More from the agent competition I mentioned.
One thing I didn't expect: when we had every agent build the same prediction feature, several landed on the exact same answer (different models, no coordination).
And the highest-quality build came from one of the smaller,
Spent the last few weeks building something we are pretty excited about:
a competition where the top coding agents all build the same app under the same clock, and we verify every phase against the real, deployed result.
A early finding that surprised me: even the best ones
A professional programmer, 999 hours into building with AI, on what nobody warns you about: the gap between code that runs and code that's right.
Grateful @alpacatechyt put it this well.
We've been saying this for a while: generation isn't the hard part anymore. The graph just makes it obvious.
The gap is quality assurance. Everyone's measuring how much code AI writes. No one's checking whether every function does exactly what you intended. Nothing more, nothing less.
"As of May 2026, more than 80% of the code we merge into Anthropic’s codebase was authored by Claude."
Matches independent measures. There really is no sign this is slowing down (which doesn't mean there aren't organizational challenges to absorbing this much productivity gain)
AI tools like Claude Code and Codex made writing syntax a solved problem. The real bottleneck now is validation.
Spoke at DevSummit 2026 in Mongolia about why the future of software engineering isn't about generating code — it's about building the scaffolding to prove it actually works.
Huge thanks to @UnreadToday for capturing the event and @BELLEfounders for backing builders worldwide.
For years, software delivery was constrained by one thing:
Writing code.
Now that's changed.
AI can generate features, refactors, tests, and even entire applications in minutes.
But there's a new bottleneck emerging:
Confidence.
How do you know the code actually works?
Most teams still rely on a familiar workflow:
→ Generate code with AI
→ Run CI/CD checks
→ Review the PR
→ Merge
The issue is that passing tests doesn't necessarily mean the user experience works.
Broken flows, missing edge cases, UI regressions, and unexpected interactions often don't show up until real users hit them in production.
That's why I found @Test_Sprite interesting.
Instead of only analyzing source code, it launches your application and actively interacts with it like an end user would.
The platform coordinates multiple AI agents that explore the product, build test scenarios, execute them, and document exactly what happened.
A few capabilities that stood out:
• Autonomous application exploration
• AI-generated test plans
• Replayable execution videos
• End-to-end API visibility
• Automatic adaptation to UI changes
• GitHub workflow integration
We're entering a world where creating software is becoming increasingly automated.
The real challenge is verifying that what was created actually behaves the way users expect.
That's the gap TestSprite is tackling.
This is the thread I send people when they ask why we obsess over test quality.
The agent did exactly what agents do: optimized the metric it could see. Your hand-written version came from understanding the system, not the loop.
We think a lot about this at TestSprite, the agent's output is only as trustworthy as the tests measuring it, and most people are generating neither carefully.
"Think. Analyze. Learn." is the entire job.
I've got an agent in a loop optimizing a renderer with the goal to minimize frame times (and tests to measure). It got times down from 88ms to 2ms and allocations down from ~150K to 500. Sounds good, right? Wrong. This is exactly why agent psychosis is a big fucking problem.
As
#1 Product of the Day on @ProductHunt 🏆
May 22 — TestSprite.
To the developers testing with TestSprite every day, the teams who told us what was broken, and everyone who showed up on launch day — thank you.
You shipped this with us
We know, we know... sorry for the long wait. 🤫 But Season 03 is going to be worth it.
We’ve thrown out the old rules. Expect brand-new tools designed to push your code quality to the absolute limit.
Drop your mystery prize pool guesses below! 👇
@DesignByMaeL@ProductHunt You are completely right about the dev trust, keep an eye on our CEO @yunhaojiao since he might drop a deep-dive thread on this😉
#1 Product of the Day on @ProductHunt 🏆
May 22 — TestSprite.
To the developers testing with TestSprite every day, the teams who told us what was broken, and everyone who showed up on launch day — thank you.
You shipped this with us
TestSprite 3.0 is live. A fleet of parallel AI agents that use your app like real users — in minutes. This is the release we've been building all year.
The numbers tell the story of our completely overhauled engine:
- Accuracy jumped by nearly 40% on the hardest, most complex projects.
- Coverage increased significantly across the board for every E2E run.
- Reliability is locked in—stable and consistent across multiple runs.
We rebuilt our entire engine around these performance gains so you can ship fast and ship confident.
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