

Tasso Argyros
243 posts

@tasso
entrepreneur & vp eng @ Databricks ··· founder of category defining cos: Aster Data (big data) and ActionIQ (customer data platform) ··· Stanford CS PhD dropout










I now constantly get questions about the SAAS meltdown, role of AI, system of records etc. I don't have an answer to all these. But I do know that we saw an acceleration in our business in Q2, Q3, and now finished the year with accelerating Q4. The question is, why? Short answer: AI. But the underlying reason is subtle. We are growing fast because we are finally removing the biggest bottleneck in data: the technical barrier to entry. For years, if you didn’t know SQL, Python, you were locked out of the value chain. That has changed fundamentally with the 𝐆𝐞𝐧𝐢𝐞 𝐟𝐚𝐦𝐢𝐥𝐲, and it is the "secret sauce" behind our recent momentum: • 𝐆𝐞𝐧𝐢𝐞: Analysts can query data without any SQL. I use this every day myself. • 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐆𝐞𝐧𝐢𝐞: Builds end-to-end AI models for you, similar to Cursor for ML on your data. • 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐆𝐞𝐧𝐢𝐞: Write Spark pipelines, does plumbing, troubleshooting. We've been talking about DATA + AI democratization, but generative AI finally enabled it in a way that wasn't possible before. That's why we're seeing a market response. Take 𝐋𝐚𝐤𝐞𝐛𝐚𝐬𝐞 𝐏𝐨𝐬𝐭𝐠𝐫𝐞𝐬. We launched this serverless engine for agents and apps recently. At 8 months into its journey, its revenue is already 2x what our Data Warehouse product was at the same stage. All this taken together, we ended up with the following stats for Q4: 🚀 $5.4B Revenue Run-Rate, growing >65% YoY 🚀 $1.4B AI Revenue Run-Rate 🚀 FCF Positive for the year 🚀 NRR >>140% databricks.com/company/newsro…



Software is no longer the bottleneck.


@DbrxMosaicAI @jefrankle The data brick got flagged at security but ultimately made it through.


Venture capital has a recurring problem. It keeps measuring the wrong thing with great confidence. Distribution is not fake but it is often a terrible proxy for usage. Something being installed by default does not mean it is used in any meaningful way. If default presence equaled engagement then everyone would be a power user of Apple Calendar simply because it ships with the phone. We all know that is not how behavior works. You can touch a product without choosing it. You can open it once a quarter without relying on it. Default availability measures proximity not pull. Proximity is a very weak signal for product market fit. This is where the Slack versus Teams framework keeps getting recycled as wisdom when it is really just convenience. Teams benefited from bundling. That made it visible everywhere. It did not magically make people love it. It did not make it indispensable. It made it unavoidable. Those are very different things. Venture capital loves proprietary distribution because it is legible. You can put it in a spreadsheet. You can count seats provisioned. You can point to rollout numbers and feel smart in a partner meeting. Engagement by contrast is messy. It requires looking at behavior instead of slides. It requires asking uncomfortable questions like would anyone be upset if this disappeared tomorrow. Engagement is how you actually quantify product market fit. That is not a new idea. It is why I got into this business in the first place. Ironically it is also why some of my best investments did not need much venture capital from me or from anyone. When engagement is real capital is an accelerant not a crutch. When it is not capital just papers over the truth for a few more quarters. We invested in Slack at a 250M post. Slack later exited to Salesforce for roughly 27.7 billion dollars. Hardly a failure by any reasonable definition of venture outcomes. Despite the annual obituary tweets plenty of remote teams and modern companies still actively choose Slack over Teams today. They choose it despite Teams being free in a bundle. They choose it because it is used deeply inside workflows every single day. Voluntarily. Intensely. Yes you can touch Teams because it is bundled. You can also touch the unused exercise bike in your garage. That does not mean you are fit. It just means you own equipment. If you measure properly real usage depth of collaboration willingness to pay retention over time and expansion within teams I would still bet Slack wins on engagement and lifetime value over the framework that keeps getting retweeted. This is why venture capital keeps making the same mistake globally. Indian VCs are not uniquely doomed here. They are just inheriting the same outdated measurement systems with more enthusiasm and fewer scars. Installed base looks impressive. Engagement compounds quietly. So we get confident tweets instead of careful analysis. Headlines instead of homework. Distribution slides instead of behavioral truth. That is fine. But let us not confuse legibility with correctness. Worth doing a bit of work instead of retweeting the framework

@DonniHonig We haven’t done it yet because it is much more likely that people create successful PMF unicorns staying in SF Bay Area at a rate of 2.5x more NYC is about 2x


“Extraordinary results demand extraordinary effort” A powerful conversation with Matt MacInnis (@stanine), long-time COO and newly minted CPO at @Rippling We discuss: 🔸 Matt’s transition from COO to CPO and what surprised him about leading product 🔸 The “high alpha, low beta” framework for evaluating people, processes, and products 🔸 Why you should deliberately understaff projects 🔸 Why you should treat escalations as gifts 🔸 Why processes exist to reduce volatility—and why it will also suppress creativity 🔸 When founders should quit their startups (hint: much earlier than VCs want you to) 🔸 Much more Listen now 👇 • YouTube: youtu.be/O_W76LR77Vw • Spotify: open.spotify.com/episode/1IdiYw… • Apple: podcasts.apple.com/us/podcast/10-… Thank you to our wonderful sponsors for supporting the podcast: 🏆 @GeminiApp — Your everyday AI assistant: ai.dev 🏆 @datadoghq — Now home to Eppo, the leading experimentation and feature flagging platform: datadoghq.com/lenny 🏆 @gofundme Giving Funds — Make year-end giving easy: gofundme.com/lenny


Lots of experienced devs are not going to get through “their grief cycle”, they’ll just leave the industry or move into real management. Coding with AI is not intrinsically enjoyable unless you have an ownership stake in the outputs. It’s not why we got into coding.

I'm hiring interns for next summer at @databricks! Specifically on (1) empirical RL at scale on non-verifiable tasks and (2) enabling real people specify the behaviors they want out of AI (e.g., through evals) on highly complex tasks. 🧵



People often ask me why we think Databricks can succeed in new areas we expand to. This is the recipe why: we build stellar teams in areas where we think we can greatly improve on the status quo. Lakehouse was one, Lakebase is next, but there's more coming, especially in AI.

