Anam Hira's banner

Anam Hira

@anamhira • 2,018 subscribers

@tryrevyl - proactive reliability | prev uber ai 🏎️

Shorts

At Uber, design source of truth was a big problem for design and engineering teams. No one knew what the app truly looked like. So every week, a group of designers would sit in a meeting room and check that engineers had correctly implemented the Figma designs. Now coding agents have increased the throughput of changes by an order of magnitude. Keeping up manually has become impossible. Here we used the Revyl to map every state in Ubert (demo uber), navigating our mobile use agent on a cloud iOS simulator. This would have taken a team of designers tens of hours to recreate by hand. We did it in under an hour, asynchronously, with a simple prompt. Let your team see what your users actually see. Empower coding agents to ship a delightful experience with no blindspots. Get started with our free trial and create a map for your own app.

At Uber, design source of truth was a big problem for design and engineering teams. No one knew what the app truly looked like. So every week, a group of designers would sit in a meeting room and check that engineers had correctly implemented the Figma designs. Now coding agents have increased the throughput of changes by an order of magnitude. Keeping up manually has become impossible. Here we used the Revyl to map every state in Ubert (demo uber), navigating our mobile use agent on a cloud iOS simulator. This would have taken a team of designers tens of hours to recreate by hand. We did it in under an hour, asynchronously, with a simple prompt. Let your team see what your users actually see. Empower coding agents to ship a delightful experience with no blindspots. Get started with our free trial and create a map for your own app.

204,156 görüntüleme

At Uber a big problem for design teams and engineering teams was design source of truth. No one knew what the app truly looked like, so weekly a bunch of designers would get into a meeting room and check that the engineers correctly implemented the figma designs that they made Now with coding agents throughput of changes has increased an order of magnitude and it has become impossible to manually keep up. Here we used the Revyl CLI to create a flow of every state in the Uber design, by navigating our mobile use agent on an cloud iOS simulator. This is something that would have taken a team of designers tens of hours to recreate manually; All done in less than an hour asynchronously with a simple prompt. Enable your team to know what your users are actually seeing and empower coding agents to give your users a delightful experience without any blindspots Get started with our new free trial and create a map for your own app 🗺️

At Uber a big problem for design teams and engineering teams was design source of truth. No one knew what the app truly looked like, so weekly a bunch of designers would get into a meeting room and check that the engineers correctly implemented the figma designs that they made Now with coding agents throughput of changes has increased an order of magnitude and it has become impossible to manually keep up. Here we used the Revyl CLI to create a flow of every state in the Uber design, by navigating our mobile use agent on an cloud iOS simulator. This is something that would have taken a team of designers tens of hours to recreate manually; All done in less than an hour asynchronously with a simple prompt. Enable your team to know what your users are actually seeing and empower coding agents to give your users a delightful experience without any blindspots Get started with our new free trial and create a map for your own app 🗺️

96,508 görüntüleme

At Uber, our testing agent hit an outage in Australia that I still think about. We had the recording. That's about it. No network trace for the run. No logs mapped to each step. No perf data. Just a video of an agent pressing a button and a team trying to reconstruct what happened underneath. We eventually traced it to a transient issue. But "eventually" is the problem. If the run had shipped with real instrumentation, the why would have taken one look, not an investigation. So when we built Revyl, that was non-negotiable. Every run comes with: > network waterfall, every request and response > device logs timestamped against each step > CPU, memory, and FPS traces for the full run The agent finds the problem. The report explains it.

At Uber, our testing agent hit an outage in Australia that I still think about. We had the recording. That's about it. No network trace for the run. No logs mapped to each step. No perf data. Just a video of an agent pressing a button and a team trying to reconstruct what happened underneath. We eventually traced it to a transient issue. But "eventually" is the problem. If the run had shipped with real instrumentation, the why would have taken one look, not an investigation. So when we built Revyl, that was non-negotiable. Every run comes with: > network waterfall, every request and response > device logs timestamped against each step > CPU, memory, and FPS traces for the full run The agent finds the problem. The report explains it.

42,149 görüntüleme

nobody at your company knows what your app actually looks like. designers ship figma. engineers ship code. PM ships a roadmap. none of them match. we built atlas to fix this. point it at any iOS app, get back a complete map of every screen and every path through it. this is doordash.

nobody at your company knows what your app actually looks like. designers ship figma. engineers ship code. PM ships a roadmap. none of them match. we built atlas to fix this. point it at any iOS app, get back a complete map of every screen and every path through it. this is doordash.

