Jay Ingle

operator notes on the SaaS-to-AI shift. revenue & enterprise value @letscompport. fellow @aiboomi. 6'3 ailurophile, @ststephensclg alum.

[Jay Ingle @jaybharatingle]

i turn 25 today. and that will give a variety of signals to a bunch of people (hope you get my sarcasm here!)

usually, these posts are a highlight reel of achievements. but today, i just want to talk about this one truth that the below image depicts.

whenever i feel a bit lost or overwhelmed, this is the one truth i always return to. there’s something deeply calming and clarifying about it.

it is a visualization from @waitbutwhy, and it serves as a powerful mental map. looking at it makes me realize that even at 25, i’m standing right on that center line, just as i was when i turned 5, 10, 15,...

two convictions i've built over the years that i deeply believe in (and my belief has just strengthened even more in the last few years):

𝟭. r𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝗰𝗲 𝗶𝘀 𝗷𝘂𝘀𝘁 𝗮 𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲 𝗼𝗳 𝘂𝗻𝗴𝗹𝗮𝗺𝗼𝗿𝗼𝘂𝘀, 𝗱𝗮𝗶𝗹𝘆 𝗵𝗮𝗯𝗶𝘁𝘀.
looking back at the grey lines, i've learned a lot about grind. there are days that absolutely will not go your way; sometimes the whole day feels like a grind to stay on a single line. i’ve learned that the biggest opportunities aren't something you just stumble into; they are often revealed slowly, day by day, to the people who are putting in that quiet, extra effort when no one else is cheering. life will give you chances, but you have to keep pedalling to meet them.

𝟮. y𝗼𝘂𝗿 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 𝗶𝘀𝗻’𝘁 𝗷𝘂𝘀𝘁 𝗮𝗻 𝗮𝘀𝘀𝗲𝘁; 𝗶𝘁’𝘀 𝘆𝗼𝘂𝗿 𝘁𝗿𝘂𝗲 𝘀𝗼𝘂𝗿𝗰𝗲 𝗼𝗳 𝗺𝗼𝗺𝗲𝗻𝘁𝘂𝗺.
looking forward at all those blue lines of possibility, i realize that the hardest thing isn't always knowing what to do, but getting seen doing it. you can possess 100 incredible skills, but if you have 0% visibility, you ultimately create 0 actual opportunities. your network provides what we often like to call "distribution" in today's AI/SaaS world — that invaluable channel that amplifies your work and connects you to the right people. this past year, i’ve tried to be much more intentional about showing up and genuinely connecting, understanding that genuine community doesn't just exist; we have to make it happen.

one thing the last 10 years has made very clear to me — the people around you don't just stay around you. you have to earn that. every call you make, every message you send when there's nothing to gain, every time you show up just because you said you would — that's what builds something real. the people who shaped my years weren't accidents. they were choices. mine and theirs. and i don't take that lightly.

here's to 25 💌 . so immensely grateful for the people who make up my world 🙏

onwards and upwards.

[Jay Ingle @jaybharatingle]

register here: https://t.co/72Qr8exiH8

[Jay Ingle @jaybharatingle]

something is shifting in the Indian AI founder ecosystem.

a year ago, the conversation was about whether AI products could actually generate revenue. that question has been answered.

now the harder questions are coming.

- what's defensible when the models keep getting better?
- how do you sell to enterprises who've been burned by AI pilots that went nowhere?
- how do you build a GTM motion when the category you're in didn't exist 18 months ago?

these aren't questions you answer alone. and they're definitely not answered in a LinkedIn post or it's comments section.

@AIBoomi Bootcamp '26 is bringing 60 AI-native founders together in Hyderabad, July 3–4. working sessions, closed door, the people who are actually in it.

this is where the next chapter of the Indian AI story gets written. Be in the room.

check out the registration link in the comments section. feel free to DM if you have questions.

[Alberta Tech @albertadevs]

BREAKING: CEO discovers tokens cost money

[Avinash Raghava 🇮🇳 @avinashraghava]

Last week in the Bay Area, I found myself sitting in rooms where some of the smartest founders in AI openly admitted the same thing: Nobody really knows where the world is headed.

And strangely, that was comforting.

Because beneath all the hype, noise, and AI hot takes, one thing became very clear: We are all entering a completely new era of company building.

Having spent one whole week with founders, operators, investors, and AI builders discussing what separates the companies that will survive from the ones that will disappear.

A lot of notes, debates, conviction, and honestly, a lot of uncertainty too.

Here are 5 insights that stayed with me:

1. The 95% Accuracy Threshold is the Magic Number: In vertical AI, 85% accuracy means customers spend 15% of their time fixing errors. At 95%, the flip happens and adoption scales rapidly. Every industry is waiting for this moment and whoever gets there first wins the vertical.

