The State of AI in SaaS: SaaS is Dead, Long Live SaaS This started as an analysis of Andrej Karpathy's excellent overview of AI's capabilities. Those who deeply understand this will make all the returns and everyone else will lose a lot of money. "Ghosts" is a brilliant metaphor for what we've created. They're not animals, and they're definitely not human. They are imperfect replicas of us. Karpathy describes them as a "statistical distillation of humanity's documents". AI channels that distribution more effectively than any human and can beat us at Go, schoolwork, analyzing medical images, and many well defined tasks. At the same time, it lacks the reward systems that humans use to improve including curiosity, empowerment, play, intrinsic motivation, and culture. As a result, AI's capabilities are limited. If you watch how the best work gets done with AI, it happens in chunks where a human supervises the output and gives iterative feedback to the AI. Large scale autonomous agents are brittle and fail quickly. Watch anyone vibe code an application with any level of novel complexity. AI also faces integration barriers into existing organizations. AI is not capable of pulling a lot of the levers you need to be effective like coordinating with multiple stakeholders, building trust, authenticity, and interacting with different modalities across time and space. You could argue that the average human doesn't either, but people know when they're interacting with an AI and don't allow it the same agency as they do to people. The most successful AI B2B companies actually need more humans to integrate what they've built (forward deployed engineers) than traditional B2B SaaS. What's next? Those who understand AI and its limitations will transform the industry. Incumbents will be killed by those who know how to leverage AI. I've seen countless homepages talk about being the "AI platform for AI agents" but can't even string a demo together. Meanwhile they're trying to pitch a future where fully autonomous entities collaborate in parallel to write all the code and humans are useless. They will be the first to be replaced when they get surpassed by AI native companies. The investors blindly throwing money into companies at 100x multiples are going to lose their money. I spoke with one of the most disciplined investors I know last week. They said they felt they had to play the game on the field even though they knew it didn't make sense. And this was from someone who is closer to the technology than 95% of investors. On the other hand, companies who deeply understand AI will win everything. Cursor, Glean, Decagon, Sierra, Linear, Lovable, Replit, Bolt, and many AI natives are off to a great start. While 90% of incumbents haven't adapted, it is possible. Figma, Notion, Vercel, Box, and Intercom have done a great job of tearing down what they have and rebuilding AI native products. They have teams who are close to the current capabilities of the models. They also understand their problem domain and as new capabilities come out know what capabilities will map well to what problems in what way. They are able to deliver on AI's promise to their customers. Whereas the majority of existing companies will die. In analytics, the door is wide open. In spite of many of our competitors filling up their homepages with the text "AI", I haven't seen a single compelling demo. We're still working like it's 2015. This will change. We have spent the last year at Amplitude rebuilding our team to be AI native. We've learned about what models are capable of, how to write prompts, and how to leverage evals for building great products. We've worked with our customers to see what gets used in practice and what doesn't. We are building a vision for the future of analytics. We are all in on AI at Amplitude. Stay tuned for what's next. We're going to be fast and furious with AI products at Amplitude.

Taking center court as the #Dartmouth24s Commencement speaker 🎾… bit.ly/4ap8Mzq

Taking center court as the #Dartmouth24s Commencement speaker 🎾… bit.ly/4ap8Mzq

Next up at #KafkaSummit London: Meet Tableflow✨ With Tableflow, developers will be able to materialize Kafka topics & schemas as #ApacheIceberg tables in one click to feed any data warehouse, data lake or analytics engine. Learn more about our vision → cnfl.io/3PnWW0f

BYOC is something I’ve been thinking about recently so I decided to write down the thoughts I have on it and where I think cloud services are going in general. jack-vanlightly.com/blog/202…

We’re committed to providing the industry’s most open cloud platform. New integrations with companies like @MongoDB @DataRobot @confluentinc will help businesses develop bespoke gen AI models & apply AI to use data more efficiently. cloud.google.com/blog/produc…

The ClickHouse Kafka Connector is now an official Custom Connector for @confluentinc! With this connector, you can now use Kafka on Confluent Cloud to easily load data into @ClickHouseDB Read our tutorial on building a zero-code Kafka pipeline 👇 clickhouse.com/blog/real-tim…

In preparation for the big day, here's some sage advice from just a few of our favorite commencement speeches—including @jaketapper, @agordonreed, @YoYo_Ma, @mindykaling, @LeymahRGbowee, @nytdavidbrooks, @shondarhimes, @wendykopp, @ConanOBrien, and @DangeRussWilson!🎓

Prepping tonight for my keynote tomorrow morning at #kafkasummit London. I think this is probably the most new product announcements, cool open source stuff, and overall material I've ever had in one talk. I guess I'll need to talk fast :-)

Our May/June 2023 issue is online now. Featuring Dan Reicher ’78, Nathaniel Johansson ’18, and an in-depth profile of new president @sianbeilock by @abigailDJ '03 dartmouthalumnimagazine.com/