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.
We're thrilled to share that Swiss tennis legend and philanthropist @rogerfederer—one of the greatest male athletes the sport has ever known—will address the Class of 2024 on Sunday, June 9. Read more: https://t.co/3cGyr5UoM2
Really interesting breakdown of one of the key decisions in building a cloud data service by @vanlightly. Long story short: there is a reason all the biggest and best cloud services (from S3 to Snowflake) aren't just puppeteering per-customer clusters in the customer VPCs.
Thanks @ThomasOrTK!! We’re excited at @confluentinc to partner with @googlecloud to build retail and fin serv solutions for our customers together leveraging gen AI.
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. https://t.co/AxwvdH3YqH
@jaykreps Join us in celebrating Rohan Sivaram as our next CFO. Rohan has been instrumental to our success over the last 3 years - we couldn’t be more excited. 🎉
And we extend our deepest gratitude to Steffan & his tremendous contributions to Confluent. https://t.co/dpkUIXw0mu
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 👇
https://t.co/JqgNnHtTBN
🔔🔔🔔
We rang the @NasdaqExchange opening bell this morning to celebrate the 2 year anniversary of our IPO.
Thank you to our incredible customers and investors who inspire us everyday to continue our mission to set #DataInMotion!
I’m so saddened by the passing of my wonderful friend Tina Turner.
She was truly an enormously talented performer and singer. She was inspiring, warm, funny and generous. She helped me so much when I was young and I will never forget her.
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 :-)