The Changelog: Software Development, Open Source - From GitLab to Kilo Code (Interview)

Episode Date: January 7, 2026

We're joined by Sid Sijbrandij, founder of GitLab who led the all-in-one coding platform all the way to IPO. In late 2022, Sid discovered that he had bone cancer. That started a journey he's been on ever since... a journey that he shares with us in great detail. Along the way, Sid continued founding companies including Kilo Code, an all-in-one agentic engineering platform, which he also tells us all about.

Welcome to the change log, where we have deep technical conversations with the hackers, leaders, and innovators of the software world. I'm Jared Santo. On this episode, Adam and I are joined by Sid Sabrandage, founder of GitLab, who led the all in one coding platform all the way to IPO. In late 2022, Sid discovered that he had bone cancer. That started a journey he's been on ever since, a journey that. he shares with us in detail. Along the way, Sid continued founding companies, including KiloCode, an all-in-one agentic engineering platform, which he also tells us all about. But first, a big thank you to our partners at fly.io, the platform for devs who just want to ship.

Build fast, run any code fearlessly at fly.io. Okay, SIDS-Brandage, back on the changelog. Let's do it. Well, friends, I'm here again with a good friend of mine, Kyle Goldbrath, co-founder and CEO of depot.dev. Slow builds suck. Depot knows it. Kyle, tell me, how do you go about making builds faster? What's the secret?

When it comes to optimizing build times to drive build times to zero, you really have to take a step back and think about the core components that make up a build. You have your CPUs, you have your networks, you have your disks. All of that comes into play when you're talking about reducing build. time. And so some of the things that we do at Depot, we're always running on the latest generation for ARM CPUs and AMD CPUs from Amazon. Those in general are anywhere between 30 and 40% faster than GitHub's own hosted runners. And then we do a lot of cash tricks, both for way back in the early days when we first started Depot, we focused on container image builds. But now we're

doing the same types of cash tricks inside of GitHub actions, where we essentially multiplex, uploads and downloads of GitHub Actions cache inside of our runners so that we're going directly to blob storage with as high of throughput as humanly possible. We do other things inside of a GitHub Actions runner like we cordoned off portions of memory to act as disk so that any kind of integration tests that you're doing inside of CI that's doing a lot of operations to disk, think like you're testing database migrations in CI. By using RAM disks instead inside of the runner, it's not going to a physical drive, it's going to memory.

that's orders of magnitude faster. The other part of build performance is the stuff that's not the tech side of it. It's the observability side of it, is you can't actually make a build faster if you don't know where it should be faster. And we look for patterns and commonalities across customers, and that's what drives our product roadmap. This is the next thing we'll start optimizing for. Okay.

So when you build with Depot, you're getting this. You're getting the essential goodness of relentless pursuit of very, very important. very very fast builds near zero speed builds and that's cool kyle and his team are relentless on this pursuit you should use them depot.dev free to start check it out one-liner change in your get-up actions depot dot dev Well, friends, we're back with a good friend of ours. It's been, Sid, way too long. Way too long, for sure.

Way too long. The last time we talked to you, the last time I talked to you, at least, was when you were leading GitLab to IPO. This is pre-IPO. This is in 2022. It was speculative. That was obviously the North Star for you. You've accomplished that mission. you've had a cancer journey,

you've had a investor journey, you've had the American Dream journey, and kind of back again in a way. So welcome back to the show. It's been way too long, good to see it again. My pleasure. Thanks for having me. Looking forward to this. When we look at your story from,

you know, some would say, you know, this shadow of GitHub from way back in the day to now, how do you personally reflect on your journey? I would say in tech, but also as a CEO, as just a normal person, as an investor. How do you reflect on this long journey of yours? Well, it's been amazing kind of living the American dream. 2015, I came to the U.S.

We raised money for GitLab, and we set our sides and growing a company, becoming a public company. And then six years later, we took a public, which was amazing. and we're very fortunate to... Six years to public, huh? Yeah. That's the speed. That speed.

And you were very much a leader, too, with the way you opened the company, your open docs, a lot of the ways you hired, the ways that you showcased culture. A lot of that was even not so much not in public, but you were very much a star of that. And then you were also a company that IPO. That seems like maybe not the way it should be done, but it's obviously the way you did do it. Yeah, we try to lead their company with a ton of transparency, and we believe that helped us be an all-remote company, but at the same time being super on the same page. And it's paid its dividends, both in coordinating us, hiring great people, but also getting customers excited about the company itself and how we partner. Are you still involved in any capacity with GoodLab?

Yeah, for sure. I stepped down as exec chair last year or stepped down as CEO and now became an exec chair which means that I still am an employee of the company

so I still have two engineers reporting to me and we're taking on projects that I'm super excited about and right now we're working on adding observability into GitLab so really really exciting to work on that

we're done so when you left git lab as CEO you're CEO correct that's what you stepped down from yep correct position it wasn't necessarily because you were done or because you were you've done your thing and you're ready to you know get a mojito and go to the island you actually had a health problem a major health problem i mean a health crisis in many ways around the end of 2020 and you've been on quite a separate journey which is amazing to me some of the details that you've gone through in order to be here today, we're very happy that you are here today. Can you unpack a little bit of what you've been through in the last three years, four years with regards to your health and the journey you've been on to fight cancer?

Yeah, for sure. So end of 22, one year after the IPO, I discovered I had bone cancer, a six centimeter tumor grown from my spine. and we had to do surgery really quickly. I was in a lot of pain. We removed the vertebrae and most of the cancer and did a spinal fusion with a titanium frame. We did radiation with chemo.

And I did my first single patient IND. Since 2017, I've invested in one other Y Combinator company. And over time, that guy became my best friend, his wife became my wife's best friend. And every time he was fundraising, the investors wouldn't put any money in. And every time I said, this doesn't make any sense to me that they're reluctant to put money in.

I'll finance the company. So over time, I became his biggest investor. And what he's doing is combining drugs with binders through click chemistry, allowing you to target different parts of the body. And when I became so very sick, he made a, we asked for an exception to treat me with his drug. And we got that exception. And we did all the treatments.

