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I’ve been set a challenge this weekend. My gym is having a trivia night + talent show, and I am opening the show with one of my oldest party tricks, a rendition of Ice, Ice, Baby by Vanilla Ice. The image on the left is the outfit that just arrived from Amazon; on the right is the man himself (and yes, I plan to shave the speed stripes).

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INTERVIEW 🎙️

Keith Peiris, Co-Founder & CEO at Lightfield

Keith Peiris is the Co-Founder & CEO of Lightfield, an AI-native CRM that assembles itself from a company's email, calendar, and meetings instead of waiting for sales reps to fill in fields. Before Lightfield, Keith and his co-founder Henri Liriani met at Meta, where they worked on products used by billions, and in 2020 left to start Tome, an AI presentation tool incubated at Greylock with Reid Hoffman on the board. Tome became the fastest productivity product ever to reach a million users, grew to around 25 million, made the Forbes AI 50 in 2023 and 2024, and raised roughly $81M from Lightspeed, Coatue, Greylock, and others at a $300M valuation.

Then they killed it. After a year rebuilding in stealth, Keith and Liriani shut down a product with tens of millions of users to start over. The bet underneath Lightfield is bigger than software. That CRM, an $80B category with tens of millions of users and almost nobody who likes the product, is ready to be rebuilt for a world where LLMs, not humans, do most of the knowledge work. Dan Rose at Coatue, who led the original investment in Tome, backed the pivot. For founders, the pull here is less the product than the decision behind it. What it actually takes to walk away from a company that was working, sit in the negative momentum, and find conviction again from zero.

What was broken about CRM, and why attack a market most people think is solved?

There's nothing inherently broken about CRMs for the old jobs they were supposed to do. In the old world, a CRM was just a place where you wrote down things about your customers so you could serve them and take care of them better, and Salesforce and HubSpot are basically fine at that. But in the past couple of years, the world changed, in two very material ways. The first is that most knowledge work now will be done by LLMs instead of humans. And it turns out most knowledge work is people running businesses, trying to take care of their customers, sell to them, and serve them. There's a need in the world for context—a need to understand people, customers, and businesses better, so that LLMs can serve them.

That's been true for pretty much the entirety of software building. You have these big teams, engineering and sales, using different systems. One uses Linear or Jira, the other uses Salesforce, and they don't really talk to each other except when a manager shares a deck back and forth.

Something changed in the past few years that shook this. All of these new software companies are blurring the lines between those orgs, because the software is all kind of the same now: agents and harnesses and APIs. The value creation is actually in the last mile of integration, of tuning, of being there with the customer to make sure you're solving their problem. That has created an org in the middle. Some people call them ‘forward-deployed engineers’. It's actually the whole company working with customers. We’re changing the way we sell the product. Suddenly everyone needs to be tapped into the same customer truth. That's the opportunity. Salesforce certainly wasn't designed for forward-deployed engineers, scientists, marketers, computer scientists, and so on. We saw an opportunity to reimagine what CRM should be, both for LLMs to do work and for companies to be fully customer-deployed.

How is Lightfield different from the typical CRM on the market?

The first big difference is the latest-generation data model—CRM 3.0. It was all about rigid structures and fields. You had accounts, opportunities, and contacts, and those objects had fields on them, such as the location of the customer or the last thing they said. It was designed for humans to manually fill out those fields. We're designed to absorb everything about a customer. And when I say everything, I mean what they said, what they're doing in your product, the commercial value, what you're selling to them and how. We ingest it all by default, and the reps don't have to update them. You're building a corpus of data about each customer. That's the first foundational difference.

The second difference is that we give you nice tools to use all of that customer information, so you can do anything with it. You can use it to make a proposal, to write your email follow-ups, to find more customers like this one and reach out to them. We're giving you your customer truth and helping you play with it so you can actually do things with it.

What was the hardest part of starting Lightfield?

With Tome, we had a lot of momentum, but I learned that it’s very hard to overcome having the wrong idea. We had all the growth and all the capital and this brilliant team, but we just couldn't make good presentations for people doing serious work. That's what made us realize we actually needed to move to a different opportunity. Lightfield was the product the Tome team needed in order to be able to make great presentations, so it felt like a natural chapter two.

There were a bunch of things that were hard about pivoting a company that was already working. The first is that we went from 70 to six people, and those people who are left are all wondering if this thing is going to work out. The only way through that is to put blinders on, work as hard as you can, try to get some customers, and stay focused on the future, not the past. I actually talked to the CEO of Slack about this, one of the more famous pivot stories in history. I don't even think he remembers this, but one day I spoke to him on the phone and he said, “You need to have a team that's small enough to fit around a conference room table. Every day you need to get customers and talk about those customers, and just create momentum until people stop talking about the old thing.” That was the overcoming-the-negative-momentum part.