2. GTM is the New Moat, Not the Product: Code is essentially free now. Building a product is no longer a differentiator. What separates winners is distribution, forward deployed engineers, in-person relationships, and the ability to sell to strangers (not just your network). Your first $2M should not come from people you know.

3. Triple Your In-Person Meetings: This came up from almost every speaker. Enterprise deals above $100K are won face to face. Go to the Midwest, go to Iowa, go where no one else is going. The founders who are winning are the ones physically showing up where competitors are not.

4. Speed Over Everything. Ship Weekly, Not Quarterly: The companies that are thriving have completely abandoned quarterly roadmaps. Observe dot ai went from shipping quarterly to weekly and called it their biggest unlock. Engineers talk directly to customers. No CPO, no layers. Bias to action is the new operating model.

5. Marry the Mission, Not the Plan: The AI landscape is shifting every 3 to 5 months. Products need to be rebuilt, teams need to change, and pricing models will evolve. The founders who are winning are the ones staying anchored to the problem they are solving, not the solution they originally built.

There are 5 more insights sitting in my notebook that I’m still distilling with better clarity. Will share them in the next post.

And in other news, we’re bringing the same flavour to Hyderabad this July with the authentic Boomi-style way of collaborative learning and bonding through a limited-capacity Chatham House Rules format.

If interested, join us at the AIBoomi (formerly SaaSBoomi) Bootcamp '26 | Hyderabad >> https://t.co/Enap90Lzrp

High signal. Founder-first. Always.

[primordial intelligence @primal_brainer]

https://t.co/tOLg044jBD

[AIBoomi (formerly SaaSBoomi) @AIBoomi]

Last year, Bengaluru showed up with ideas, ambition, and the kind of energy that made us reflect on two things:

1. Why this city continues to shape the future of technology.

2. Why builder events like Startup Weekend should continue to be nurtured.

So, we’re coming back! 🙌

Presenting AIBoomi Startup Weekend | Bengaluru 2026 >> https://t.co/cvoAVT0JGD

Just builders building alongside mentors, operators, founders, and people who genuinely love the craft. That’s it. Period.

Let’s build, again. 💚

#StartupWeekend #Bengaluru #AI

[Jay Ingle @jaybharatingle]

@siddsax @pratyush_r8 awaiting the invite to test Thine!!

[Jay Ingle @jaybharatingle]

in the name of the father, the son, and the large language model. amen.

[Disclose.tv @disclosetv]

NOW - Pope XIV says the church and Anthropic, will work together to "find the way for humanity, in this time of artificial intelligence."

[Jay Ingle @jaybharatingle]

this is the best piece of video that AI has generated yet. period.

[Siddhartha Saxena @siddsax]

Anthropic onboarding day: Michael Scott introducing Karpathy like he just signed Wemby in free agency.

[Avinash Raghava 🇮🇳 @avinashraghava]

https://t.co/nO1vnFBk9p

[Jay Ingle @jaybharatingle]

for last few years the consensus was that AI labs would never make money — compute and inference costs were/are simply too high.

per the FT, Anthropic now expects its first profitable quarter: $10.9B revenue in Q2 2026 (2x Q1's $4.8B), with $559M operating profit.

ahead of OpenAI and xAI. the "AI can't be profitable" question might soon get a real answer.

[Jay Ingle @jaybharatingle]

@neilshroff @kaashvisaxena [email protected]

[Jay Ingle @jaybharatingle]

i recently read in an FT article that 76% of large financial firms say they can't measure the value of their AI.

they've deployed it. they believe in it. they still can't put a number on it.

whoever makes AI ROI legible — clean before/after, honest attribution — has a wedge most founders are ignoring.

[Jay Ingle @jaybharatingle]

95% of Indian CXOs have embedded AI. adoption is no longer the story, maturity is. the

@z47_vc x @OpenAI x @Zinnov survey of 100+ CXOs found four archetypes:

(i) tinkerers (26%): bottom-up, no mandate. productivity gains, no strategic impact.
(ii) enforcers (26%): top-down, no execution. most outsourced. 1 in 5 can't measure ROI.
(iii) democratizers (29%): grassroots that scaled. found new business models almost by accident.
(iv) transformers (19%): bottom-up + mandate on top. value across cost, CX, revenue.

the trap most leaders are falling into: declaring an AI mandate before any team has used AI in anger.

the mandate doesn't create value. it multiplies value that bottom-up adoption has already made possible.

i think the hardest archetype to sell into? 'enforcers'.

[Jay Ingle @jaybharatingle]

Indian AI funding doubled in a year, from $627M → $1.3B, but the headline number hides the more interesting story: where the money went.