And then two years later, in 24, the cancer started growing again. And the doctor said, you're done with standard of care. There's no more treatment we have for you. Maybe there's a trial somewhere. And I started looking around. I have a weird HLA type, which disqualified me from a few trials. And I have a bone cancer, osteosarcomas, kind of a rarer disease. So there wasn't anything for me.

And it was my oh, shit, moment. Like, oh, if I don't move, I'm going to be that soon. I had to step down as a CEO because I needed to focus my full attention on this. I started talking to anyone traveling anywhere. I went to the medical conferences. I went as far as China to get scans. And I started doing maximal diagnostics, making my own treatments,

doing treatments in parallel, and trying to scale that for other people. And so that's been the journey I've been on over this last year. And it's been a lot of ups and downs, but also extremely interesting. And I've learned a lot, but I've also think that there's a lot of things

that could be better. And I'm trying to change those to be better and making the path I've been on easier for other people to follow. I understand the reasoning for parallel directions or testings because you only have so much time before it's too late. And so I totally understand that. It seems like as a software guy,

you want to try to isolate and do one thing at a time and then see if it works. and then do the next thing versus having multiple factors. I suppose if it's working, it doesn't really matter which of the five or six is working if it's working. But certainly for reproducibility and for helping others, you do want to be able to have some sort of result that you can come out of it. So tell me about the parallel side and some of the trials of that introduces and how

you're maybe solving those problems as you go. Yeah. If you want to be able to reproduce, you need to isolate. the change. So when I started doing parallel treatments, one doctor told me to my face, but what if it works? We won't know what would have cured you. And then I let the doctor know that I wasn't interested in finding what cured me. I was interested in getting cured. That's right. I'm not research, but I'm a real person. That's right. The combination of treatments, there's very little incentive for pharma companies to kind of spend a billion dollars. It's now

a billion dollars for a successful trial to spend a billion dollars for an approved medicine to research a combination of drugs so there's no incentives so all you see on the market are these drugs taken in isolation and doctors are reluctant to combine them because it's never been done before but if you look at the first principles you can say hey these treatments are probably okay to combine what you don't want to do is have like combined two things that both hit the kidneys because your kidneys are going to be overcapacity, and that's not good.

So every time we do, we combine treatments, I have, for example, a pathologist in my tumor board to look at like, hey, can we combine these things? And we also look at my own markup, including genetics, but also histochemistry, where you kind of, we color slides in, and we do multiplexing so we can color multiple things. And for example, I told you,

I went to China three months ago. And I did that to get the first B7H3 scan available to me. And because of what we learned there, we were able to kind of change the development of one of the drugs I'm developing to remedy what we saw. We saw in China that I have higher B7H3 expression in the liver than any one of the 20 patients they saw before. and we decided to combine that medicine

with something that's rarely expressed in the liver. So it's not going to destroy my liver going forward. So you've got to be kind of, what I'm trying to do is kind of be first principles about it instead of kind of relying on evidence for the ability to combine because that evidence, it doesn't exist because no one has the incentive to do that. Right.

And most people die because they, not because they've run out of treatment, they run out of time. So why China, is it a technical thing? Is it a regulatory thing here? There's just more advanced in certain areas. Like, why do you have to go all the way there for this particular test? Yeah, so to be clear, most of my treatments and most of my tests are happening in the U.S.,

but Europe and China are also part of it. And what's remarkable about China, I found remarkable that I was the first, it was my first time traveling to that hospital. When in two hours, I was checked in. in, they formulated the diagnostic scan ingredients, they gave me the scan, they printed the results, they talked me through it, and I was outside again. I've not seen that speed in the US. One other thing that's happening is that these hospitals have a lot of patients. So instead of running a trial at 10 different hospitals, where it's a lot of work to combine all these investigators and to train

all of them. You can run it in a single hospital, the same hospital where the investigator is at, the researcher is at. So they have a much higher speed of running trials. And we're starting to see a giant shift in the literature of trying to do more trials and making more medicines. So where do you stand? How is your health? How are you feeling? How are you doing? What's the future look like? Yeah. I'm doing well. Right now we cannot detect my cancer. So that's great. It's a really good spot. That is great. Yeah. That's a great spot to me.

Compared to a year ago where it was growing and we had zero treatments. Today I have kind of a therapeutic ladder as in like if things got worse, we'll escalate the medicine and there's 30 medicines on it. So like we have options now. And I'm continuing the development of 10 different drugs and diagnostics that make a lot of. a sense for me to, to have. I've also started in the meantime six companies to scale treatments for other people, treatments that I've done, but also treatments. I've not done, but just technologies we came across that we thought are, and they're invested in. Yeah. Do you know what has made your cancer undetectable then? Do you, I know that you weren't being that research lab before, that

research right before, but like how do you, do you, have you pinpoint of what may have worked with these 10 different medicines you're developing. Yeah, for sure. I might have been one of the first people to do single cell sequencing as an individual patient outside of the context of a trial. It's kind of a strange name because you're not sequencing a single cell. You're sequencing thousands of cells, but you're kind of, you're able to see the genetic markup of each cell, and you're able to see what the, what the tumor is looking at.

looking like which cells are in there, how do they behave and what's their genetic markup. It's an incredible powerful technology. We compared that to an atlas of kind of what bone marrow should look like. We zoomed in, we were able to kind of zoom in on the cancer cells. And one thing we noticed is that they had a lot of fibroblast. Fibroblast is kind of scar tissue. And we were aware of a treatment in Germany, an experimental treatment that has a FAP binder that binds to fibroblast, and then on the other side, you put a radioactive element,

lutecium or actinium. And it did two treatments there with incredibly good results. First of all, no side effects. I couldn't detect any. And we saw 60% necrosis and 20% shrinkage, which considering it was only two treatments, that was a great result. And my cancer is in my back near my spinal cord. Because of the shrinkage, it detached from the spinal cord, allowing a really talented surgeon to go in and go after it and remove most of it surgically, which wasn't possible before. And this is because it would attack the scar tissue. What was the name for the scar tissue? Is it because it, you were able to pinpoint that and allow it to detach from the scar tissue?

