I've been reading @androidweekly since 2018. For eight years I've opened that newsletter every week to read about what other people were shipping. Seeing my own project sitting there is a wonderful feeling.
Huge thanks to @androidweekly team for the feature. If you deal with flaky mobile UI tests, give it a look, it's open source on GitHub (link in comments).
We are cooking with finalrun open source, just getting started btw.
If your ai coding agent needs to reproduce an issue reported by your teammates, just use finalrun replicate it for you.
Use:-
/finalrun-generate-test write the test case to replicate <What to replicate> and run the test
Checkout:-
https://t.co/VlD1hMPsDx
For years, Android/iOS code and UI tests lived apart — we’ve brought them together. Generate and run tests from the same codebase.
#HappySiblingsDay
Its open-source. Try it out today and share feedback.
https://t.co/GNLsqvPiak
Just open sourced Finalrun -> because your coding agent can code the feature but can't tell if it actually works on android/ios screen.
Coding agents like Claude Code and Cursor are blind to what ships on screen. They generate code, not verify what user's see.
Finalrun is a vision agent looks at your actual app screen and executes steps exactly like human.
YAML tests live in your repo. Use Claude code or cursor to generate and run these test via skill.
Checkout:- https://t.co/VlD1hMPsDx
I’m thrilled to announce we’ve raised $44M to build a new home for product design. Meet @noondesign.
No workflow is more broken and fragmented in 2026 than the product designers’. The very same people who care most about building software don’t have software purpose built for them. @kushagrasinha7 and I have lived this problem first hand as designers ourselves.
That’s why we built Noon. The first product design tool that works entirely on your product code, so you can design not only how a product looks, but also how it works. With AI at its core that works in seconds, not minutes.
For the first time, you can create, iterate, build, test and ship. All in one canvas. No translations or roundtrips to the codebase and back.
Comment “Get Noon” and we’ll get you on the list for early access.
Using AI to generate test scripts is a trap (so we open-sourced an agent instead)
With LLM generated tests, you still end up with:
❌ Brittle selectors
❌ Constant maintenance
❌ Flaky tests with Random popups
❌ Tests that don't understand product intent
Today, we are open-sourcing the FinalRun QA Agent to fix this. 👇https://t.co/6TyoUKzHFb
AI is helping dev teams ship faster than ever. Testing is the new bottleneck. the only way testing can keep up is by adopting spec-driven development and therefore 𝗦𝗽𝗲𝗰-𝗗𝗿𝗶𝘃𝗲𝗻 𝗧𝗲𝘀𝘁𝗶𝗻𝗴.
Vision-based agents can see and interact with apps like a human, which solves the brittleness of selector-based tests. But if you treat the agent like a black box, tests will still be flaky. The secret is: feed the agent a clear, contextual spec and it will return repeatable results.
We built a natural-language QA agent at Finalrun (@get_final_run) that runs mobile tests from plain English on both Android and iOS. Now the missing piece is the Spec. Better spec → better context → more deterministic outputs.
We’re open-sourcing it soon — if you want a ping at launch, sign up here:
https://t.co/Muk9LGKmtr
We keep asking for faster horses. 🐎
In testing, that means faster frameworks, faster CI, faster flaky fixes. But faster horses are still horses. They don’t solve why test automation keeps breaking.
The real leap is the motorcar, rethinking testing tools entirely. Not speed for its own sake, but shipping without test debt dragging you back.
What’s your motorcar for testing? 👇
We keep asking for faster horses. 🐎
In testing, that means faster frameworks, faster CI, faster flaky fixes.
But faster horses are still horses. They don’t solve why test automation keeps breaking.
The real leap is the motorcar, rethinking testing tools entirely.
Not speed for its own sake, but shipping without test debt dragging you back.
What’s your motorcar for testing? 👇
We keep asking for faster horses. 🐎
In testing, that means faster frameworks, faster CI, faster flaky fixes. But faster horses are still horses. They don’t solve why test automation keeps breaking.
The real leap is the motorcar, rethinking testing tools entirely. Not speed for its own sake, but shipping without test debt dragging you back.
What’s your motorcar for testing? 👇
What if your UI tests could "see" and understand dynamic app content?
Imagine a tool where your tests aren't just clicking buttons, they're intelligently processing what's on the screen.
This quick demo shows you how:
Step 1 — 𝗘𝗳𝗳𝗼𝗿𝘁𝗹𝗲𝘀𝘀 𝗗𝗮𝘁𝗮 𝗘𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻
Scan the mobile screen, pull every audio preference category, and save them as a JSON list.
Step 2 — 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗩𝗶𝘀𝘂𝗮𝗹 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻
From that list, confirm "True Crime" appears on-screen by checking the visual context for a reliable match.
If you think of the possibilities: we can pull data from an API and verify it against what’s displayed on the UI, regardless of position or how the list is rendered.
How are you tackling dynamic UIs in your testing? Share your thoughts below
Just applied to SPC Fall batch, our pitch:
AI is accelerating app development cycles, but QA is still a bottleneck. FinalRun is your AI QA agent. It tests mobile apps and constantly learns about your app, so your team can ship quality code faster.
-1 to 0
@spc@arny_laishram@get_final_run
🌐https://t.co/vYirxil1xd
Check demo here
Random popups derailing your mobile tests? 😩 We've built FinalRun AI to intelligently dismiss those blockers & keep your tests flowing seamlessly. No more flaky runs! ✨
Book a demo: https://t.co/O9AbcotewH