Rahul Mathur Profile picture
Oct 18 7 tweets 5 min read Read on X
This year, ICONIQ led Anthropic’s $5bn Series F, ElevenLabs $180M Series C, Legora’s $80M Series B and TinyFish’s $47M Series A..

They are a media shy Wealth Mgt firm with $90bn+ of AUM who put their money where their pen is (quite literally)

Earlier this yr, they published their “State of AI 2025” report - now they’ve topped it up with several updates in a 73 page analysis of their portfolio companies.

Sharing a few takeaways ⤵️
(1) “AI” has changed what “best in class” means for Software

(a) OPEX leverage: ARR per FTE has increased 65% from ~$200K Pre-AI (2020) to $331K now; touching $390K for co’s with $500M+ ARR

(b) The goalpost “Rule of 40%” is now the “Rule of 60%” - BUT, there is ONE nuance: FCF margins are taking a hit - but growth rates are MUCH higher (even for “AI adjacent” SaaS co’s)

(c) NDRs (net dollar retention) also takes a hit - gold standard was ~135% in 2020; it is now down to ~115%. Elevated churn (experimental ARR, hype etc), competition & pricing pressure is hurting.

The change doesn’t impact Seed investors (like me) - but is VERY relevant for Growth & Public market investors.

Btw, ICONIQ’s Enterprise Five - ARR, NDR, Rule of 60%, Net Magic Number & ARR per FTE provides an excellent scorecard for Growth investors!Image
(2) The mere presence of “AI” revives growth (not joking)

(a) The one pint comment is that every VC has an “AI heavy” portfolio because all SaaS co’s have pivoted into AI co’s

(b) There is some data to support why this might help - it reinvigorates innovation (EPD teams), outbound (Sales morale) & inbound demand (FOMO)

(c) I’ve seen at least one of our portfolio co’s come back from extinction to growth mode because of AI - even SMBs can now be targeted profitably (CS cost is down, Sales can be automated & outcomes can be sold)

Example from ICONIQ: Palantir went from 15% YoY growth in Q2 ‘23 to ~35% growth in Q4 ‘24 - driven by “AI”Image
(3) ERR is the new buzzword - “Experimental Random Revenue” - elevated Churn haunts

(a) ICONIQ totally didn’t come up with that - I added it to an internal doc last week for one of our partners (who totally glossed over it)

(b) There is a dual headwind for revenue retention in PLG companies - logo churn (competition driven) and contraction (price negotiation during Enterprise signing)

(c) This is the counterbalance to $100M ARR in 3 years - revenue is low(er) quality esp. because Enterprises & Prosumers are in the “discovery” mode with tooling (not deployment mode)Image
(4) AI native v/s AI enabled v/s AI adjacent

(a) AI native co’s see 3x faster revenue addition v/s AI adjacent co’s

(b) $100M ARR in 2 yrs is possible & proven (albeit subject to the FCF margin & churn dynamics mentioned earlier)

(c) You will see AI native companies with < 20 employees when at $100M ARR

(d) AI native co’s have pipeline acceleration with 2x converts from trial to subscription

But, like I pointed out above - faster revenue growth ≠ better business 😊

Downward pricing pressure remains painful (more notes below):

x.com/Rahul_J_Mathur…Image
(5) GC’s Hemant Taneja got roasted but he’s right - (1)3322 has become (5)5322

If you read this and said :”WTF is this?” - here’s the simple explainer:

(a) Pre-AI (2020) - the gold standard of Software was to do $1M ARR in Y1 - and then triple, triple, double & double again i.e. get to $36M in ARR by Y5 and therefore to ~$100M by Y8

(b) Latest data from a16z suggests that gold standard in Enterprise AI is to do $5M ARR in Y1 (driven by FOMO & everything else)

(c) Per ICONIQ, in a post AI era (2023+) - the gold standard trajectory in AI is to x5 in Y2, x3 in Y3, and X2 for 2 subsequent years i.e. $300M in ARR by Y5

Btw, despite our reservations on AI ARR - Harvey has hit $100M in Y3, Cursor (Anysphere) crossed $500M in Y4 etc. Ballistic growth (if you get the joke)Image
Those of you who have read several of my posts might wonder why I frequently cite ICONIQ - they have a unique structure (given their Tech founder centric LP base) and an incredible portfolio (Glean, Databricks, Snowflake etc)