Yeah. So what we were able to do, because of the scar tissue, because of the scar tissue, it was, of the scar tissue, we had a binder for that, called FAP, or this experimental treatment in Germany had that, and you combine the binder with the radioactive stuff. So a lot of drugs, you just give them to the entire body, like a standard chemo drug. It's devastating. This drug is also like a really nasty thing, like Lutetium is like radiating you from the inside. I was like 10 times as radioactive as an airplane at altitude from the outside, let alone what was happening inside of me. Oh, wow.

They have to, like, they keep you in isolation because you can't be around people. You can be around people. But because it was on this FAP binder, it targeted my tumor especially. And there's also a little bit of risk for, like, for example, your loss of taste and smell, but I had non-side effects. there. So it was, it very specifically bound to, to the tumor tissue, which is just amazing. Like

most, most cancer treats are way worse. And, yeah, enabling surgery was a, was a big deal. Like, if it's right up against the dura, your spinal cord, that's not great. But in this case, it was detached from there. Because, it's amazing. Yeah, it was really great. How long were you radioactive, radioactive? You're radioactive for kind of a week, but only two days in isolation and then you get a letter and then you walk at the airport.

Maybe you've seen those things in the U.S. now. You walk into the airport and there's kind of a black thing. I guess what? Beep, beep, beep. We once had three people with scanners around us and they

had to call kind of Washington because their sensors were showing plutonium which would not be good. Wow. But it was, luckily, it was the Lutetium after all. But they had to have a scientist in Washington. You were a person of extreme interest there for a little bit. Yeah, they, as soon as they knew it was me and not my luggage, they were super chill about.

They were super chill. That's hilarious. Wow. Can you talk about the type of cancer, the sarcoma? There's like 70 different types. And I asked this question because I have a dear friend. of me and my wife's who passed away probably 14 years ago and she had sarcoma in her lungs she was actually studying in Houston which is a very popular place for cancer research at least here

in the States is one of the capitals of cancer research and she was studying to become a doctor in this field and actually not through the not through her lab time or anything like that but she came to actually get the cancer I don't know how to to describe getting cancer, if it just develops her, if it grows, or what actually gives the cancer to you. But she developed the same sarcoma cancer that she was studying, and it was just really, really bizarre. Yeah, quite bizarre.

Like there was no real connection there. The same doctor that she was studying under was her doctor during her process. She obviously ended up passing away. It was about a year, maybe a year-ish, devastating to our life and our friends. but can you speak to the sarcoma type cancer and what that type of cancer does or does not do? Do you know much about? Obviously, you probably do, but like there's 70 different types. And I'm not even that familiar except for I knows that she had sarcoma cancer.

And you mentioned you have a version of as well. Yeah. Like I'm not a doctor. This is no medical advice. I know very little about that type of sarcoma. I do know sarcomas are genetically pretty diverse. So there's a lot more studying to be done. For example, the standard genetic reports showed like TFE3 amplification, but when we really started digging, it wasn't true that wasn't the driver at all.

So because of all that copying of the genes, it's harder to analyze, but there's also more kind of special things about it that allow you to do more targeting. Yeah, and you mentioned Houston. Big fan, Houston Methodist is especially great here. And I know very little about lung sarcoa. What I do know is that for bone cancer, the biggest risk is that it spreads to the lungs. If you have these cells going on the loose, the first place that likely end up are your lungs. also because your lungs are very tiny vessels, so they get trapped, the cells get trapped there

the fastest, but also because it's kind of a similar cancer that can grow there. So we were watching for that. And at a certain point, I did a kind of a regular pet scan where you look for activity that is out of the ordinary. And I remember vividly,

I was talking with my direct reports and I get a message, a text from my GP, and he says, it's positive, not subtle. I'm like, it's positive, okay, great. And I'm like, oh, no, positive in a medical setting. That means something else. It means positive for cancer. And not subtle, that sounds bad.

And I opened up the report. And I read my death sentence. It spread to 50 sites in my lungs. My lungs were lighting up like a Christmas tree. And the radiologist gave an undifferentiated diagnosis. Definitely cancer spread to the lungs. Way metastatic. Fifty places means like surgical, your host.

There's no way to do it with surgery. And so worked out at a really. room, collected my thoughts for 10 minutes, called my wife, called in my CFO, CLO. I think this is the situation. What do we do? We're going to tell or not. Decided to tell. And we all took a long walk together. I started to my doctor started coming in. So sorry for you. So sorry for you. So sorry for you. Then this, the last doctor, basically, to chime in was like, yeah, 60% chances isn't cancer. Say what? I give a call, like, Chala, what do you say?

Right now? Yeah. He's like, yeah, the lymph node pattern, how it spreads, this doesn't seem like lung cancer to me. And this is a guy who've run the most osteosarcoma trials or the most sarcoma trials in the nation. so he he might not he's he's just seen so many patients and seen so many people who this happened to so okay so i i went to now i was a dog with a bone and within a few hours we cleared it up that this this was the remnants of covid it wasn't because we were so afraid of this happening including the radiologist everyone had a bit of tunnel vision but it quite the experience to

to tell your team you're you're gonna yeah and then the exact opposite when you're like you know what they made a mistake it was yeah just a mistake and not not because that's that's exactly like it went to her lungs and brain quickly very very quickly there's the two places that tends to spread so it may begin lower in your liver and in your back like you were but it spreads quickly to other places and it sort of takes you quickly if it if it's not if it's not COVID if it's something different right probably the happiest COVID diagnosis of all time wasn't yeah thank God it's COVID for sure I wasn't super happy about the diagnosis though that really just and I maybe not going to be friends yeah I mean obviously they put you through