Then, for Lightfield in particular, there are some strange things. CRM is very big. It does a lot of things. I'd argue we're going through it really fast with AI coding and the way we built the system, but it's very hard to get someone to use your three-month-old CRM. As a founder, you build a better product and company with customers, so you almost have to come up with a trick to get people to use your early product so you can get to the next stage. We had a few tricks. When we were three months in, the first thing we used was our giant office space. We told people that if they were willing to use our CRM and give us training data, they could work out of our office. That's how we got our first five customers. We knew we were onto something when they stopped complaining about using us.

The next hardest part was getting our first hundred. I basically cold-emailed all of these Y Combinator founders, hosted events, and went zero to one there. And then, maybe the hardest thing about CRM is that it's very easy to build a simple CRM that looks like it's going to work. But it's a very painful engineering challenge to make a CRM work for a million records, with all of this unstructured data, with clean APIs. We needed to hire good folks and afford ourselves the time to build all of that.

What's your North Star metric, and how do you improve it?

I think there are two types of metrics. There's breadth, and there's depth. I'm old enough in my founder journey to know that as long as you have depth, you can get more breadth. To put it another way, if our customers use our product all the time, they love the work it produces, they reference it, they're really happy, then I know I can always pay to get more customers. We can always hire more salespeople, and we can always do more marketing.

So the first thing I look at every morning is how much time our customers are spending on the platform, how many agent actions they’re running, how often they’re accepting the work we create, and how far we’re spreading within the company. The best version of Lightfield is when we're wall to wall—the engineers are using it, support is using it, sales is using it. So I'm always watching the spread of Lightfield inside a company to see whether we're working toward that vision, or whether we're just a thing a salesperson uses a couple of times a day. Assuming all of that looks good, then I'm obviously looking at how we get bigger companies to be very happy on the platform.

How would an engineer use Lightfield?

There are a couple of ways. The most obvious one is the handoff from sales to engineering. We just got this big customer, so we're going to have to do a bunch of work for them. It's the whole ‘let me ramp up on this customer’. Understand what they need, make sure you show up to their next meeting prepared, and influence the roadmap.

The second one is that most of the companies we serve don't actually have product managers. It's the engineers who run the products and build. To do that, you need a sense of the priority of the roadmap, and you want some scientific measurement of how many people have actually asked for this feature. I know the sales guy was very loud about us having to build feature X, but how many people have actually asked for it, what's the commercial value, and what's the why behind the ask is really helpful for the roadmap prioritization exercise.

Related to that, when you build a feature, it's hard to know whether it's actually going to solve the problem for the customer, or whether you just built an unserviceable version of it.

What does your week look like as CEO?

It's funny, I have a very reductive view of what a CEO should do, which is that it's the CEO's job to work on the rate-limiting step of the company until it's no longer the rate-limiting step, and then move to the new one. Every Sunday night I'll write down the three biggest problems of the company. Sometimes it's engineering hiring, sometimes it's ramping up sales, sometimes it's positioning in the market, sometimes it's pricing. Then I'll send it to my core team and let them know that I'm going to pick off these things this week and go really deep, and ask if they need help with anything else. Then I'll basically be an individual contributor on that thing until it's good.

Right now my biggest focus is on sales and customer success. The product and engineering team has a ton of velocity, and we actually have way more demo bookings and pipeline than AEs. So my job is to help us find a sales leader, and take what’s worked well for us and help it scale.

Even though we’ve started to build out a commercial team, I still like to take a set of customers and work with them through the entire customer journey, from the first call to post-sales implementation. It helps me stay close to what’s actually happening in the field and gives me firsthand experience that supplements the context I get from Lightfield on what’s happening in our market. I get a lot of satisfaction watching customers go from their first ‘aha’ moment with Lightfield during the sales process, to transforming how their company operates after we stand them up on our platform.

So that’s where 80% of my time goes. I'll spend 20% of my time making sure the other trains are running. I've found that the process meetings, where I go in and watch people do standup, don't really work for me. I prefer to do stochastic sampling, where I'll just Slack a couple of people on each team and ask how things are going and whether they think something should change, and then react off of that.

How do you approach goal setting and product cadences?

We plan about six months out in terms of revenue. We're trying to 10x revenue in the second half of this year. To work backward from that, some things need to be true. The obvious one is that now we need to be able to support a Series C company being very happy in Lightfield, and we need some amount of commercial capacity. So in my head, I know we need to ramp up to 10 reps and have a certain level of product functionality by the end of six months. That part is somewhat rigid. But on a day-to-day and week-to-week basis, we operate with continuous planning. We have one engineering and product roadmap and then a separate go-to-market roadmap, all in Linear. Every day we'll look at it and ask ourselves if it needs to change, and every week we'll have a conscious conversation.

We have a Friday afternoon meeting called ‘roadmapping’, where we check if we need to make any radical changes for next week. We've found that works really well. Be somewhat rigid on a six-month-to-one-year time horizon of where you want to be, but be continuously shifting and adapting day to day, week to week.

What do you look for when hiring? Do you have any unique go-to’s?