While most valley VCs have pivoted to video “marketing” - ICONIQ has stuck to long form writing with independent research (see the footnotes on methodology etc in their publications)

One can only aspire to match their level of diligence, discipline & foresight! This post is (at best) an average summary of their work - you’d do yourself a favor reading it first hand 😄

➡️ ICONIQ’s State of Software report can be downloaded here: iconiqcapital.com/growth/reports…

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More from @Rahul_J_Mathur

Oct 16
Doug Leone has been a Partner at Sequoia for 32 years now - he doesn’t do a lot of interviews - but his track record is incredible - ServiceNow ($187bn), Nubank ($73bn), Medallia (acq. $6.4bn) and he continues to serve as a board member to many companies.

Doug did a rare interview on the Training Data podcast where he answered some key Qs about investing in AI today; sharing a few notes from the same:
(1) Where will value accrue in the AI stack? Applications!

“Values always accrues up at the application layer - near the customer, money & the business user.”

(2) Can you sit out of AI as an investor? Nope
”You are at the front end of a cycle, which doesn’t mean you have to invest in everything but you have to invest.”

(3) What to do about round prices in AI today?

“You see a small company with very good momentum in a front end of the market; you lean in and you hold your nose on price.”

(Arguably, Sequoia did this with Google back in the day; a $100M post money valuation for a Series A)
(4) Did Sequoia foresee the AI wave? Nope!

“In March 2022, I had a slide that talked about all the waves - the next box was a question mark. We (Sequoia partnership) did not see the wave coming; this wave has been a tsunami and I don’t think there’s there’s any end in sight.”

PS: That March ‘22 investor interaction was Doug’s last one as an active partner at the firm (he has since stopped doing new investments & has more of an advisory role)

(5) Is AI any different from the previous waves? Maybe

"The AI wave is bigger than the Industrial Revolution. I had never imagined that there would be something bigger than connectivity (Internet) and the mobility (Mobile) era."

(6) Does company building change in a world of AI? Nothing has changed.

“The business fundamentals are very similar - you need a terrific founder, world class engineers, salespeople that are not administrator etc”
Read 4 tweets
Oct 9
GFF is an annual circus show for Financial Services professionals, founders & entertainers. Hence, I chose to wear my customary Papa Pump outfit (IYKYK, comment below).

I spent most of my two days in meetings (managed to get 17 done!) and a bit of time at the exhibition booths; sharing a few notes from these meetings:The trademark yellow tie predates an Internet meme celebrity
(1) AI first collections agencies are emerging 🗣️

- Lazy VCs wrote this space off when Credgenics raised a $50M Series B from WestBridge in August 2023
- Collections is evergreen - stress emerges in each pocket at different times (e.g. unsecured PL, MFI etc)
- Due to competition now, Collections has moved from Software + Service to Outcome i.e. pricing based on ROR uplift delivered; this is a great pricing model for AI services
- The prev. gen of Collections companies were either offline agencies or human call centers or a hybrid of both
- The modern Collections agencies are building AI enabled Credit Engines i.e. a full funnel process to manage cases from pre-due to NPA; Voice AI to call || agents to email, WhatsApp etc || route optimization to direct field force etc
(2) Lots of activity in MFD roll-up & tech enablement 🏦

- Everyone’s uncle wants to build the new age Prudent (NSE:PRUDENT)
- The thesis is “priced in” - the next gen of MFDs are digitally savvy and/or are based in non-metro cities; they need training & then tenure to build their book of biz.
- Several VCs have started to take positions (e.g. $6M Series A in AssetPlus by Eight Roads, $3.5M Seed in ZFunds by Elevation)
- There are several companies still stepping out of woodwork; primarily ex AMC execs or seasoned BFSI professionals who have spent 3+ yrs building their book while bootstrapping & are now starting to raise $$
Read 7 tweets
Sep 26
At a private event, the CEO of a leading Indian bank highlighted that over the next 3 yrs, they will spend ~10% of their IT budget on AI.