turmoil and terrible things I had a nowhere near as serious and yet relatable diagnosis with my knee when I was told that I had torn my ACL and I would never play basketball again by a physician's assistant. And then the actual knee doctor came in. He's like, no, you're good. He's like, I'm shortening the story. But I had like 15 minutes of like, oh, I love basketball. Like my whole life changes in small ways. Yours obviously in a huge way. But then him being like, no, she didn't understand this thing. And she messed up and it's not as bad as she thought it was. And I was like let's fire her or something you know and these things are not trivial to diagnose you know yeah it's not easy so it's undetectable in this in this moment you just shared this dramatic story arc

that you've gone through you're recalling it here in this moment this podcast is the expectation at this point with you and your medical staff that it's not going to come back or it's just undetectable and you're still actively trying to just work on it or treat it like what is the current status of how you're dealing with it? Is it just gone for now and wait or how are you handling things? Yeah, we assume that it's not gone and the only reason it'd be gone. We know that the surgery didn't cure it that they left positive, so-called positive margins. So they left cancer. The only thing that was remarkable when we, the cancer we've removed, we were able to flesh-free some of it, which is amazing.

For people with cancer, it's way better to flesh-free stuff because it allows you to do many, many more diagnosis on it later than if you do the standard, which is FFPE, which is like it preserves it, but it precludes you from doing a ton of tests. So if you want to have an active role in your treatment, you've got to convince the hospital to do flesh-free, of it, so that you preserve optionality to run these diagnostics later. And what we saw was that the T-cell infiltration went up a lot.

It went up from 20% to 90%. So the place was buzzing with T-cells, which is a good thing. And we think that is a combination of the two checkpoint inhibitors that I'm taking that kind of unleash your immune system. and one experimental treatment that is an oncolidic virus so like a modified common cold virus that drops the TGF beta

and the TGF beta is something the cancer uses to hide from the immune system and it kind of tears away that invisibility cloak. So that's good news. We don't super think that that's curative but I'm gearing up in two weeks to take an MRI vaccine and that's like a 50-50 of curative.

But there's a reason we have like 10 drugs in the pipeline. It's where we're trying to cover all our bases and rather have a drug too many than one too few. Yeah. It sounds like you're going to buy time kind of scenario. Am I reading that, right? You're buying time to research it more, to attack it more, to have a MRNA opportunity for a 50-50 chance.

Is that kind of where you're at? Yeah. So the MRNA is potentially curative. So in that case, you're kind of, you're done with this. But it's certainly like buying time. You got to have enough treatments to make it to the new development, both science advancing and some of these drugs that I'm developing. They just take years, many years to develop.

So you want to make sure you make it to the next spot and hopefully in as good of a state as you can with like no, hopefully no metastatic cancer, hopefully no fry kidneys. This is the year we almost break the database. Let me explain. Where do agents actually store their stuff? They've got vectors, relational data, conversational history, embeddings, and they're hammering the database at speeds that humans just never have done before.

And most teams are duct-taping together a Postgres instance, a vector database, maybe Elasticsearch for Search. It's a mess. Our friends at Tagger Data looked at this and said, what if the database just understood agents? That's Agentic Postgres. It's Postgres built specifically for AI agents, and it combines three things that usually require three separate systems.

Native Model Context Protocol servers, MCP, hybrid search, and zero copy forks. The MCP integration is the clever bit your agents can actually talk directly to the database. They can query data, introspect schemas, execute SQL. Without you writing fragile glue code, the database essentially becomes a tool your agent can wield safely.

Then there's hybrid search. Tagger data merges vector similarity search with good old keyword search into a SQL query. No separate vector database, no elastic search cluster, semantic and keyword search in one transaction, one engine. Okay, my favorite feature. The forks. Agents can spawn subsecond zero copy database clones for isolated testing. This is not a database they can destroy. It's a fork. It's a copy off of your main production database if you so choose. We're talking a one terabyte database fort in under one second. Your agent can run destructive experiments in a sandbox without touching production and you only pay for the data that actually changes. That's how copy on right works. All your agent data.

Vectors, relational tables, time series metrics, conversational history lives in one queryable engine. It's the elegant simplification that makes you wonder why we've been doing it the hallway for so long. So if you're building with AI agents and you're tired of managing a zoo of data systems, check out our friends at Tiger Data at Tiger Data.com. They've got a free trial and a CLI with an MCP server. You can download to start experimenting right now. Again, taggerData.com. What does day-to-day like for you, I guess, as maybe the last six months, how is your

life in terms of how you live? What are the things you focus on? Are you traveling a ton to obviously do research or get treated? What's a day-to-day in your life right now? Yeah, it's a lot of working. I like working. These last few weeks I've worked 10-hour days. a lot of meetings mostly the whole day is meetings 25 minute meetings like 15 a day

I've also done some traveling for pleasure we thought at the beginning that this might be my last year so we celebrated the 25 year anniversary of me and my wife extensively with thank you with friends and family that was great also a lot of traveling like going to medical conferences going to treatment on multiple continents. But also doing fun stuff, like adding observability to GitLab. I started an AI coding company called Kilo. I'm still creating these companies around open source projects

with OpenCore Ventures. And then since September, starting to biotex every month. So how many companies are you currently involved in today and here in December? So I started 30 companies over the last three, four years. And what made you want to get into open source agentic coding when you have all these medical companies, you've got to get a lot of stuff going on, you want to, but you want to work on this. Why do you want to work on this particular problem? I saw kind of the rise of open source agentic coding companies and obviously agentic coding is very cool to the future.

And it was cool to see that open source had a chance here. I kind of before I thought it's all going to be closed source. And I saw the rise of open source. And I thought, okay, time to join that game. Are you deploying a similar playbook that you deployed with GitLab back in the day? Yeah. The, you know, Kilo is, it has great agentic coding. But the best reason to use it is that,

that it's all in one. So not only can you do the coding, it can also review your code. Not only can it do that, it can also do the security review. Not only can it do that, it can also deploy it. So it's available everywhere. PSCO, JetBrains, CLI, in the cloud,

and the mobile app. And it can do the full life cycle, including deployment and we're working on more there. So just like GitLab, the ideas to be the all in one solution where you don't have to switch applications the whole time to do what you need to do and to be open source where people can contribute improvements. Right. So what's the open core aspect with Kilo?