(i) vertical AI: 2.5x growth, now 37% of all funding
(ii) horizontal enterprise AI: 2.1x, holding 40% share
(iii) infrastructure & foundation: 1.2x, dropped to 16%

capital has moved decisively up the stack. from "build the picks and shovels" to "solve a specific industry problem".

healthcare, fintech, and legal are the three biggest beneficiaries. these are categories where domain depth creates moats horizontal platforms cannot replicate.

the takeaway for founders: the infrastructure layer is standardizing fast. differentiation now lives where AI meets a regulated workflow, a domain-specific dataset, or a deeply entrenched human process.

my foresight: the next billion-dollar AI company from India is probably solving for a single vertical, not all of them.

[Jay Ingle @jaybharatingle]

the biggest moat for the next wave of AI-native SaaS is going to be the data exhaust companies are already sitting on.

observable assets unlock nonobvious adjacencies:
(i) decision patterns → decision automation
(ii) interaction transcripts → interaction automation
(iii) process traces → autonomous execution

platforms should stop just storing your users' workflow data. and rather use it to build and scale the engine that does the work for them.

[Jay Ingle @jaybharatingle]

a chart from a recent @BainandCompany brief on agentic AI caught my attention. the US market for new applications of agentic AI sits at roughly $100B, of which, only $4B - $6B has actually been captured so far.

that's about 95% of the opportunity still wide open. interestingly, this market isn't coming from fresh software budgets. it's labor spend quietly converting into software spend. the work that today shows up as salaries for coordinators, analysts, and ops folks slowly becomes a line item that says "agent".

for founders building AI-native, this is the real prize. not stealing share from existing SaaS, but capturing work that software never touched before.

the opportunity is massive, but the window to define your position is incredibly short. we're talking quarters, and not years.

[Jay Ingle @jaybharatingle]

it's been ~3.5 years since generative AI went mainstream, and ~1 year since agentic AI started doing the same.

the default question we ask about AI is "how much faster does it make you?"

the FT last week covered a new research from @METR_Evals that pokes a hole in the above question.

when software engineers were earlier asked how much faster AI makes them, they said 20% faster. measured against the clock? and it was actually 20% slower.

so, METR tried different questions this time. instead of speed, they asked about value:

(i) if your team had to replace you with people just like you but without AI, how many copies would they need?

(ii) how long would last month's work have taken you without AI?

(iii) what fraction of the value you currently deliver could you produce if AI tools became unavailable?

reframing from speed to value pulled the estimates down, from ~3x to roughly 1.6x.

the third question is the one I keep coming back to.

it's also a harder question. easy to confuse "i did more things" with "i delivered more value". especially now that AI lets us spin up bonus work that wasn't really moving the needle.

curious to hear your honest answer below.

[Jay Ingle @jaybharatingle]

what fraction of the value you currently deliver could you produce if AI tools became unavailable? @METR_Evals

[Jay Ingle @jaybharatingle]

India doesn't have an AI adoption problem. it has an AI distribution problem wearing an adoption costume.

[Alesya @AlesyaMacWaters]

Founder wives are just VCs who emotionally invested pre-seed

[Jay Ingle @jaybharatingle]

Indian AI funding doubled in a year, from $627M → $1.3B, but the headline number hides the more interesting story: where the money went.

(i) vertical AI: 2.5x growth, now 37% of all funding
(ii) horizontal enterprise AI: 2.1x, holding 40% share
(iii) infrastructure & foundation: 1.2x, dropped to 16%

capital has moved decisively up the stack. from "build the picks and shovels" to "solve a specific industry problem".

healthcare, fintech, and legal are the three biggest beneficiaries. these are categories where domain depth creates moats horizontal platforms cannot replicate.

the takeaway for founders: the infrastructure layer is standardizing fast. differentiation now lives where AI meets a regulated workflow, a domain-specific dataset, or a deeply entrenched human process.

my foresight: the next billion-dollar AI company from India is probably solving for a single vertical, not all of them.

[Jay Ingle @jaybharatingle]

today for an entire generation, the first instinct when they want to learn, build, decide, or apply for something is to open ChatGPT. not Google. not YouTube. not a textbook.

half of India's ChatGPT messages come from users under 24.

48% genZ vs. 33% globally. the 18-24 cohort overtook 25-34 in mid-2024; even as the rest of the world stayed 25-34 led.

this is the most 'under-discussed fact' in Indian tech right now.

some implications:
(i) discovery is being rewritten. SEO is dying for this cohort.
(ii) learning is unbundling from institutions.
(iii) career exploration is happening through conversations with an AI.

if you're building for India's next 200M consumers, embedding into the AI discovery journey isn't a strategy, it is table stakes.