57 points wuweiweiwu 1 hour ago 40 comments
Here’s a demo: https://youtu.be/BFsM-Se1Fh8
We’re both software engineers that spent our careers on dev tooling and infra across companies like Robinhood, Retool, WeWork, and Qualtrics. Testing was always a pain in the ass (esp Playwright and Selenium), so we built agents to do it for us.
Modern day software has a ton of bugs and the change failure rate is only growing faster as coding agent adoption scales. LLMs are really good at generating code, but reinforce their own assumptions, write a ton of useless tests, and are bad at visual understanding. On DeepSWE v1.1, Sonnet 5.5 hit 66.2% pass rate when banned from writing tests, versus 65.3% when allowed.
OSS end-to-end testing frameworks like Playwright, Selenium, or Maestro force you to hardcode implementation details like XPath, text, or aria-* attributes in your tests. Even with agents, these take a nontrivial amount of time and tokens to build and maintain.
In 2023, we saw Nat Friedman drive a browser with GPT-3 via natbot. We were inspired to use this technology to automate the most painful and tedious parts of software engineering: testing. We started with using LLMs to generate and maintain Playwright, but quickly realized that those primitives were fundamentally misaligned with the agentic SDLC. We think the future of QA is agents testing themselves, not writing scripts.
Mo is a custom agent harness for catching bugs that builds on the past 3 years of Momentic and millions of test traces from complex, real-world applications. Mo is built for recall: it finds the most real bugs, though Codex is a bit more precise at 86% vs 84%. The tradeoff is cost: Mo costs $2.67 per bug vs $0.80 for Codex, less than Claude Code and Devin.
- Self-organizing agent graph. Mo builds a directed acyclic graph (DAG) as it explores. Large product areas automatically fork into parallel sub-agents, each with their own browser or device for concurrent execution.
- Specialized agents for domain specific tasks. Planner agents reason over screenshots and video while dedicated locator agents inspect page structure to resolve plain-English interaction targets. Others include image analysis, video understanding, audio generation, and more.
- Parallel agents coordinate through cooperative resource leases. Agents can announce that they’re “using” or “modifying” overlapping resources or fixtures. Multiple “using” claims can coexist, but only a single “modifying” claim can be active on any particular one.
- Scaled infrastructure. Mo ships with a tunnel that lets users expose private sites and local apps to our hosted agents and infra. A single bug bash can spin up 100s of concurrent browsers and devices.
We benchmarked Mo against coding agents on 4 popular open-source apps: Gitea (58.8k stars), Metabase, Twenty (YC), and Saleor, with 1,396 human-labeled bugs. Each agent got the same brief, a fresh E2B sandbox, and no access to source code. Codex and Claude Code used hosted Browserbase browsers, while Devin used its built-in browser. For evaluators, we implemented LLM as a judge (GPT-6.1 Sol) with a human reviewer.
Results from a time-boxed 60-minute run:
- Mo: 269 bugs, 19.3% recall, 84% precision, $2.67 per bug
- Codex (GPT-6.1 Sol + Playwright MCP): 86 bugs, 6.2% recall, 86% precision, $0.80 per bug
- Claude Code (Opus 5.5 + Playwright MCP): 59 bugs, 4.2% recall, 80% precision, $4.09 per bug
- Devin: 27 bugs, 1.9% recall, 84% precision, $3.89 per bug
Mo finds more bugs the more time it has. From 30 to 60 minutes, it went from 177 to 269 bugs (+52%), while Codex gained only 16%.
Results: https://momentic.ai/qa-bench
Write-up: https://momentic.ai/blog/qa-bench
Dataset: https://huggingface.co/datasets/momentic/qa-bench
Harness: https://github.com/momentic-ai/qa-bench
We just shipped PR testing for Vercel and Cloudflare deploy previews and we’re giving every new signup $250 in Mo spend. Paid plans have higher infra capacity and included usage along with options to top up.
We’d love for you to try it out and give us feedback. Feel free to comment here, we’ll be around all day!
aliasxneo 1 hour ago | parent
To be more constructive: let's say I have 2 frontier subscriptions and I end up with 20% left on each at the end of the week. It feels awful knowing that I would _love_ to use that with Momentic but I can't because I have to pay for yet another set of proprietary non-transferable tokens. It's like dealing with airline rewards.
amunozo 1 hour ago | parent
aliasxneo 1 hour ago | parent
freedomben 1 hour ago | parent
nkozyra 1 hour ago | parent
aduwah 1 hour ago | parent
jeffan 1 hour ago | parent
That doesn't mean we won't eventually support byok, especially as OSS models catch up! We have our finger on the trigger there.
kart23 1 hour ago | parent
MGabrielDenton 13 minutes ago | parent
bortimus 1 hour ago | parent
Aboutplants 1 hour ago | parent
0xy 1 hour ago | parent
Fordec 13 minutes ago | parent
This strikes me as a company that is late delivering a product for November 2025, when it is November 2026.
sercand 1 hour ago | parent
jeffan 1 hour ago | parent
1/ General purpose models are still not good at this task. I would personally love it if I could trust my agent when it says its done after a 24h build. But whether it's because of sycophancy, context degradation over time, or something else coding agents still struggle to verify their own work. Maybe with 1B context windows this will change.