For context: The IT budget (headcount, Tech, outsourcing etc) at this size of bank would be ~₹2,500 to ₹3,000 crore per year

Single bank spend on AI is therefore ~₹250 crore per year (there are approx. 25 odd banks of this size or larger).

Now, there are 2 ways to interpret this ~₹6,000 crore ($750M) per year AI spending ⤵️
This depends on whether you are an optimistic or critic:

(1) Optimistic view: In 3 yrs, the actual spend would be X2 or X3 higher i.e. > ₹15,000 crore because some of the AI deployments will eat into the labor budget (check the example in this Thread below)

Indian banks are lighthouse customers (for SEA banks & rest of Indian Enterprise); therefore it would catalyze X5 further spending on AI - HUGE (~₹50,000 crore p.a.) opportunity within India itself - great for startups!

(2) Critical view: ~₹6,000 crore in AI spending is not sufficient to catalyze a new set of FinTech Infra vendors (centered around AI); maybe all of the incremental spend will go to incumbent service & Tech vendors

But, for the critics, I have 2 interesting examples from BFSI:
Navana AI x Bajaj Finance

Mr Sanjiv Bajaj (MD @ Bajaj Finserv) highlighted ~6 months ago that ~₹150 crore of loan disbursal per month is powered by Navana AI (indic voice AI)

The most recent public figure is that Navana AI is doing ~₹1,000 crore of loan disbursal per month for Bajaj Finance - rapid scaleup!

For those who track Bajaj Finance closely, you would know about their “FinAI” company ambition & the goal of saving ₹150 crore in OPEX for FY26 using GenAI; I had covered this in a 20 minute Breakdown video earlier this year:

youtu.be/qUWfilxx-yI?si…
Read 5 tweets
Sep 25
From 0 to $15M ARR in 90 days of launch - Emergent Labs is India’s fastest growing AI startup🤯

Emergent was founded a year ago by Dunzo’s former CTO Mukund Jha - they now have 57 team members (75% of headcount) in India

The velocity of product shipping & pace of ARR addition is insane; last month they were at $10M ARR - they’ve grown 50% MoM!

Sharing a few mind blowing facts about this company⤵️
The metrics are off the charts 📈
(a) 1.5 million+ unique apps created
(b) 1 million+ sign-ups to date
(c) 25,000+ paying customers
(d) 180+ countries represented in user base

Above was reported this month by the company during interviews with TBPN & with their early investor Together Fund (anchored by Freshwork's founder Girish)

Emergent is a great example of “Globally competitive product, built with love from India”
How did they execute this?

Firstly, this is a “hardcore” team (by all standards) - they subscribe to the 996 culture which is in Mukund’s DNA from having run an operationally intensive offline business (Dunzo)

They key to their early success is Engineered (not, accidental) Virality:

(1) Invested in Product upfront: They had 8 team members (incl. 2 founders) who spent 6 months building; ensuring the “time to value” from the onboarding flow to end output was brought from 1 hr to < 20 mins

(2) Built technical differentiation: Neo, their AI coding agent, ranked no.1 on SWE-Bench on two occasions (Oct ‘24 and Dec ‘24)

(3) Created hype before launch: Because of the technical progress & word of mouth, they had a 20,000+ member invite waitlist ready before launch day

(4) Thoughtful GTM on launch day: Planned weeks in advance & allocated a $100K marketing budget for TikTok, Reels & Twitter - used the influencer channel to their advantage

(5) AI-led continuous content push: For a brief period post launch, they released ~500+ AI generated videos of the product, customer outcomes & UGC success moments

(6) Product/PLG: Per the team, ~5% of their inbound traffic is attributable to the “Made with Emergent” badge (this is the old Hotmail trick); you can see this even in the tools I have built with Emergent

Overall, this is what you’d expect from a 2nd time founder - thoughtful & planned GTM followed by relentless execution (which has paid off); this brings me to:
Read 7 tweets
Sep 9
Reliance & Meta are together investing ₹855 crores to build AI Infra in India

RIL is also partnering with Google to build an AI data center in Jamnagar

At RIL’s 48th AGM, Mukesh bhai stated: “Jio promised and delivered digital everywhere and for every Indian. Similarly, Reliance Intelligence promises to deliver AI everywhere for every Indian”

“Reliance Intelligence” is RIL’s next bold bet after Jio ⤵️
Remember: RIL has partnered with both Meta & Google in the past for Jio

Jio raised ~₹150,000 crore from strategic & PE investors in early 2020 which included:

(1) Meta, who invested ₹43,574 crore (~$5.7bn) for 9.99% (announced April 22, 2020)

(2) Alphabet, who invested ₹33,737 crore (~$4.5bn) for 7.73% (announced July 15, 2020)

Btw, these two investments were strategic in nature e.g.

