Andy Fang @andyfang

about 3 years ago, micro1 lost 60% of its revenue overnight and almost went bankrupt. today, i'm proud to share we've surpassed $1B annual run rate while remaining historically profitable. it’s been a special journey. we’re grateful for every struggle, moment, and person who has been part of it. we've taken a very untraditional path to get here. our core team is only ~180 people, spanning 14+ countries, and fully remote. many of our decisions sacrifice hundreds of millions of revenue and slow us down short term. but we believe they compound into advantages that are impossible to replicate long term. the long term is now. these are the 8 principles that made micro1 a leader in the data industry and will soon make us number one: 1.) human 1st AI: treat the tens of thousands of experts helping train models with absolute best-in-class care. our goal is to make AI training one of the largest, highest paying, and most enjoyable job sectors in the world. 2.) U.S. first: we refuse to work with adversarial nations, or export data that improves models against the interests of Americans. 3.) long-term research over short-term ARR: invest in deep research, products, and infrastructure for years from now, not just the next customer pipeline. 4.) proper incentives for intensely hard work: no arbitrary requirements like 996. inspire people to work extremely hard with outlier incentive structures instead of forcing weekend work. we’ve maintained close to 100% core team retention as a result. 5.) stay lean and global: we’ve reached $1B run rate with ~180 people, and intend to slow team growth significantly from here. exceptional talent is found around the world, and pedigree is the wrong thing to over-index on. 6.) execution alignment: company to retain a streamlined board so we can optimize for the next several decades, remain light-weight and dynamic, and take bold & calculated risks. 7.) abundant intelligence improvement: invest in building data generation models to make high-quality datasets and RL environments dramatically less expensive and more abundant. 8.) scale data on realism and horizon: realism brings the complexity of the real world into training models, while horizon extends how long models can work and how much complexity they can handle. both have enormous room to scale, and we’re pushing the limits of both. additionally: after surpassing $500M run rate this summer, we priced our Series B at a $4B valuation, alongside a ~$25M tender to give our early employees liquidity as we build for the long term. the round was led by Dream Ventures, a longtime supporter and one of our earliest investors, alongside Microsoft, Javelin, Flybridge, G Squared, Up Partners, and LG. we’re also grateful to be backed by incredible industry leaders, including Guodong Zhang (co-founder of xAI), Andy Fang (CTO of DoorDash), Igor Babuschkin (co-founder of xAI), Behnam Neyshabur (founder of Mirendil), Jerry Tworek (ex-VP of Research at OpenAI), and many more. data is on its way to becoming the largest industry humanity has ever seen, and we're certain this is just the beginning. best, Ali

You can now just text DoorDash and let it order for you. It’s proactive, learns from your repeat orders, and helps you find the best deals and new spots. Just tell it what you want without any extra setup. Ask it to reorder your usual, or add it to a group text to collect everyone’s orders. You can even send a photo of your fridge and it’ll tell you what ingredients you’re missing for a recipe you want to make and deliver the ingredients to your doorstep. We believe agents are a new app paradigm and are building for that future at @AIatDoorDash, with a lot more to come. This feature is in beta in the US, would love for you to let us know what you think! Waitlist: doordash.com/text

We've seen a lot of enthusiasm around the DoorDash CLI, and people have been asking for it to work across their teams. Today, we're introducing the DoorDash MCP for corporate ordering, so your team’s agents can place group orders, restock the office, schedule team lunches, track deliveries, and more. We’re proud that @spacexai, @vercel, @cognition, @Tempo, and @mercor are some of our early adopters already using the DoorDash MCP so employees can order agentically. A few great use cases we’ve seen so far: agents automatically restocking office supplies and snacks based on inventory signals, and Slackbots to collect the team’s lunch requests and handle placing the order. And we’re opening availability of our dd-cli to more developers in the US and Canada on macOS and Linux. Show us what you build and check out some really cool ways folks are using the CLI! Get access to the MCP or CLI here: developer.doordash.com/mcp

something big is coming tomorrow 👀

Fear the Tree! 🌲🌲🌲

Stanford Women’s Tennis @StanfordWTennis

3 weeks ago

The next chapter: delivered. @GoStanford x @DoorDash

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I’ll always be proud of being a Harker alum. High density of nerds, they had the foresight to offer a neural nets class back in 2009 that now I’m very glad I took Go eagles!!! 🦅

Sheel Mohnot @pitdesi

4 weeks ago

Bay area schools with the most National Merit Semifinalists & the share of senior class that qualified. South Bay is absolutely dominant, there are many schools where >10% of the class qualified

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One of many lives deliveries happening autonomously with DoorDash Dot today. After the food’s placed, Dot makes sure nothing’s missing (this part can be faster). Then off to the races! 🏁 Dot is rapidly improving through these live orders happening everyday.