So you mean what's the paid functionality? Yeah, where are the lines drawn? Like, where are you thinking? We're thinking if a feature is more appealing for managers or executives, that's where they need to pay. So for our team's functionality, for example, to see AI adoption throughout an organization that's paid functionality, 15 bucks per user per month. And then we also have an enterprise version with features that appeal to executives,

like centralized, bring your own keys, so they can send it to bedrock in their VPC. That makes total sense. So are you working on models as well? Are you just a model agnostic? What's your look on that aspect of the world? Yeah, we're not working on models ourselves. We're working very, very hard on supporting all the models. So hundreds of models work over 500.

We're the most prominent launch partner for new models. So a lot of new models, a lot of stealth models are first launched on Kilo. And our users, a lot of our users use free models like GROC, MinMax, GLM with KELO. Interesting. I think I haven't even heard of a couple of those. I've heard of GROC, but MinMax I haven't even heard of. So this is either underground or upcoming or when you say new, bleeding the edge perhaps. Are these... Oh yeah, it's all new. It's like all launched in the last two months.

There's a lot of kind of Chinese frontier labs. And they want to quickly get their models more popular. So they offer incredible pricing just like rock it's it's it's got code is incredibly good model and it's been free for months now it's an interesting space because you've got a lot of things happening around google in particular there was an announcement today for a flash model i think it's called jemini flash if i can recall correctly but uh you know when you look at that they can essentially offer their models in the API layer for virtually free or a loss leader because they're trying to build their platform while opening eye and anthropic are burning cash making money for sure

but you know when you when you're fighting a competitor that essentially can outlast you because they already have so much incumbent cash or value elsewhere in the chain it's kind of hard to battle somebody who's willing to lose or break even when you have to profit what's your take on the current landscape of just the competitive nature from nations to like maybe China, et cetera, maybe that's just companies there to the battle that's playing out here in the U.S.

Yeah, I think the kind of the leading coding model, that's an incredibly competitive space where kind of the it always feels a bit like Open AI is a better model, and then Google has a better model, and then Anthropic comes back with like

the best model by far, by for sure. Yeah. But also the best kind of free model is incredibly competitive with Deep Segment, Macs, DLM, all these providers and kind of one-upping each other. And what we offer our users is you're going to keep using the same application.

You don't have to sign up for a ton of stuff. It's just our thing. There's no charge. It's completely free. And then you have the ability to use any model you want. Soon you can use different models. You can use free models, bait models, whatever you see fit. So in Kilo, you can also kind of define different profiles because a lot of people prefer to open AI models for planning and architecture, that they prefer something else like I'd use Opus 4.5 for a hard book, troubleshooting.

I'd use GROC for kind of the smaller tasks that are easier. So it's kind of a mix and match approach. I think we're going to live in a multi-model world instead of one model that's the best at everything. For sure. One of the challenges I remember for GitLab, which I think you all overcame, was because you wanted to be all in one and you were providing like the entire software development lifecycle tooling, almost every aspect of that you had like startups and businesses that

like their entire focus was that one thing, whether it was like bug tracking or observability or deploying or whatever it is. I feel like you're going to have the same situation here with Kilo where it's like there are people attacking like separate slices of what you're trying to do and I wonder how you're going to do all the things well. Yeah, the same way we did it with GitLab go incredibly fast. If you look at like where we've come from, like we only started in March and now we have like code reviews, deployment, all these things in one packet.

So we're moving extremely fast, also thanks to agentic coding, plus contributions. And I think we can even improve a little bit on working with the wider community. And yeah, it was like, when GitLab grew up, it was like, oh, but Travis CI has already dominated the CI space. It's now like, hey, Code Rabbit is already dominating code reviews. Just, yeah, let us cook. We'll go faster than anybody else. You got the same people working on it or how do you know you can cook so fast?

I mean, it worked last time, but was it the same team? Because the talented people make good products. There's some people who after GitLab went to work for other companies and some of them have joined, but the majority of the team has never worked at GitLab. And they joined Kilo because they want to go incredibly fast. They know the bar is high. They know they've got to work really, really hard. For example, at some point, we,

Once a quarter, we come together. We do Focus Week, and we all work our butts off for a week. And we do that together. And a week before Focus Week, it was clear that we weren't recruiting fast enough. So I put a LinkedIn post out. I said, look, fly by Monday, we'll make a decision by Wednesday. And then the next Monday, you're expected in Amsterdam. And four people did that.

And they all shipped the initial prototypes of their functionality by the end of the week. and all of them launched their functionality December 10th, less than two months after Focus Week. And it's all held up so far and now they're all going to make it better. But it's incredible speed. The way I would look at it is it used to be that you needed like a team of seven people to do something.

Now you have one person and kind of a whole team of agents working on something. So yeah, we have like 20 engineers, but in reality they're all working with seven agent coders. And that's the expectation that you, as one human, you ship at the speed of what two years ago would be a team of seven or eight. That's interesting. So you've successfully parallelized your cancer treatments and your engineers are parallelizing their agents. I can still only keep one agent busy at a time.

Maybe I'm not ready for this new era. I couldn't work for Kilo. How do they do it? You know, when you got all these different, you know, down in the weeds of how they're managing multiple agents. working on a singular feature, I suppose, or a set of features that support a larger feature and how are they staying productive and fast in that environment? That's common.

Like, you're not alone in only being able to keep one agent busy. But I think 2026 is going to be the year that that changes. Our parallel functionality, where you have kind of, you farm it out to multiple agents in multiple work streams that's just getting started. A month ago, the engineer who made Schaltwerk, one of the early ways to paralyze things joined us and he's doing amazing work. There's still a lot to do.

