why aren't all 17 resolved? a statement only gets an assessment when the public
record can support or contradict it. opinions and what-ifs never can, and 0 checkable
ones are still open, waiting for their date. predictions held up or didn't;
assertions are supported or contradicted. on every card:
▮▮▮▮▮ certainty ·
▮▮▮▮▮ debate potential. speakers are clickable
Assertion Not checkable as stated
Jain: Glean intentionally did not charge customers for its first two years
“We actually were not selling the product. We had no pricing. We had no plans to make revenue. That was an intentional decision we made that we were actually not even charged for our product for the first two years.”
Insight
Jain: Avoid using friends as early design partners; prioritize cold outreach instead
“I didn't actually go and, like, you know, hit my friends, you know, and say, like, hey, can you actually, you know, take this product and give me feedback? Because I felt like, you know, they'll all be very nice to me. And they will do it like, you know, even …”
Disclosure
Jain: Glean skipped TAM analysis entirely because the market did not exist
“Like, you know, sometimes we sort of talk to our team about it, so we didn't do any TAM analysis. Like, how do you do TAM? There's no product in the market. Nobody actually is even solving this problem.”
Insight
Jain: First-time founders optimize for entrepreneurial success; repeat founders focus on problems
“For a first time founder, like, you know, they're actually trying to, their goal is actually You know, succeed as an entrepreneur. They want to actually learn that, you know, that art. Sort of like, you know, it's personal in that sense. You know, for me, that…”
Disclosure
Jain: He avoided early feedback from business people to protect his idea
“In fact, the more people I would talk to, like, you know, especially people who are, Who have business acumen, like they would actually turn, turn me farther from this idea. So I actually chose not to talk to too many people.”
Disclosure
Goel: Scale AI, Rippling, and Glean are Maxima clients
“At many companies, which there are clients of ours, like Scale AI, Rippling, Glean, and many others, as you scale up,
The problem is exponentially.”
Opinion
Jain: Prior enterprise search efforts, including Google's, failed to satisfy users
“Well, historically, like this is not a new problem, like helping employees find information at work. So there have been companies, you know, Google had a product too, and, but nobody really solved it in a way where somebody liked the product, somebody actually…”
Insight
Jain: ChatGPT turned workplace search from a vitamin into a painkiller
“And this is where, you know, the transition happened from the vitamin to the painkiller. When people saw that if only I had something like ChatGPT inside my company or all of my company knowledge, people realized that, whoa, like that, no, this is something I …”
Disclosure
Jain: Early investors offered to back him but rejected Glean's product idea
“There were investors who would tell me like, you know, that they would back me, you know, because I've experienced building a company before, but they didn't want to back, you know, the idea that I was working on.”
Assertion Not checkable as stated
Jain: Software engineers spend one-third of their working time searching for information
“I know all these engineers, they're spending one third of their time just trying to find things.”
Insight
Jain: Enterprise search startups require heavy upfront R&D and roughly 20 engineers
“Search requires a lot of R&D, lots of technology to be built. So we wanted to build a team of about 20 people and divide it into, like, you know, three different areas, you know, of our technology stack.”
Insight
Jain: Founders should ignore the vitamin versus painkiller framework and just build
“And I think it's important, like it's important sometimes not to overanalyze and actually focus on the use end user and the problem and just go and solve it.”
Assertion Not checkable as stated
Jain: Glean has consistently grown its revenue by 3x to 4x year-over-year
“So we've been actually growing at about three to four X, like, every year in terms of multiplying our revenues.”
Assertion Supported
Srugo: Glean raised $200M at a valuation exceeding $2 billion
“And you just raised two hundred million dollars for that at, you know, over two billion dollar valuation.”
Disclosure
Jain: Glean only began charging when users averaged ten searches per day
“When we saw that it crossed 10 searches per day on average, that's when we knew that, well, look, now people are dependent on this product. They are actually getting value from it. And that's when we felt, you know, we were ready, you know, to charge for this …”
Assertion Not checkable as stated
Jain: Glean generated $3 million in revenue during its first sales year
“So, so getting, getting to like I think the first year of selling, like we did three million dollars, if I remember right now.”
Disclosure
Jain: Glean utilized large language models in its product from day one
“And actually, like, it's always been part of Glean. So even on day one our product, we're using LLMs.”