Peter Wu

Want a preview of what I'm going to be talking about in my keynote for RubyConf? You can catch a glimpse of it here!

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🍜Anybody up for some ramen? I am excited to share that I am back in the garage, building again (it’s actually a house in the Berkeley Hills). We are taking the wraps off of Supercog AI, a new startup focused on solving Application Integration using LLM powered agents. My co-founder in this new venture is a great friend of mine (and a former co-founder partner), Alex Osborne. Alex and I have worked around the application integration space for a long time, and we are unrealistically excited about applying the GenAI stack to this problem. Not many people relish the task to get some bits to move from system A to system B. But it’s a critical job to be done, and that’s led to a lot of brittle scripts, a myriad of inflexible “no code” tools, and a lot of hand crafted SQL. But the power of the Large Language Model, trained on a huge corpus of information, offers a remarkable tool to solve this problem. The LLM you use today already knows the APIs of hundreds of popular systems. It knows the SQL dialects of every major database. It understands the semantics and data schemas of many popular SaaS systems. It understands much of the specific domain in which your business operates. I like to call the AI revolution “the last platform shift”. That may turn out to be hyperbole, but I definitely believe we are in the very early stages of seeing what this new stack can enable. I know we are hardly the first folks to claim that “amazing stuff is coming!”. But this is why Alex and I have decided to focus on a real and hard problem. If we can prove that LLMs can power a new way to solve this problem, it will be the first successful *new* approach in 15 years.. We will have much more to share about this new platform soon. In the meantime, if you’re interested in getting a peek - or even better if you have application or data integration tasks that you would like some help with - please reach out because we want to help. #genai #startups #backinthegarage

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The newest issue of The Pragmatic Engineer found a surprise uptick in eng hiring in the typically slow summer season - I'm curious to see how the macro environment impacts this uptick as we head into the fall, but I remain hopeful. I asked Gemini to give me the tldr of the article to share with my team (sorry, Gergely Orosz) and found it missed one of the most interesting pieces of the article. Gemini's highlights - Unexpected surge: Tech recruitment has seen an unusual spike in June and July, contrary to typical trends. Increased demand: Startups, especially AI-focused ones, are driving the hiring uptick. Global phenomenon: This trend isn't just limited to the US; Europe is also experiencing increased recruitment activity. Reasons for hiring: Companies are backfilling positions, investing in growth due to improved financials, and responding to increased VC funding. Challenges remain: While the job market is improving, finding qualified candidates and offering competitive compensation remains difficult for many companies. What I found most interesting - The nature of the backfills: the article finds that a lot of new headcount are actually backfills of folks that were "over-slashed" during rounds of layoffs. Not entirely surprising with the "trim the fat" and "rebuild lean" mentality, but interesting nonetheless. Either way, the uptick is encouraging (and don't always rely on Gemini's tldrs). #hiring #startups #VCbacked #softwareengineering

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Since the YC deadline to hear back for W25 is coming up next week, here’s the story of how we went from 2 students coding in an MIT dorm room to being full-time YC founders building Delve in SF. For all you founders anxiously waiting to hear back, just keep building — you’ll be successful regardless of the decision. -- In Fall 2023, my co-founder Karun Kaushik and I were studying AI at MIT and spending all of our free time building an AI medical scribe to help doctors. We had vaguely heard about YC from a friend who had just gotten accepted but had no plans of applying whatsoever. However when the YC deadline rolled around, we spontaneously decided to put in an application on the very last day. We spent that whole day in Karun’s dorm room typing up the application and filming all the required videos. We finally hit submit the minute of the deadline! By the next day we had already moved on. We went back to the usual rhythm of coding in the dorm room, calling with doctors, attending conferences, etc. If anything, we were even more motivated now to get more traction and be successful regardless. Later that week, while we were eating in the dorm kitchen, I noticed I got an email saying we had a YC interview scheduled. My heart rate spiked. I jumped up out of my seat and immediately told Karun. I never seriously considered YC, but for the first time it hit me that it might actually be a possibility. When the day of the interview rolled around, we did mock interviews with former YC founders and focused mostly on calming our nerves. More important than the actual content of the interview, we wanted to show our excitement for building and hacking together as co-founders. Unfortunately the interview caught us by surprise. The group partners didn't seem to care as much about our actual AI medical scribe. Instead, they seemed more curious about a side idea we had listed in our application that we wrote up in a day. The idea was about streamlining HIPAA compliance (since we had to go through HIPAA for our AI medical scribe). By this point, we were already seriously considering pivoting into this and had made a lot of progress on the idea. The YC interview was our tipping point Not too long after, we got an ominous email titled “YC.” We were freaked out. I could not sleep the entire night. Then, in the middle of class the next day, I got a phone call from Karun with Surbhi on the other end of the line. My heart rate spiked. I ran outside of the classroom. That turned out to be our acceptance call:) -- For everyone out there still waiting to hear back, just keep grinding. Build as if you’ve been rejected and you might just be pleasantly surprised. I’m also always here to help with mock interviews/give advice! We’ve helped a handful of friends through the YC app process and are always here to support other founders!