For example, Kilo has a functionality that's orchestrate. With orchestrate you say, this is what I want to achieve and split it up into separate jobs. So each of those jobs have small context windows because small context windows means it's cheaper to run, it's faster to run. But most importantly, it's not going to lose half of its context because it's kind of getting to the D. the maximum complex window that's effective. But in the common weeks, we'll ship something where those different agents are now able to work in parallel. And you can do a runoff, especially if you're using these free models,

you might as well have two models work and then see which one has a better result. So I think we're going from, you have one working directory today to in the future, you have multiple tasks running in parallel and each of those tasks is running multiple types of agents because it's hard to predict up front

which agent will be the best in any given thing. Right. That sounds cool. It also sounds expensive. I suppose commodity pricing just keeps going down. Is that the approach here? Just innovation and investment brings down the price of agent decoding? If you go to keelow.aI

and you look at our homepage, we see the 10 most popular models for Keelow. I try to count them this morning, and I think eight out of 10 offer free usage today. So that's a way to afford it to... Free as in freemium or free as in free? Free as in free. But until you, until what? What's the catch?

There is no catch. GROC is amazing. I've told that plenty of times in my life. And then eventually there's a catch somewhere somehow. Well, it might be that this whole thing ends at some point where it's most, where it's Yeah, the catch is, it's temporary maybe. Where these models, but what we've seen over time, this has been going on for half a year now. And there's models that kind of launch for free and at some points they become paid.

But the rate at which three models are launching is faster than the rate at which they're getting deprecated. So there's now more free models on the market than there were half a year ago. That's interesting. Eventually, you would think you'd have to make some money somewhere, you know? Yeah, maybe this is like when VC money was plentiful and the Uber's were really affordable. VC dollars are plentiful and the leading labs have free models. Right. I use it while you can.

Use Keeler to burn the VC money out. Burn the VC money. I think that's a legit strategy. The challenge with it is over time, I think you do become hooked. You know, it's like drug dealer is the first one's always free. now in this case, maybe you get a lot for free. But eventually, it's like, I don't know how to write software any other way. And then, you know, three years from now,

and that's when they turn on the old money-making machine. And now you're just subjected to renting your life away. Yeah, I think what you're hinting at is that the cost will go up. I think the cost will go up. Not so much because the same quality model will get more expensive. like the same quality model gets 10 times cheaper year over year. Right. But what we've seen is that the price of a frontier model per token has kind of held steady.

And every time we think it's going down, there's like GPT 5.2, what is it? Thinking or Pro, the really expensive one. And so that's holding steady. But the amount of tokens you can burn as a human, that is shooting through the roof. Yes. With this like split up the work. Or even with my only one agent, you know, I'm going to do one agent, I can burn some tokens. I imagine if I had six agents going.

I mean, that's just six X my token ability. Exactly. And the future we're going to live in is not one where you have like a $100 or like a $20 subscription a month. I think humans are going to burn $10,000 in tokens, maybe $100,000 in tokens per human. You think so? And they'll be a hundred times more effective than the humans of yesterday. Right. It'll be worth it because one human plus all that is more effective than however many humans would cost you that 10 grand.

Doing what? I guess is the question like, is it just coding? Is it just planning? Start this is next business, man. I mean, this guy has got business has come out of his ears. Doing everything. Like every knowledge worker is going to have a collection of agents working for them. It's a wild world.

Yeah, it's interesting about how that plays out, though. you know, it's almost unimaginable to think about, like, I couldn't imagine this year from last year, for example. I could, I suppose, but the vantage point, the perspective is, it shifts so quickly and so much. Like, for example, I just mentioned, you know, Google and their flash model. That's like news as if I believe today, like in the last 15 hours. You know, every day or week, we have a new model, a new flip, a new change. and it seems to be like UX is the moat

UX is still being figured out I think Kilo is an example of how you're trying to evolve or think about different UX around agentic usage it seems hard to predict where we'll go it's incredibly hard

and like we thought this like AGI where the AI would be as as smart as a human would be this seminal moment and it happened in April and like it just flew by and we hardly even noticed it

You said we had AGI in April? Is that what you just said? Yeah, I think in April, the models became as smart as the median human. Oh, is that what AGI is? Artificial general intelligence. Yeah, it's my definition. I stole April from Tyler Cowen, which I think is one of the smartest people on Earth. Okay.

I must have missed it. I just don't know how generally, I guess maybe you're saying because most humans are generally unintelligence. well also like think about chat gpd like it's it it might not know more than the expert in a field but it knows it is it knows a lot about everything the ultimate polymath yeah yeah i mean like i was having some really interesting conversation with chat gpt the day that was that was very therapeutic you know i have been on the code side of things and that's where i'm comfortable at like with how it knows what to do and i guess on the human side where i'm I have a conversation with it, and it's very, it's not just a question and an answer.

It seems to know such detail about particular things, and I don't know how it does that, but it was a therapy conversation essentially. And it was just uncanny, the response type and the level of care. And it wasn't just how it outputs. It wasn't just formatting. It wasn't just user experience. It was this depth that I never expected. machine basically and potentially even AGI who the heck knows to give me back this feedback

loop I just never like I'm steeped in this stuff right we've been steeped in this stuff for years and it is just quite literally unbelievable like unbelievable that I can have that kind of conversation I'm being vague to a degree but it was very therapeutic and so it's incredible this year it helped us a lot like think about how much stuff I had to hear to learn this year and even yesterday i was like i don't really know how a tcr is different than a car t and wow chat gpt walked me through through it and all the pluses and minuses but yeah we're going to give a talk at open a i soon because we did some we things that that were super beneficial to us like we did an RNA test of my cancer so know what RNA was going on and we just sent the spreadsheet

to chat gpt and what came out of it was really insightful. Can you be specific in any way? Like what blew your mind, I suppose? What you're looking for with RNA is like not so much, you have the genetics, but what's actually happening at the cell level, what's being expressed, and what are potential pathways that are over-expressed and you can target? Because I know from the genetic, there's something that sounds like a party drug, but isn't. MDM2 is over-expressed. But I want to see how like the thing it acts on, the P53 division, how that's going in my cell. And there's better examples here, but I'd have to pass that GPT for them.