57,771 görüntüleme

you've never actually seen your own app. you've seen one build. in english. logged in as you. on your phone. at Uber, that was the whole problem. no one knew what the app actually looked like. every week a room of designers would sit down and check, screen by screen, that the build matched the figma. and that was one language. the app shipped in 50+, across thousands of a/b tests, on hundreds of devices. thousands of versions of the same app, and nobody had seen most of them. we built atlas to map what users actually see.

you've never actually seen your own app. you've seen one build. in english. logged in as you. on your phone. at Uber, that was the whole problem. no one knew what the app actually looked like. every week a room of designers would sit down and check, screen by screen, that the build matched the figma. and that was one language. the app shipped in 50+, across thousands of a/b tests, on hundreds of devices. thousands of versions of the same app, and nobody had seen most of them. we built atlas to map what users actually see.

26,814 görüntüleme

we built mobbin, but for your own app every screen, every flow, mapped automatically.

we built mobbin, but for your own app every screen, every flow, mapped automatically.

20,599 görüntüleme

Videos

Anya Rossi

sweetdream.ai

SweetDream.ai•Sponsored•Livecam

Watch Anya Live

Anya is streaming live right now! Join her private show and enjoy exclusive content.

Exclusive private shows

1.2k viewers online

Private Show

Join now for exclusive access

Free preview available • Premium content

At Uber, one bug reaching production could cost millions in a single day. So quality was solved with headcount. Rooms of people would manually tap through the app before every release. Request a ride, add a card, cancel a trip, in 50+ languages, release after release. Now coding agents have increased the throughput of changes by an order of magnitude. A room of people can't keep up anymore. Nobody can. Here we used Revyl to run those same flows on Ubert (demo uber), sending our mobile use agent through the app on a cloud iOS device. Every step verified, with CPU, network, and state traces attached when something breaks. What took a room of testers hours per release runs in 16 minutes, asynchronously. Get started with our free trial and put an agent on your own app.

At Uber, one bug reaching production could cost millions in a single day. So quality was solved with headcount. Rooms of people would manually tap through the app before every release. Request a ride, add a card, cancel a trip, in 50+ languages, release after release. Now coding agents have increased the throughput of changes by an order of magnitude. A room of people can't keep up anymore. Nobody can. Here we used Revyl to run those same flows on Ubert (demo uber), sending our mobile use agent through the app on a cloud iOS device. Every step verified, with CPU, network, and state traces attached when something breaks. What took a room of testers hours per release runs in 16 minutes, asynchronously. Get started with our free trial and put an agent on your own app.

377,735 görüntüleme • 2 ay önce

Uber had entire floors of people doing manual testing and manually clicking through the app, checking whether the app worked. It still wasn't enough, and it was too expensive They used deterministic script frameworks like Appium and XCUITest, but engineers ended up spending 50% of their time just maintaining test cases because of their brittle nature. This is a clip from a conversation with one of my DragonCrawl teammates and the overall goat, Juan Lopez Marcano, discussing the problems Uber faced at scale with end to end mobile testing.

Uber had entire floors of people doing manual testing and manually clicking through the app, checking whether the app worked. It still wasn't enough, and it was too expensive They used deterministic script frameworks like Appium and XCUITest, but engineers ended up spending 50% of their time just maintaining test cases because of their brittle nature. This is a clip from a conversation with one of my DragonCrawl teammates and the overall goat, Juan Lopez Marcano, discussing the problems Uber faced at scale with end to end mobile testing.

243,582 görüntüleme • 10 ay önce

We mapped every flow in the Uber App Design source of truth Made with the Revyl CLI

We mapped every flow in the Uber App Design source of truth Made with the Revyl CLI

68,018 görüntüleme • 4 ay önce

Grok Build is able to write code, deploy to a phone on revyl, and look at the screen to check its own work. no human in the loop. watching it edit, hot-reload, and screenshot to verify in real time is genuinely wild.

Grok Build is able to write code, deploy to a phone on revyl, and look at the screen to check its own work. no human in the loop. watching it edit, hot-reload, and screenshot to verify in real time is genuinely wild.

10,683 görüntüleme • 3 ay önce

Daha fazla içerik yok.