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🎉 Big congratulations to our incredible team (Haoyu Chen, Nick Greenquist,Yuxing Wang, Sridevi Maharaj, Ruiyang Wu and many more) for delivering several quarters-long impactful features on the Play Store! 🚀 We’re thrilled to have launched key updates like Search Home, Sports Moment, and WearOS recommendations, all designed to enhance personalization and help billions of users worldwide search and discover content they love. 🌍✨ Check out the Play Store Q3 updates: https://lnkd.in/dn5wx8Mi #GooglePlay #Personalization #Recommendation

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𝗡𝗲𝘁𝗳𝗹𝗶𝘅’𝘀 𝗟𝗮𝘁𝗲𝘀𝘁 𝗘𝗮𝗿𝗻𝗶𝗻𝗴𝘀: 𝗔 𝗠𝗮𝘀𝘁𝗲𝗿𝗰𝗹𝗮𝘀𝘀 𝗶𝗻 𝗦𝗰𝗮𝗹𝗶𝗻𝗴 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗣𝗿𝗼𝗳𝗶𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 Netflix stock is soaring over 11% after its latest earnings report. The company exceeded expectations with EPS of $5.40 (vs. $5.12) and revenue of $9.83 billion (vs. $9.77 billion). Looking ahead, Netflix projects 15% revenue growth and a six-point improvement in operating margins. By 2025, they expect revenue to hit $43-44 billion—$4-5 billion more than 2024. Here are 𝟯 𝗸𝗲𝘆 𝗹𝗲𝘀𝘀𝗼𝗻𝘀 we can all learn from Netflix’s approach: 1. 𝗙𝗶𝘅𝗲𝗱 𝗖𝗼𝗻𝘁𝗲𝗻𝘁, 𝗘𝘅𝗽𝗮𝗻𝗱𝗶𝗻𝗴 𝗔𝘂𝗱𝗶𝗲𝗻𝗰𝗲 Netflix spreads its fixed content costs over a growing audience, with 14% subscriber growth and increasing engagement. Whether it's hit series or sports offerings like NFL games, their content model scales profitably with each new viewer. 2. 𝗚𝗶𝘃𝗶𝗻𝗴 𝗔𝘄𝗮𝘆 𝗩𝗮𝗹𝘂𝗲 𝘁𝗼 𝗚𝗿𝗼𝘄 Netflix’s strategic moves, like offering free sports events, and a lower priced ad tier prove that giving value leads to growth. As Co-CEO Ted Sarandos stated in the Q3 earnings call, “Engagement drives retention and acquisition, which in turn places more value on a Netflix subscription”​. This strategy keeps users engaged and drives new signups. 3. 𝗡𝗼 𝗡𝗲𝗲𝗱 𝘁𝗼 𝗕𝘂𝗻𝗱𝗹𝗲—𝗧𝗵𝗲𝘆 𝗔𝗿𝗲 𝘁𝗵𝗲 𝗕𝘂𝗻𝗱𝗹𝗲 Unlike other platforms, Netflix doesn’t rely on traditional bundles. With a wide range of content, including live sports, they are the ultimate bundle, growing through value-driven engagement without complex packaging. While other companies raise prices or experiment with aggressive strategies, Netflix shows that 𝗳𝗼𝗰𝘂𝘀𝗲𝗱 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗶𝗻𝗴 𝘃𝗮𝗹𝘂𝗲 lead to sustainable growth. Full transcripts: https://lnkd.in/g3mEDWcH #Strategy #BusinessGrowth

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Want to tease something my team has been working on over at Buffer! The attached image isn't a mockup, but a screenshot of a live prototype of RSS feeds directly in Buffer! It's only available internally and still pretty rough at this point, but we'll have it available for user testing soon. With this enhancement, we hope to help Buffer users easily find new and engaging content to share with their audiences. What do you think? Will RSS feeds in Buffer help you create more content?

