Arun

John O'Shea at

[Arun @arunsdevine]

Reminds me of how Ethereum bag holders invested in DeFi apps. Fat protocol thesis...

[Joe Weisenthal @TheStalwart]

Great chart from Slok. Everybody knows that a very small % off companies are consuming the lion's share of token consumption

What's interesting is that of those top 1% of spenders, they're overwhelmingly VC-backed companies. May have implications if VC-funding starts to slow.

[Arun @arunsdevine]

@gokulr That makes sense is a models all the way up world. A lot less in a harnesses all the way down. A lot of the recent math wins have actually been the latter sold as the former.

[Arun @arunsdevine]

@ponnappa You should consider a career in AI Alignment ya.

[Arun @arunsdevine]

@nutanc Only 14 people will get the equity upside though. Like Instagram and WhatsApp scenarios

[Arun @arunsdevine]

@anuragwho @alexandr_wang Muse can be meta’s angle to compete with google search

[Arun @arunsdevine]

@pitdesi Isn’t the TAM for this of the same order of magnitude as google search?

[Arun @arunsdevine]

@buccocapital @zephyr_z9 How were the content companies caught unaware while the commerce companies seem ready for the fight?

[Arun @arunsdevine]

I have the highest regard for you Gokul. But a crazy set of problems don't translate from AI native shops to the rest of the world. e.g. Accounting Ops are quite different for s/w companies and retail/mfg shops. One doesn't get you the other. [We have scars on both btw]

[Gokul Rajaram @gokulr]

The New Kingmakers

It's become clear that revenue scale no longer matters - or is correlated - with raising a round. It's important but not sufficient.

Besides team caliber, what ACTUALLY matters to fundraising is how many top AI-native companies use your products, love your products, embrace your products and profess undying loyalty to you (i.e. say they won't replace it at the drop of a hat).

Why?

AI-native companies are the hardest customers to win. They have the engineers to build it themselves. They have the taste to know when something is mediocre. They try every new tool the week it launches and rip it out the week after. If one of them pays you and stays, your product survived the toughest evaluation there is. Investors know this.

Revenue can be bought. Pilots, services, discounts, a heroic enterprise sales team. ARR built from Fortune 500 pilots proves you can sell. The product might still be mediocre. Loyalty from a kingmaker can't be manufactured.

These companies are the leading indicator. Investors are underwriting where the market will be in 5 years, and the AI-native companies are already living there. Their workflows today are everyone else's workflows in 2029. If they picked you, you've been chosen by the buyers everyone else will copy.

The last reason is distribution. Kingmakers talk. Their engineers post what they use. Their founders compare notes. One of them begets the next three.

Who

There are probably ~50 AI-native companies that are perceived as kingmakers for startups. I've seen $50M+ rounds raised on the backs of just having one of these as a customer. (not pilot, but actual paying customer using the product as a core part of their infra and workflows).

Meanwhile, I see early-stage founders spending 12 months chasing CVS, Walmart, and Pfizer. Long procurement cycles, security reviews, a pilot that never converts. Even when it lands, the logo proves you can survive procurement. That's the wrong thing to prove in 2026.

If you're an early stage enterprise/B2B AI company, Instead of targeting CVS, Walmart, Pfizer, etc, go after the companies on Forbes' AI 50 list.

The new milestone is kingmaker logos. That's what your next round will be priced on.

[Arun @arunsdevine]

@ponnappa Ya I really want a sci fi loving vc to be investing in accounting software. 🏃‍♂️

[Arun @arunsdevine]

Us accounting focused plebs will call this the internal audit function.

[Ali Ansari @aliansarinik]

evals will be the primary moat for every enterprise long term.

Abridge CEO @ShivdevRao dropped an amazing article about this on how enterprises are approaching product evals (link in thread).

many AI product teams are already committing $10M+ annually to human expert evals, because you can't improve what you can't continuously measure.

our bet is that within 12 months, every Fortune 500 building AI products will have an 8-figure evaluation stack.

the very early days of the data exponential is now.

[Arun @arunsdevine]

@ku1deep @ponnappa Give people what they want sir.

[Arun @arunsdevine]

@ponnappa Sir my daughter's IB school evals are usually 25 pages and appear AI generated. Unreadable pro max.

[Arun @arunsdevine]

@nikhiljoisr Also when your particular fastag lane moves fast and rationally.

[Arun @arunsdevine]

@ponnappa I was thinking it’s more of hearing all these other startup’s 0-500M+ ARR in 3 months.

[Arun @arunsdevine]

Also a mistake startup founders make...

[Arun @arunsdevine]

Ownly may have some odds of disrupting swiggy/zomato

[roon @tszzl]

you either die a frontier lab or live long enough to see yourself sell compute

[Arun @arunsdevine]

@dharmeshba Sometimes konjam nilavu also da.

[Arun @arunsdevine]

All I can tell you now is that this is just a legacy myth. Not true anymore and we have scars to show for.

[Alok Goyal @alokgoyal1971]

5/
The hard part: initial scale built in India is often not an asset but a liability.

It tethers your thinking to being incremental from what you've already done at home.

[Arun @arunsdevine]

@ponnappa Sir its entirely due to MSFT's trust esp around InfoSec++. No one else comes close.

[Royal Challengers Bengaluru @RCBTweets]

Ee Sala Nu Cup Namdu! ❤️‍🔥🏆

Welcome to the RCB Era, ladies and gentlemen! 😎

You waited, you believed and you stayed… this one’s for you again, 12th Man Army! 🥹❤️

#PlayBold #ನಮ್ಮRCB #IPL2026