JioPhone Next was built with Pragati OS - a collaboration with Alphabet in Oct ‘21

Meta owned WhatsApp launched a deep e-commerce integration with JioMart in Oct ‘22

Jio is expected to IPO in the ~$110bn valuation range i.e. an acceptable 13% $ IRR for Meta & Alphabet

Meta & Alphabet may sell down some stake in the IPO (liquidity always helps drive re-investment decisions)

Btw, I had written about Jio’s upcoming IPO almost a year ago (nothing much has changed in the analysis) - bookmark for future reading:

x.com/Rahul_J_Mathur…Image
So, what is this collab b/w Meta and RIL?

RIL and Meta are forming a JV with 70:30 split to create a platform targeting Indian businesses to offer AI services billed on a monthly basis. Meta is the Tech partner offering its open-source Llama models & deep integrations with the Meta ecosystem products (e.g. WhatsApp)

Key features are:

(i) Local data residency

Indian user queries will hit local data centers & data won’t moved to SG/USA. We have already seen the RBI Mandate which requires payment related data to be stored within India; so there is clear biz rationale for the same

(ii) SMB focused products | WhatsApp focused
SMBs in India prefer Zoho & other SaaS partners who offer low cost products for tracking inventory, analyzing sales data & managing relationships.

RIL Intelligence plans to offer AI solutions like an automated sales analyzer which can scan bills & run customer campaigns on WA

(iii) India pricing

Since OpenAI has led the way here with ChatGPT Go - RIL Intelligence will aim to provide business solutions at an affordable India specific pricing (esp. since the underlying models are hosted in their own cloud)
Read 7 tweets
Sep 5
I read Ruchir Sharma’s new book “What Went Wrong With Capitalism?” earlier this week

Ruchir spent 25 years at Morgan Stanley & headed up their Emerging Markets investments ($20bn+ in AUM across funds)

He’s also a great writer on macroeconomics & history; there are 3 great points which he has made in this book ⤵️Image
First, I think it is important to set the premise of this book:

Ruchir highlights how constant intervention (bailouts, interest rate drops, welfare programs) from the Govt & Central Bank has altered the normal functioning of key economies:

(1) Recessions are less frequent but more severe

(2) Wealth is more concentrated (Top 1% of US controls 40% of wealth)

(3) Economies are becoming financialized (10% of income flows to Finance)

(4) Debt fueled economy: 80% of US lending happens in the shadow bank economy

(5) Big companies dominate: Low interest rates & high regulatory compliance requirements perpetuate oligopolies & monopolies

The funniest acronym used in the book was NINJA - a loan customer who has No Income (NI), No Job (NJ) and no Assets (A) - which is apparently Ruchir’s characterization of sub-prime lending in USA.

The 3 points most relevant to the common man are:Image
(1) Investing has changed

Gugenheim CIO said: "The Fed has made it clear that prudent investing will not be tolerated”

And, Ruchir adds to this by highlighting: "Investors get outsized gains during the boom times and benefit from socialization of outsized losses during the pain times”

Unfortunately, the current Govt approach (low interests + bailouts etc) stand to benefit the rich far more than the poor:

(a) Capital markets are overwhelming owned by the Rich | Bailouts help the stock market more than the economy
(b) The Rich have assets which can be used to access cheap debt to earn more income

(c) There has been a steady low of wealth from labor to capital (”ownership”) with automation, offshoring & financial engineering

The data shows this too - Share of income owned by the Top 1% in USA is back to its peak of 20%; top 1% own ~40% of wealth (still shy of the 1929 peak of 50%)

YOLO isn’t just for the retail pleb but also for the Manhattan institutional investor - you either make bank or get a bailout.
Read 7 tweets

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