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My cofounder Saumil goes on the Stack Overflow Podcast to deep dive on AI Agents! He goes into detail how we leverage AI agents to power automated workflows to accomplish the most complex tasks. Including agents firing off tasks to other agents to tackle the details. Need an agent to verify your work? No problem. Give it a listen and let us know what you think!

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It’s eye-opening to see how AI model businesses are dealing with tight margins despite big investments. 🤯 Aidan Gomez’s comments about the “zero margin business” highlight the fierce competition and price cuts in the industry. 💸 With giants like OpenAI and Anthropic lowering prices to stay ahead, it’s a tough time for startups. The future of AI might depend on finding new ways to make these technologies profitable. 🚀 #AI #MachineLearning #TechTrends #Startups https://lnkd.in/ejkDu_wT

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Come join us tomorrow in SF to learn more about the latest updates to run AI workloads on Google Cloud!

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My journey at Meta was nothing short of transformative: 1. Mastering Scale: I delved deep into creating systems designed not just for the present but engineered to handle exponential growth. This focus on scalability has been a cornerstone of my technical philosophy. 2. Cross-Functional Synergy: I thrived in environments where tech, product, and strategy intersected, learning the critical importance of empathy in understanding user needs and aligning them with business goals. 3. Leadership and Legacy: Leading initiatives and mentoring peers, I've embraced leadership that fosters growth, innovation, and a culture of continuous learning. To my colleagues at Meta, your expertise, camaraderie, and innovative spirit have been invaluable. Thank you for the incredible journey and for pushing me to excel. As I move forward, I carry with me the lessons learned and the ambition to continue innovating in technology, leading with empathy, and solving complex problems. Excited for what lies ahead and eager to contribute to the tech community in new and meaningful ways.

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~40% of Frec’s customers are engineers working in tech, many of whom expect frequent and large capital gains. They also prefer to self-manage their money, which makes Frec an ideal platform. Meet Evan: an engineering leader who upgraded from investing in ETFs to direct indexing. Direct indexing appealed to Evan because it offers comparable returns to his ETFs while saving him money on advisory and ETF fees. “ETFs are true and tested, and giving folks a different way of investing in the market while saving more money is really appealing.” He’s used many other robo-advisors and other fintech tools, but “Frec seems to maximize tax loss harvesting opportunities better than any other product that I’ve used.” He also likes Frec's transparent fee structure.  “I feel like with a lot of other companies, that’s muddled in with the cost of investments,” he told us, “and you don’t really know how much you’re paying or how much you’re not saving as a result. I think Frec does a really good job of laying all of that out and giving you a true understanding of the cost of these investment products.” Read more about his Frec journey here ⬇

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ModernBERT is an open-source embedding model which represents a significant leap in encoder-only transformer architecture merging: > Long context (8k tokens) > Local-global attention for efficiency > Up-to-date code and text training data (2 trillion tokens) > FlashAttention & Unpadding to push performance on consumer and server GPUs > High retrieval and classification accuracy that sets new benchmarks across GLUE, BEIR, code tasks, and more. Learn more about this exciting new embedding model here: https://lnkd.in/en5ud9VE

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I am excited to share the latest blog, co-authored by myself, Junhwi Kim and Vyas Sekar, detailing how we managed to successfully localized and improved LLM by combining Fine-Tuning and RAG. https://lnkd.in/gKDkgGPq

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Hey everyone, I am an investor and advisor to Katanemo.... They are reinventing the infrastructure primitives for GenAI and launched Arch - https://lnkd.in/gCrbbkEV - an intelligent prompt gateway. Give the project a look on Github, and star the project if it resonates

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