As a CEO, you constantly need to hire people into roles where you have low task maturity. I would hope I'm worse than the marketer or the infrastructure leader I'm about to hire. There are some things I do that are pretty conventional. I like hiring people who have intentionality in their career, because if you've made intentional career steps, that suggests to me you'll be intentional in your planning and your autonomy with us. So usually I'll ask someone to tell me their life story, and look for intentionality and good reason from one step to the next.

The other thing I've found is that right now I'm not in a place where I can create lots of structure for my team, because I'm jumping from one problem to the other each week. So I'm looking for folks who can bring structure and order to chaos. The best way to test for that is having a working session in the interview. I do a 90-minute version of reviewing the current state of this domain, the problems we face, the things I don't like, and the threats and opportunities. Then I work with the candidate on two things. First, can we steer this toward truth? The worst thing at a startup is when you have people managing process instead of outcomes, so I want to see us get to ground truth and actually problem-solve. Second, can we steer it toward removing entropy and land on a reasonable plan by the end? That deep situational problem-solving interview has been the best one for me. I don't try to do any posturing. I actually try to be the worst version of me, chaotic and all over the place, and see if this person can turn it into something good.

At our stage, we're a little under 40 people now, and we don't hire anyone who acts like an exec. We try to hire people who are still in the work. My favorite people are the ones who have been really good at their function and are now looking for a chance to run the whole function. Great at craft versus professional manager. For the most part, I hire people for whom Lightfield could be the pinnacle of their career, where they're going to be irrationally bought into making the company work, because making the company work could mean everything to them, as opposed to just being another notch on their belt.

How are you thinking about AI operationally across the company?

The forcing function for AI inside Lightfield is that we're not trying to build a 10,000-person company. We have the aspiration of having more revenue and more growth than Salesforce, but we don't want to be Salesforce-sized. I want this company to be 500 people, not 10k. If you impose those headcount limitations on the team but you enable technology, you start to see whether the incentives can create the outcomes you're looking for. We're almost 40 people, and we still don't have a recruiter. That's one of the sources of pressure. If it's really easy to hire people, you'll just hire people to solve your problems. If it's hard to hire people, you end up coming up with creative solutions.

Inside product and engineering, it's fairly clear. We've moved everything to a mono repository. We put product specs into it so Claude can understand them, we deploy agents everywhere, and our team burns lots of tokens. Outside of product and engineering, it's been more challenging, and really interesting. It turns out we can get pretty far with AI. For example, maybe I don’t really need a head of finance if my chief of staff with a finance background can get really far using spreadsheets and context.

In addition, we record all of our internal meetings and dump them into Lightfield, so it has a knowledge base of everything we've ever discussed and everything we've ever decided. It turns out that if Lightfield has all of that context, it can do some good work for you. We fed a lot of that context into Paraform, and we're getting good candidates from it. Because of all that, we have about five people outside of engineering and product, and we've been able to get really far without any more.

How do you use AI personally?

I think this is true for a lot of CEOs. The thing that hurts me most is asking an employee for something and being told it'll take weeks when you know it could take hours. I'm realizing I can have a hero complex because of AI, in that we'll all ship features to the codebase instead of begging engineers to do them, and that's been a big unlock. I'm not super technical anymore, but we still push things to prod using Cursor.

The other thing I've found is a strange one. One of the hardest parts of my role is making sure I'm operating from reality, because everyone tells you a different version of what you want to hear. Employees sometimes overrepresent how good things are, so they look good. Investors have a different view that isn't entirely aligned with you. I've found it really useful to have a mirror to double-check if stuff is sensible or believable. Planning different scenarios has been a big unlock for me. Being able to accurately forecast where your business goes is one of the hardest problems, because it's not just the numbers. It's about having the right customers, building the right thing, considering the risks of competition, and more. I'm essentially trying to build a world model of our company so I can forecast better and act differently.

How do you get the best out of yourself?

I find there's just too much noise in tech right now. I used to read everything on X and listen to every founder podcast, and now I never log into that stuff, and I don't listen to podcasts. I just read books, and I find I have a clearer, simpler mind as a result. You can either be in a mode of consuming content or creating content, and I find it's hard to be creating when you're consuming all of this noise. So right now I'm in a state of creation, where I've shut that stuff off and I just keep going.

Related to that, I try to work out every other day. I have a rule with my wife where we go to sleep at the same time every night, no matter what we're doing, to force the eight hours. When I was fundraising, I was taking a magnesium supplement, because it turns out that when you're stressed out, that stuff helps. And because I'm in California, I'll go on long bike rides to try to gain some perspective. Another strange thing is that I used to play competitive chess in high school, and I find that when my mind is running, I just get my butt kicked on chess.com. It's a good barometer. If I open it up and I just get stepped on, that's a good sign I need to focus on peace.

Extra reading

• Building the CRM that works for you - May, 2026

• The founder's guide to evaluating an AI CRM - January, 2026

• Why we built Lightfield - November, 2025

And that’s it! You can follow Keith on LinkedIn or check out Lightfield on their website to keep up with what they’re building!

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TOOLS WE RECOMMEND 🛠️

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