Coding agents struggled to navigate the messiness of DoorDash’s data, so we built our own internal data agent: Vera. Business leaders now can self-sufficiently make critical decisions and answer WBR questions with Vera, which previously would’ve required hours of analyst work. Analysts now oversee our semantic data layer and maintain the eval set. Anyone across DoorDash can now ask Vera and get reliable answers to their business questions. Great work by the team on this one!

DoorDash AI Research @AIatDoorDash

a month ago

We built Vera, an internal data agent that gives teams across DoorDash reliable answers to business questions from our data. Frontier models inside general-purpose harnesses like Codex and Claude Code often struggle with the sprawl of enterprise data. Our own harness, with

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@ianwong_ Congrats Ian on the launch! 🚀

i'm sad to announce that our recent fundraising round did not go according to plan... we initially planned to raise $18m. we didn't end up getting that number. we ended up raising a $40m series a instead. co-led by @MarathonMP and @chemistry, with participation from @Wing_VC, @AMD Ventures, @outsetcap, @fiftyyears, and @ycombinator, and our existing investors doubling down on @wafer_ai. we are also joined by an incredible list of angels, including @JeffDean (CEO, @DiscoLoopAI), @rauchg (CEO, @vercel), @andyfang (CTO, @DoorDash), @kvogt (CEO, Bot), @akothari (COO, @NotionHQ), @eastdakota (CEO, @Cloudflare), @deepgramscott (CEO, @DeepgramAI), and more. back to the kernel mines

@LukeYoungblood Interesting, will take a look

Cloud-based agents are what most engineering orgs want but few are comfortable turning on for security reasons. Our internal platform Flux is how we addressed this at DoorDash. Every Flux background agent runs in an isolated sandbox with scoped, audited access, which gives us confidence to run them across our systems: code review, bug triage, incident response, and long-running coding agents from your phone. It now handles 130k agentic tasks a month. Credit to the @AIatDoorDash team for getting Flux to this scale.

DoorDash AI Research @AIatDoorDash

2 months ago

Today we’re proud to announce Flux, our own cloud platform for running agents across DoorDash. Flux automated 130k engineering tasks in one month and now powers 25k+ code reviews each week. Creating the platform ourselves moved us beyond local, laptop-based agent workloads,

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As I've said before, @t_xu is the best person in the world to run DoorDash, world-class CEO. Glad everyone now gets to hear how he thinks...

Gokul Rajaram @gokulr

3 months ago

EVERYTHING IS AN EDGE CASE @t_xu (Tony Xu), Co-Founder & CEO, @DoorDash, interviewed by @jaltma (Jack Altman) (Uncapped) (PS: This was a special episode for me to transcribe because I worked closely with/for Tony at DoorDash, and this episode perfectly brings out the values -

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@stanleytang LFG 🚀

DoorDash Air is here. Officially certified drone operator in the US. Delivering real orders, not demos "People come here because they want to solve real problems and see their work show up in the real world within days, not stuck in R&D hell watching a demo that never leaves the lab." If you're interested, apply here: careersatdoordash.com/career-areas/d…

Stanley Tang @stanleytang

3 months ago

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@DoorDash is proud to join the Open Secure AI Alliance to advance AI Security. It’s critically important for defenders like ourselves to be able to develop and deploy the strongest cybersecurity tools. Open, auditable tools, and models that invite broad participation and scrutiny is an essential part of that process.

NVIDIA @nvidia

3 months ago

AI security advances when the industry builds in the open, together. We're introducing the Open Secure AI Alliance with industry leaders to develop new techniques and tools to safeguard software and agents. By sharing models, tooling and research in the open, we can broaden the

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We’re proud to have @DoorDash be an updated signatory of this letter. We fully support America being the world’s AI leader. Open weight models are crucial to that future Thank you Jensen and Satya for your leadership here. We stand behind you 🇺🇸

Jensen Huang @JensenHuang

3 months ago

For my first post, I’m sharing a letter @nvidia signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.

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For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models. images.nvidia.com/pdf/Open-Weigh…

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It was fun being on the @NoPriorsPod yesterday with @saranormous chatting through DoorDash's AI and autonomy ambitions! Here's @stanleytang talking about getting started building DoorDash Dot, our L4 autonomous delivery robot, back in 2018.

@patloeber For 3.5 flash lite, seeing 80% cost reduction, 13% latency reduction at comparable quality vs. 3.5 Flash. Good stuff Glad you guys care about good intelligence at low costs/latencies