Lightfield创始人复盘：因不热爱产品而硬转向

Three out of our five founding members came from Facebook. Building a revenue team is a very rich problem set. It's something that everyone cares about. It could always be done better.

What's the most exciting thing someone's doing with Lightfield today? This company Power, they have this marketplace where they're aggregating folks that have various illnesses and complications that are looking for frontier treatment. So, they've modeled all of this in Lightfield and Lightfield actually helped someone with Alzheimer's find frontier treatment within days. Is there anything that you've done differently in this kind of AI era?

As a CRM company in a red ocean space, we have to be an expansion company. If we can help you completely model your business and your customer reality, then the rest will be easy.

What would be the one piece of advice that you'd go back and give yourself if you are just starting again? Um, welcome back to the A6Z podcast. I'm Joe Schmidt. I'm joined by my partner, Alex Rmpelle, and Keith Paris. Keith is the CEO at Lifefield. Lifefield just raised a $47 million series A led by us and they're building a business world model. A business world model turns customer emails, calls, and meetings into a record that AI agents can use to get work done.

We'll explore how Keith pivoted, which is very interesting to Lightfield. How they built the initial product and what customers can do with it. Keith, thanks for joining us.

Excited to be here.

Yeah, maybe we'll start just going back to the tome journey and how you got to light field. very atypical journey. You got two products now to explosive scale. Um tell us a little bit about uh that that experience and how you ended up at Lifefield.

We started to uh you know mostly because we were consumer people and we thought like LLMs were going to change the way people communicate and we were working on like selfie design you know at Instagram and Messenger and we decided to to go into the the storytelling of ideas. We got this product out to launch around the time of GBT3.

Yeah. And what was the and tell us a little bit about the product too. So it was a it was a presentation product where you could use uh GPT uh to generate presentations and generate pages and and so forth. And we launched it around the same time as chat GPT and uh we just got explosive growth. Um we got you know 2 million users a month. Um you know uh people were uh lining up when we didn't have enough inference to uh you know to to support them.

Wow. Oh my gosh. And so you got that to amazing scale. You then decided to stop and completely hard pivot.

What was that decision like? How did you make that choice? Why?

Yeah.

So I would say there are a lot of metrics behind it, but you know deep down I think at an instinctual level. Um none of us like the product which is which is kind of a funny thing to say. Like I think at the end of the day if you're a a founder you have to like love the product that you're building and you have to be excited for your customers to use it. And um we just couldn't for the life of us make good presentations.

Wow.

You know uh and what what I mean by that is you know we could never we could not see the path of like a high quality discerning presentation maker using this tool. Yeah. In an indispensable way. We couldn't see you know people like yourselves using it for memos. We couldn't see people using it in in like investment banking or consulting. Um, we just thought that the technology constrained us to being a tool for individuals and students.

So interesting. Okay. So you go from AI presentations to

nothing. And so how did you make the choice of what to

maybe if if I can rewind a little bit. I mean sometimes you get to this point and you're like oh well if the technology kind of continues advancing then it will be good enough.

Yeah.

But that's also a little bit of a danger. I think the uh it's calledium uh is is the but how did you decide I mean this was probably the question that you were getting at but like why not just wait it out for the technology to get better

because I mean the leap between GPT3 and GPT6 with Astra is extraordinary

but obviously if you're burning money and everything you don't have the luxury of waiting but I guess how did you think about like just the shape of the curve and why not wait out the curve?

Yeah it's a good question. So we we we definitely thought about let's shrink the team and wait it out, you know, because we were seeing 3.5 to four and and seeing the leaps being made. But I think the biggest issue was that the model just didn't have enough context to to really understand the presenter, the audience, the relationship between the presenter and the audience and like no amount of general reasoning gets you past that.

Um, so we were like, this is a going to be a best a great tool for a oneshot pie in the sky presentation and we just couldn't figure out how to turn that into something that we were excited about.

Yeah. How did you think about the problems that you wanted to attack next? I think the, you know, the hardest part of what you just said and the most painful part is none of us liked the product. Like

that's hard if that's your entire life. [laughter]

How did you decide what was the product you actually wanted to build? What was that process like? So I think we we had a lot of conversations internally about how wait a minute why did we even build this company? We built this company because we wanted to help you know uh professionals tell expert stories you know hard stories. So we're like let's see if we can find the B2B use case.

So we um we we sort of looked in our user base. We had 25 million users or something and we found that the the the uh the B2B users were sales and marketing.

Yep.

Um so we reached out to them. We went and got 12 pilots uh from call it like 500,000 person companies around here and we're like hey we'll we'll do this for free. We'll just we'll we'll we'll do great presentations for you and let's see where it goes. So we ended up being used by a couple of sales teams. And um at first we came in with we'll make your new business decks or we'll make your proposals and we're like wait a minute while you're here can can you do other things?

Can you guys do some research? could you help us qualify leads? Could you help us like um understand companies for expansion? And um

at that point we were like sure, you know, let's just follow the heat, see what happens. I I think I think what makes early stage founders good at this is that you you sort of have no priors. You're you're willing to ignore the thing you built. And we were like, let's just follow this trail and see where it goes. Um, and then the uh the first thing we asked was like, "Oh, just give us access to your context box," which at the time I thought was Salesforce.

So, we're like, "Great. Give us access to your CRM, your call recorder, your data warehouse, more and then we'll figure out how to do this work for you."

Then we realized actually the hardest part of doing this work was actually um making sense of all of the data across all of these disparate systems, you know, and it was sort of uh it was incomplete. it was uh conflicting. You know what what the the call recorder often had a different view of reality than the CRM. Actually the the work required to reorganize it felt like the most important work. M

um and I I think through that we we started to realize, wait a minute, maybe this is the more interesting problem to solve,

which is that if you can reorganize reality for a company in a way that machines can understand and also for humans to understand, um that feels like a way more interesting and enduring company than the one that we're on right now.

Yeah. When did you know that you were on to something with the new product? So there there's a a little bit of discontinuity. W