What does it take to write the very first check into a company that has almost nothing to show yet, sometimes not even a finished idea?

Afore Capital helped invent the pre-seed category. When Gaurav Jain and Anamitra Banerji started the firm ten years ago, "pre-seed" was almost a slight, a label for founders who couldn't raise a proper seed round. They set out to build the world's largest pre-seed fund anyway, closing $47 million on a $40 million target, and every fund since has closed above plan. Afore now runs more than $500 million across four funds, with top-quartile DPI on the first three. The idea has become so mainstream that when Sequoia launched its latest fund, it said, "I guess we're pre-seed investors too."

The real substance of the conversation is how Gaurav thinks. He is clear about what matters most in venture, and the order tends to surprise people. Being in the very best companies matters more than anything else, ownership comes after that, and the entry price that so many investors fixate on matters least, because fifty per cent of zero is still zero. He is also convinced that the genuine bottleneck is talent. There is a great deal of money in the world and very few people who can build something truly large, which is why at the earliest stage founders tend to choose their investors as much as investors choose them. You give a founder a million dollars with no collateral, and then you still have to convince them to take it. A pre-seed pitch, he says, is almost entirely storytelling with very little data behind it.

If you want to understand how the earliest checks actually get written, and what it really costs to say no, this episode is worth your time.

00:00 - Trailer
01:00 - From Dehradun to Google to starting Afore
02:08 - The Waterloo co-op that talked him out of every job
03:18 - Back when "pre-seed" was an insult
05:44 - When Sequoia said "I guess we're pre-seed investors too"
07:26 - Afore's three products, and the experiments that failed
09:01 - Hightouch was a travel company when they invested
11:02 - Goldcast: no visa, no money, funded anyway
12:07 - The through line is always the team
14:44 - The Ramp miss
17:24 - "Founders pick us more than we pick them"
18:45 - The constraint isn't capital, it's talent
22:24 - The Solana miss, when it was still Loom Protocol
24:46 - Ramp's Super Bowl ad, the buses, his wife's business
25:32 - What he looks for in founders
28:50 - Coachability, happy ears, and the Mom Test
31:28 - The biggest mistake: falling in love with the idea
35:04 - The three things that matter, and "50% of zero is still zero"
39:25 - "100% storytelling, 0% data"
41:25 - Investing in India, and the fear of being dumb capital
44:41 - "Sign the deal before Monday"
47:26 - One engineer now does the job of 20
51:43 - Raising from LPs, the undiscussed part of VC
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India’s talent has built the world’s tech—now it’s time to lead it.
This mission goes beyond startups. It’s about shifting the center of gravity in global tech to include the brilliance rising from India.

What is Neon Fund?
We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that’s done it before.
Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we’re doing it all at Neon.
-------------
Check us out on:
Website: https://neon.fund/
Instagram: https://www.instagram.com/theneonshoww/
LinkedIn: https://www.linkedin.com/company/beneon/
Twitter: https://x.com/TheNeonShoww

Connect with Siddhartha on:
LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/
Twitter: https://x.com/siddharthaa7
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This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.

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How do you know whether an AI agent is doing its job or quietly failing in production?

Galileo is building the trust layer for AI. Its evaluation and observability platform is how enterprises measure whether the output of an LLM or an agent is good or bad.

Galileo started before "LLM" was even a word. When Atin showed his prototype to Stanford's Chris Ré, his own first question was "what is a language model?" Today its customers include Reddit, Airbnb, P&G, Comcast, and six of the Fortune 50.

Atin spent a decade in big tech before co-founding Galileo with Vikram Chatterji in early 2021. He worked on the knowledge graphs behind Siri at Apple, then became one of the leads and architects of Michelangelo, Uber's AI platform, that hosts thousands of models across pricing, ETA, and demand.

That Uber experience taught him the lesson the whole company is built on; that in AI, observability and evaluation are the real bottleneck, and bad data is catastrophic.

As ChatGPT turned every AI output into something a user sees directly, the measurement problem went from academic to mission-critical. So Atin made a contrarian bet: instead of using giant LLMs to judge other LLMs, Galileo built Luna, small 1-3B parameter models that run evals at breakthrough latencies of 100 milliseconds and below.

If you are excited about how AI actually gets shipped, trusted, and controlled inside real enterprises, this episode is for you.

00:00 - Trailer
01:14 - From India to Apple, Uber, and Galileo
01:34 - Where the name "Galileo" came from
02:38 - Building Siri's early knowledge graphs at Apple
03:29 - Becoming an architect of Uber's Michelangelo
05:15 - Why every AI output is now mission-critical
06:45 - How Atin and Vikram zeroed in on Galileo
07:42 - "What is a language model?"
09:38 - Building the world's first feature store at Uber
11:27 - Language models and tokens, explained simply
14:19 - Where the observability insight came from
15:53 - Quantifying uncertainty and hallucinations
16:36 - The first customers and first use case
19:15 - How the product evolved from a data scientist tool
23:18 - Why ChatGPT changed everything for Galileo
23:57 - The enterprise AI adoption curve, 2021 to 2026
26:35 - Why they built the Luna model
28:32 - Turning LLM "writers" into "calculators"
28:51 - Attacking the latency problem
31:48 - Luna: the modeling and infrastructure innovation
33:09 - What evals are, and why they blew up
34:26 - The case for small language models
36:58 - What "general reasoning" really means
40:39 - AI usage is exploding — and why that matters
43:08 - Online vs offline: the "it worked on my machine" problem
44:33 - The evals flywheel and evals-driven development
46:56 - Galileo in a nutshell
47:39 - What real agents in production look like today
49:30 - A sales intelligence platform, powered by Galileo
50:47 - The agent control product
52:12 - Building GTM as a hardcore engineer from India
54:43 - Garbage in, garbage out: nailing the ICP
55:42 - How the pitch changed from customer 1 to 20
57:27 - Why Atin switched from CTO to CPO

-------------
India’s talent has built the world’s tech—now it’s time to lead it.

This mission goes beyond startups. It’s about shifting the center of gravity in global tech to include the brilliance rising from India.
What is Neon Fund?

We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that’s done it before.

Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we’re doing it all at Neon.
-------------
Check us out on:
Website: https://neon.fund/
Instagram: https://www.instagram.com/theneonshoww/
LinkedIn: https://www.linkedin.com/company/beneon/
Twitter: https://x.com/TheNeonShoww

Connect with Siddhartha on:
LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/
Twitter: https://x.com/siddharthaa7
-------------
This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.

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