I don't want to be distracted while talking with you. But like, for sure. Just incredible things. And it's not the end-all be-all, like don't take a treatment without first checking it with a doctor. But just if you have to get smart about a subject in a year, what an amazing blessing it is. It can connect dots. That's where I, like, in this, the dot connecting is, is across the board of all sorts of different disciplines and domains.

That's why I said polymath is like, yeah, that's probably not even a great example. It's like, you know, Uber, ultimate, ultra-think polymath. I don't know. No, polymath is great. And that's also the big benefit, right? Like, we deal with a, I've talked to hundreds of specialists this year. But when you start talking to people who are extremely narrow because they're like the expert in the world in one specific thing. Right.

It's really hard to do the integration. You end up in these meetings with like eight people and they're incredibly expensive and hard to organize. And something like chat GPT, which is like very knowledgeable about everything, is incredible for integrating the knowledge and giving you directions to go in. Yeah, that's where I really,

and maybe this, I don't want a tangentist by any means, but this is where I get really, really conceptual, I suppose, about where the future might go, because we need, I think at least, even in this moment, we need humans to go super deep and super thoughtful into a very specific domain. And like you had mentioned, you have to have eight humans in a room, hard to organize.

But we need those kind of folks to think about the long-term future of humanity. And not so much like in this way I'm saying about, like feed this algorithm, this LLM, this model, its knowledge, not to, not to replace them, but to augment how fast we can iterate through a problem set that requires eight humans and a polymath that sits above those folks to go so deep on a subject that's just basically impossible for eight collected minds to do in one briefing room. It's just humans don't work that way. We don't share that way even interpersonally, but a machine or an AI that's designed to do that can for us.

And that's really where I, it's kind of like a headspace kind of thing, but that's where I, it's where I, I'm mapped to is like you got to have these super deep thinkers with this deep knowledge and they they're obviously going to be human because that's what what we've been as a race to enable this AI to think so deeply and so vastly as a polymath would and connect dots that we just wouldn't normally connect as humans. That's just saying if I've been able to look further it's because I stand in the shoulder of giants and it is in a very narrow field, you're able to, some people are able to read all the relevant publications and to keep up with that. But it's incredibly hard work. And now with these AI things, you suddenly

have a thought partner that not just read everything in the field you're in, but in all other fields. So you're not, you're not forming these people standing on top of each other in one discipline. It's like, it's as far as the eye can see, every discipline, you're up to date on the latest knowledge. That is just incredible. It allows you to run around where before if you moved outside of your field, the whole thing fell down. And now you're just able to combine disciplines like never before. Yeah, it truly is amazing where it stands today and also where it's headed, which none of us can really know, but we can see that trajectory moving us forward. So you just got this engineering meeting. All the ideas are great.

And now you've got to go through your notes, this time-consuming part, read them all, digest them all, had action items, put it in the right places, tag team members. This is all necessary work, but it's tedious. Okay, so flip side that, take that same position and flip it over into Notion and using Notion Agent. Notion Agent does the busy work for me. It's like having a project manager that keeps everything on track in the background while I focus. on the bigger picture, getting my work done, doing my best work, being the artist. Notion brings, as you know, all of your notes, all your docs, all your projects, into one connected space that just works, seamless, flexible, powerful, and actually fun to use.

With AI built right in, you spend less time switching between tools and more time creating great work. And now, with Notion Agent, your AI doesn't just help you with work, it finishes it for you. Notion agent can do anything you can do inside Notion. It taps into your workspace, the web, and connected tools like Slack and Google Drive to complete assigned actions end-to-end so you can focus on the hard decisions. It's like delegating to another version of you that knows your style, knows your workflow, and knows your preferences because it learns from how you work. With a single prompt, Notion Agent forms a plan, executes it, and will

will even reassess and try again if it hits a snag. Completing multi-step tasks like creating new pages or databases from scratch, summarizing entire projects. It does this all in minutes. You assign the tasks and your agent does the work. And since this is all inside notion, you're always in control. You tell your agent how to behave and it will remember and update automatically. Everything your agent does is editable and transparent.

You can always undo changes so you can trust it with your important work. And Notion, as you know, is used by so many people. Over 50% of Fortune 500 companies and some of the fastest growing companies like OpenAI, Ramp, and Versel, they all use Notion agent every day to help their team send less emails, cancel more meetings, and stay ahead. So try Notion now with Notion agent at notion.com slash changelog. That's all lowercase notion.com slash changelot to try your new AI teammate Notion agent today. And when you use our link, you're supporting our show. Again, notion.com slash changelog. You mentioned $10,000 a month, something like this, you know, with a human and some agents doing their thing in the future.

I just saw a post today about Cursor, someone paying $1,400 a month for Cursor. And someone's saying that's ridiculous. And then the other person's saying it's worth it, et cetera, et cetera. We can have these kind of battles. But it made me think back to Kilo because I did see on your homepage, you're kind of trying to attract cursor customers. I think there's even a billboard somewhere in the valley. Calling all cursors over to Kilo. Can you explain the angle, the relationship?

I'm sure we have plenty of cursor users listening to the pod who are very familiar with that particular tool and maybe use that as a way to explain. what Keelow looks like and how it works and all that. Cursar is always a little bit vague about, like, what is list price and how much do you, how much do you pay and they made significant changes over time? With Keelow, we pride ourselves on, you can use over 500 different models, including a ton of, like, stealth ones and free ones. But also, if you're going to pay for a model, you pay list price. We charge exactly what the provider lists as a price, and so you know exactly

what you're getting for your dollar. And I think as people start kind of consuming these AI tokens, more and more, that is the way to go instead of like a subscription where it's a fixed amount, but if you go over, there's a charge, which might, it's probably higher than list price, but it's hard to exactly know, we think a great mix of free models for the problems where you can use those, plus paid models at exactly list price without any commission or overcharge is a compelling proposition. And so Kilo uses this orchestrator itself in order to pick models

in addition to orchestrating your own tasks based on complexity and the particular needs. Right now, people are still selecting their own models in Kilo. It's not trivial to select the best model. and people also have their own preferences. And what people especially don't want that choose key load, they don't want the model to switch up on them. They don't want auto model where you don't really know what it did. And they also want to be sure that they're using the exact same thing the whole time.

