dustin

@praveenTweets @Uber are the Agents just custom code agents or you using a platform for them?

Agentic AI adoption is on fire at @Uber, and it's changing the way we build, not just in engineering, but across the entire company. Today, 99% of our engineers use AI tools. More than 70% of pull requests are attributed to local or cloud agents. And our engineers have built 2,500+ agent skills across the software development lifecycle. Those numbers are exciting, but they led us to a much bigger question: How do we bring agentic AI beyond engineering? Finance. Legal. Operations. Marketing. Customer Support. HR. Procurement. These functions run on complex workflows that are often manual, highly nuanced, and spread across dozens of systems. You can't automate them effectively by looking at process diagrams or documentation. You have to understand how the work actually gets done. So we created something called Agentic Pods. The idea is simple. We handpicked ~30 of our most AI-proficient engineers (people with deep knowledge of Uber's systems) and paired each of them with a domain expert from a business function. Then we gave every pod just two weeks. • Days 1 – 2: Shadow the expert. Observe every step. Document workflows. Ask questions. Build intuition. • Day 3: Prioritize opportunities based on scale, repetition, business impact, and data availability. • Days 4 – 5: Build a working agent alongside the person doing the job. • Days 6 – 9: Validate with several others performing the same work. Does it generalize? Does it actually make their job better? • Day 10: Ship. In just the past two months, we've run 16 Agentic Pods across 16 different business functions. • Capital allocation across 150 cities: 15 hours → 30 minutes. • Financial pacing reports: 2 days → 10 minutes. • Marketing web quality assurance: 2 weeks → 50 minutes. • Support workflow creation: 9,000 manual workflows → self-service automation. The productivity gains are impressive, but what surprised us most wasn't the speed. • It was how quickly engineers embedded in unfamiliar domains uncovered opportunities that had been hiding in plain sight. • The biggest wins rarely come from automating one task. They come from rethinking an entire workflow. Once you redesign the workflow around AI, you often eliminate handoffs, remove unnecessary approvals, replace legacy tooling, reduce vendor spend, and dramatically accelerate decision-making. • The workflow becomes the unit of automation - not the individual task. • The most impactful agent skills cut across teams, orgs, functions, tools, and systems. The biggest lesson? The best AI opportunities are rarely visible from the outside. You discover them by sitting next to the people doing the work, understanding every friction point, and building with them, not for them. We're now forming a dedicated team to scale this further and go deeper. They'll deeply understand the work, redesign it from the ground up, and use AI to fundamentally change how the business operates. It's exciting times!

@claudeai is there a trick to getting enterprise support - were having an outage and i can't find help

youtu.be/odw_uIScUZU?is… 🦃

@vulturetrades Ey

@OpenAIDevs this work well with the Desktop app?

OpenAI models and Codex, now in your AWS workflows. Build AI apps and software engineering workflows with OpenAI on Amazon Bedrock, using the AWS environments and controls your team already trusts.

@claudeai were using Cowork 3p right now and Live Artifacts don't show up. They work on Mac. Any ideas when that will be available in 3p version?

In Cowork, Claude can now build live artifacts: dashboards and trackers connected to your apps and files. Open one any time and it refreshes with current data.

With the model's simultaneous speech capability, Horace has gotten a lot easier to work with recently.

@PriyankaPhatak Will this ever be available for 3p / Bedrock users. We’re using cowork 3p now

We launched multiagent orchestration, outcomes and webhooks today in public beta and dreaming our newest feature in research preview! I’ll be posting tips on how to use these features over the next few days. If you’re at code with Claude today we have a demo booth setup for Claude managed agents as well as a workshop - stop by to learn more!

New ChatGPT image model infographic from the via score. Pretty rad. Can’t wait for this to be in the API

@JordanMorgan10 This is dope. I’ve played with it a few times. Wanted to build a collection of plays and send to my youth team. I’ll check out the app

Today I shipped one of the most challenging features I've ever worked on: a frame based play designer with an inline timeline scrubber. Powered by CADisplayLink, AVFoundation & friends. Turned out really nice!

@nsbradford @cursor_ai I just skipped right over this in the settings is what it was... thought i had to go to the side panel team settings.

@DSmith1024 @cursor_ai Dashboard > Cloud Agents > Team Settings > Pull Requests #team-pull-requests" target="_blank" rel="nofollow noopener">cursor.com/dashboard/clou…

Cursor can now attach demos and screenshots of its work to PRs it opens. Your team can review artifacts created by cloud agents directly in GitHub.

@nsbradford @cursor_ai got it thanks! i refreshed permissions on the Github App this morning. wondering if that made it show up. Either way good now.

AI Engineer Livestream from last night: youtube.com/watch?v=O_IMsE…

Today was a win for Anthropic They only leaked one company's codebase out of the millions they have

Horn won’t stop at the Iowa game lol youtu.be/0cVlTeIATBs?si…

This is awesome stuff from Ben McCollum Love when coaches break down the game like this for the fans (Via @BRSchuff 🎥)

@cursor_ai will the Marketplace plugins be available to use in Cursor CLI soon? I was hoping they would sync over.

@rodriscoll I’m feeling 2 slightly different - the engineers are moving faster but it’s not directly correlating to revenue growth. Operation cost is decreasing and old tech debt is being squashed but haven’t found viable new income streams yet.

AI has become the justification for every layoff. It's the perfect excuse card, but there is a lot of spin involved. Every layoff is some combo of the following five very different AI stories. 1. Nothing changed, we just realized we have too many people. We are going to blame AI, but we are bullshitting. This is the AI as an excuse; it was really sloppy hiring, and we are just blaming AI. (See Block) 2. Growth has gone away so now we have too many people. This may be because of AI if you are a SaaS company. All the customer love is now going to AI. But it's less AI as a productivity lift, and more about you just building a less ambitious growth company. (See Salesforce and most every SaaS company) 3. We spent our money on capex to build AI so now we can’t afford as many people. Management may say it’s about AI making us productive (4 below) but my gut is a lot of it is about Nvidia getting our money so now there is none for you. (See Meta and Oracle) 4 We are really using AI the way god intended us to. We don't need as many people. This is the ONLY version of the story that is actually about a productivity increase. It's real, it's happening, but I wonder if it is even the majority of the layoffs. (See some software engineering departments right now) @jasonlk raised a fifth reason that doesn't get talked about enough: we just have the wrong people. Maybe we don't need 20 engineers who all know C++, but rather eight who have strong AI skills. This I think should be happening everywhere. Every time a layoff announcement comes out, I try and mentally categorize per the above.