Micro1 gave up a growing recruiting business to focus on data

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 16:13

   Because, like, early 2024, it's still the very beginning of, like, Chachi BT was released a few months prior. Like, people are just starting to really, like, use LLM. Yeah, yeah. So this was the time where it was sort of late 2023, early 2024, where we got a really massive customer that was actually a data company that is now a competitor that basically requested hundreds of engineers to hire from us in like a matter of a couple of weeks.

2. 16:47

   And we realized that this is very quickly our largest customer by far. and so we kind of looked into this market we're like you know we're trying to figure out what they're doing with all these engineers and essentially uh the the focus at that point uh or what was happening is we were transitioning from the journalist data and you know journalist data sets and environments to to to broadly this like expert level data and the first domain that this was happening in one of the first domains but but the first kind of big one was was coding Um, and, and that's why the, you know, the focus was a bunch of engineering hires.

3. 17:23

   Um, and today that that's, that's still a very important domain. And in fact, it's one that's growing really fast as models get better. But now there's, you know, experts and pipelines across, across the board, finance, medical, legal, uh, and, and, and, you know, many other domains. At that time, by the way, when you pivoted it, did it feel like a risky decision or it felt like you felt confident in this sort of like obvious thing?

4. 17:46

   because it's you know you have a team of people working on something you raise from investors like it's already a set company so I actually think it takes a lot of um it takes something to be like okay we're going in this other direction now because we're still young enough we're like we want to be big and this is how we get there yeah no it wasn't easy at all and and actually I um we should have done it earlier and you know obviously it's always clear that you I should do it earlier when something works, but we actually took a little bit of time.

5. 18:16

   We sort of had this like transition period where it was like a couple of quarters, frankly, where we were doing some work with data, but we still had our AI recruiter. We still had our talent marketplace, which startups would hire from. And it took us a while to, it took us a few months to essentially say, okay, we're going all in on data. And when we did that, we we essentially made the decision to slowly kind of shut down and delete the revenue that we had before from this like version one which was like also growing it was millions of dollars in run rate and it's it's not an easy thing like for the team to be like we're just like a completely new company now and uh and of course we we used a lot of the base that we had built in terms of the software in terms of the team etc uh but but it was a pretty massive shift so it was uh it was

6. 19:07

   really difficult for the company but these are these are the moments where if you have sort of like a very not obvious conviction in something you have to take it like you felt it inside like yeah exactly it's like a huge hugely outlier decision and it sounds crazy um but but that's like what results in like the crazy outcomes and was the customer pissed when there's not