Top startups are seeing 26x YoY revenue growth

👇🏼 I’ll be hosting the annual DECODE conference next month!

Join the conference, and let’s catch up in-person!

• DECODE is the largest founder community co-hosted across UC Berkeley and Stanford. The DECODE annual conference focuses on helping founders in their earliest stages of starting a startup. I’ve had the honor of serving on the DECODE board since 2016.

• What makes this gathering unique? Speakers don’t just speak on a big stage and disappear. They stick around for off-the-record roundtable discussions with a dozen of handpicked founders, giving attendees a chance to not just listen but to actually meet them.

Past attendees have …

• Successfully raised pre-seed, seed and series A rounds from top-tier investors (including a16z, Sequoia and Y Combinator), met through DECODE roundtables and dinners.

• ​Identified advisors and mentors (including experts from Apple, Google and Microsoft) who’ve helped them 10x their startup’s growth.

• ​Found co-founders and early hires for their startups through DECODE community members, like the founding teams of Databricks ($62bn valuation), Agora (IPO) and FlowGPT (Series A).

3 trends in startups/tech/venture

📈 Top startups are seeing 26x YoY revenue growth

• We all now know that AI enables founders to build in hours what used to take months. However, the latest data shows top startups are scaling revenue exponentially faster, too.

• According to the Pacesetter Index, the top quartile of startups generating under $10M in revenue is growing ARR by an astounding 26x year-over-year (meaning a startup generating $10M today would hit $260M this time next year).

• A prime example of this speed: Typesafe AI's Jev — an advanced decision-making model that’s great at multiple choice — scaled from $0 to $100M in just 7 days.

🤖 Frontier AI labs are seeing customer concentration

• Per the latest data from Ramp, ~80% of OpenAI and Anthropic’s enterprise revenue comes from just 1% of customers with a heavy concentration in tech and AI.

• Anthropic’s leaked IPO prospectus confirms this datapoint, with ~25% of Anthropic’s revenue coming from just 2 unnamed customers.

• Bottom line: Yes, enterprise AI spend is surging, but this spend is coming from a small handful of players.

💰 Startup fundraising has become a two-step process

• In the past, when startups raised money, they’d approach investors and raise as big of a round as they can in one go. That process is now being split into two steps:

  • Step 1: Raise at a lower valuation from strategic partners who help build the company.

  • Step 2: A few months later, land a big valuation markup from deep-pocketed capital partners.

• We haven’t just seen this process play out repeatedly across our portfolio. It is also validated by data from Sequoia which suggests that founders are raising at an average post-money valuation of $110M in step 1 and then raising at an average post-money valuation of $3.4B post-money in step 2.

2 theses on what’s next

🤖 Intelligence per megawatt will become the new metric to measure

• With so much money flooding AI startups, the bottleneck to startup growth is no longer monetary but physical: electricity access, permits, and supply chains — and how to get access in the most capital- and time-efficient manner possible.

• Therefore, it will no longer be enough to say that you’ve got the most powerful model; you’ll need to be the most powerful on a per-megawatt basis.

🤔 Startups will increasingly pursue value-based pricing

• When determining how to price their product, startups typically take 1 of 3 paths:

  • 1. Competitor-based pricing: Looking at what the market charges and then charging within the same range.

  • 2. Cost-plus pricing: Looking at how much it costs to serve a customer and then adding a margin.

  • 3. Value-based pricing: Looking at the ROI the product can generate and then asking for a percentage of the spoils.

• Currently, over 1/3 of AI startups default to competitor-based pricing, whether or not it makes sense.

• However, as more companies implement AI (and as we have more data to prove the ROI of AI investments), I expect more founders to lean into value-based pricing to fully capture the upside. This was one of the top topics we discussed at the Jeffersonian dinner I hosted earlier this week. (More about the dinner here. Photo above ☝🏼 and more notes and videos to come.)

• Sandy (my business partner) and I also just discussed this trend at our Stanford entrepreneurship course and where it makes sense for startups to charge (a) per workflow, (b) per outcome, (c) per agent or (d) per agent action.

• (I can’t believe this is already the fourth year that Sandy and I are teaching this course together for full-time and fractional founders! You can find other key takeaways from our course here. Bonus photo below 👇🏼)

  

1 tool I love

🎓 Wearable AI companion

• Sophia, a former student turned advise-to-invest portfolio founder, just launched Blinkko, a wearable AI companion.

• Sophia worked at Apple before getting funded by YC China to focus on AI x hardware at Blinkko.

• Learn more about their recent launch in SF here.

More of my work 👇🏼

🎤 Decode videos | For top Berkeley and Stanford founders

• DECODE is the largest founder community co-hosted across UC Berkeley and Stanford. The DECODE annual conference focuses on helping founders in their earliest stages of starting a startup.

• I’ve had the honor of serving on the DECODE board since 2016. You can find videos from the latest conference I helped host here 👇🏼

🤖 Founders' prompt library

• My team and I have crowdsourced the largest AI prompt library optimized for founders – especially fractional founders — to help them build, sell and operate 10x faster and better.

👥 Pop up board

• I regularly host pop-up boards, a unique 45-minute session where founders ask their toughest strategic questions and get tailored advice from top builders and operators from Google, Microsoft, Meta and more.