgment about what to test, what a failure means, and whether an assertion is meaningful stays human. This service multiplies your engineers, it doesn't replace them.
Test automation, engineered.
Book a free 30-minute call. We assess your test automation gaps and show you how a modern SDET practice ships faster with fewer escapes.
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