2/ Infra is still annoying to setup. We wanted to provide a unified interface across web, mobile and soon desktop as well. So users don't have to worry about provisioning, concurrency, security, etc.
3/ As with any SaaS, even beyond the initial build, maintenance is a headache. I think most companies would rather not consider agentic QA as one of their core competencies and investments. It takes a ton of eng effort to keep the lights on, continually update the models used, train new ones, groom ground truth, onboard infra providers, etc.
Arkada 8 minutes ago | parent
schainks 1 hour ago | parent
momentichenry 1 hour ago | parent
staindk 1 hour ago | parent
Some questions are top of mind after having done POCs and trials with other companies that have products in this space (excuse me if they are answered somewhere obvious - I skimmed the site and your post before drafting this):
1. What is vendor lock-in like with Momentic? In my mind there's space for a mature QA platform that agentically generates and maintains playwright/similar tests, but perhaps I'm wrong.
1.b. will Momentic code or testing standard or some aspect be open enough that it is feasible to move away from it if needed, or continue using it if Momentic goes under/deploys major breaking changes?
2. How deterministic are Momentic tests?
3. Who is your target user? Product owner / developer / SDET / ?
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Also - is this saying Codex is better and cheaper than Mo?
"... though Codex is a bit more precise at 86% vs 84%. The tradeoff is cost: Mo costs $2.67 per bug vs $0.80 for Codex, less than Claude Code and Devin."
jeffan 27 minutes ago | parent
1. Mo generates its own test cases in natural language, but you can ask it to write Playwright and maintain it in your repository if you really want. We actually do have a regression testing product as well where tests are just natural language in your repository. For that product yes there is some vendor lock-in since this is a proprietary format that only our CLI translates into browser actions. But ultimately since it's natural language it's pretty portable :)
2. Mo is focused on exploratory testing and so is inherently non-deterministic. But the regression testing product has a ton of caching built into it that we've written about in the past (not just a single css selector). https://momentic.ai/blog/teaching-browser-agents-user-intent This is a big part of reliability and latency optimization, otherwise your CI would just hang for hours on any reasonable suite.
3. I would say the regression testing product was very much SDET/developer focused since it required you to have a codebase and use Git. Mo is meant to be super easy for anyone to onboard onto and lower the barrier to entry, so we're hoping we'll see more product owners, PMs, QA and even leadership use the product. But devs are always going to be our bread and butter, we ultimately tried to build the product we wanted to use ourselves.
4. We're optimized for recall (# of bugs you find in a given amount of time). The bench shows we find ~3-5X more bugs compared to Codex and Claude Code, with approx. the same precision. The service costs more than the raw harnesses for sure, but that's the all-in cost including our infra, parallel agents, etc.
JulianPaul 1 hour ago | parent
MGabrielDenton 53 minutes ago | parent
cacio-e-pepe 36 minutes ago | parent
MGabrielDenton 20 minutes ago | parent
mikert89 44 minutes ago | parent
adwn 1 hour ago | parent
jeffan 59 minutes ago | parent
adwn 19 minutes ago | parent
podoman 1 hour ago | parent
is this good? so Mo costs more money per bug? I'm confused.
luckydata 1 hour ago | parent
Smoofer 1 hour ago | parent
momentichenry 51 minutes ago | parent
The main thing we're trying to show is that Mo finds over 3x as many correct bugs in the same amount of time as the next-best QA agent. This is the main thing we optimize for since the worst thing you can do in QA is miss a real bug and ship broken code to prod. Currently, the tradeoff you make for that better recall is higher cost. I would say the precision is more or less comparable, but marginally lower.
Obviously we'd love to be beating every other agent on all of these numbers, and we're actively working on it, but for now this is an honest and transparent look at how the tool is doing.
Feel free to take a look at the full writeup for more detail!
mlcruz 19 minutes ago | parent
I also do believe search quality is recall dominated, but the link between the metrics and results are not as clear as they could have been. I think you have a stronger sell here than it looks at first glance.
Congratulations to the team tho! Those are very nice results
momentichenry 10 minutes ago | parent
adwad 53 minutes ago | parent
jeffan 49 minutes ago | parent
Everything has to be reproducible and runnable by the general public
lejohnq 26 minutes ago | parent
how does this fit in to fixing the bugs? how do we close the loop with the agents we have coding?
momentichenry 18 minutes ago | parent
sailorganymede 14 minutes ago | parent
jon128 5 minutes ago | parent
https://rescript-lang.org/