So if I say I want that, I want exact that with the exact context window because it's very frustrating if you're randomly using another model or somehow the context window is half of what. you're used to. So I think humans are really good at kind of using, selecting the right model for the right task, but you don't want to, you don't want the software to change it up on them unless, unless they, they give you permission and then still you want to know what exactly was used. That could be configuration in a way, right? You can automate that, that selection through

configuration. Obviously, we want convention over configuration in a lot of cases, but that's a way where you can say, well, when you do these kind of tasks for me, I'm cool with you being on the Flash model, for example, or on the Haiku model where it's faster, more iterative, planning, whatever. But when we're planning, we're going to go deep and we're looking at a Jira ticket or a linear ticket, or we're looking at a pull request,

and we're looking at this, I want the better model, the more reasoned model, to examine that for me. In Kilo, you have profiles, and you kind of set your own profile. That's a combination of want to use this model, but I also want to include these prompts. You can even share these profiles across your organization.

So you collectively work together of like, this is a really good agent for upgrading our Java code or something like that. Because those are going to change too. And, you know, your mileage may vary. So you may use a particular model and you're a rest developer. Or you may use a different model. You're a Java developer. And you may get better results per your team with a model.

That's something you should probably be able to select from. But you're still getting top tier models. in a config where you can say, well, I prefer Opus 4.5 versus the latest Gemini, for example. Yeah. And you're basically creating team members. And just like in a real company, like, it's helpful to have the same team member. Now, these profiles don't have memory yet. That's something for the future.

But they already have a collection of prompts that are super helpful for that company. For example, in a simple way, your style guidelines. Or like, I tried to upgrade our Java before. and it needed these and these prompts to be effective. So being able to share at least these prompts is super helpful. How does Kilo manifest itself to people? Like, what does it look like? How does it work?

You mentioned it's in like all the major editors. So I imagine it's just in the case of VS code extension and there's a windsurf deal. Can you explain kind of the surface area of the product? Yeah, so it's all the VS code-based editors, all the JetBrain's editors, it's available. there's a CLI that you can run anywhere and then we also allow you to kind of run it into cloud cloud agents that's called and then we're soon launching it works on mobile already but we're soon launching a mobile app as well

oh explain how that would work I think one of the cool things is if you have a thought you can just kick off kick off the agent with that so instead of kind of give it to me yeah look you're somewhere you're not going to go to your desktop, you have an idea, now you write it in your notes or whatever you do. Tomorrow you just kick off an agent and then you can pick up that agent whenever you get behind your notebook again. It's going to be available in Japan, in VS code, etc. So all your sessions, you have a complete overview of your sessions, whatever platform you're on. And I'm looking forward to also getting kind of a mobile notification when my agents are done because that's my primary thing.

like the agent is done, I need a ping so I can see what it produced. This is something that cloud web is what I call it. It's just clod.ai, but it's not cloud code. It's cloud web. They just enabled you to connect a repo on GitHub. And I think this is like early days of this feature. And I didn't really have a repo to connect it to to think about. So I was like, I just want to like do it in an isolated area where there's no damage.

You know, it can't go write code accidentally or send a pull request or do something weird. And I connected to a brand new empty repo. And I just kind of one-shot it in a way this idea that was really just a basic go-cly. And in this case, it was kind of a coding session, but I was just trying to thought experiment, okay, if you have this mobile interface or this web interface that is not a coding environment at all, it's not cloud code in the terminal. It doesn't have terminal functions. It doesn't have your system or things like that it can use to write a Python script and run it kind of thing.

I suppose it does in its own, you know, virtual environments, but I was like, how does this work where you can not be in any sort of way an IDE or a code editor and be, in quotes, a developer or a builder or someone who's thinking about software and planning it? But then it's like, hang on, I'll just go ahead and write this for you and commit it back to this repository. I'm like, what? Okay, do it.

You know, like that's a kind of a cool world. Is that a version of what you're doing with Kilo in the mobile app? Yeah, for sure. And that's available on our website, too. It's called App Builder, and it's more of the Replit experience where you just prompt what you want, and it starts coding that. And because we have these cloud agents, which are really the back end of that are Cloudflare containers.

Because we have that, we can also do code reviews. So as soon as you connect your GitHub or your GitLab, you can just say, hey, from now on, all the code that was written automatically kick off a review. view for that as well. You can already configure Kilo to focus on certain aspects, be less strict, more strict, et cetera. I think that just gives us more of a reason to always be working in a way. It's like in the new knowledge worker world, and it's like, hey, what are you doing over there? Well, I'm not scrolling TikTok. I'm actually writing software right now, but you're on your mobile device. That's just an iPhone, right? Yep. It's like, no, I'm knee deep and a problem.

and I'm fleshed out of spec or I'm, you know, whatever. You know, like that's kind of wild to think that from this mobile device, we could just be on the subway or at a birthday party and we're bored and working. Yeah, I think these are your coworkers. The most natural way I interact with my coworkers is either a video call or Slack. And we're like, we're going to launch a Slack integration in, you know, hopefully this month and otherwise next month because that's the way I interact with

a co-worker and that's the way I want to interact with an agent too. So I think collaborating with agents is going to look a little bit less like this big monitor with an IDE on it and more like slack on your mobile phone. Yeah. Think mode. I said the term earlier, polymath. Would you consider yourself

a polymath said? Well, since this year, at least I do two things. You're poly. Do a math, maybe. Look, I'm no Colossumbrother and no Casey Handmer. I get by. I certainly have a broad set of interests with help, which helps. It's like imposter syndrome right there.

You don't want to call yourself a polymath, but you're a polymath. He'll let us say it, but he's not going to say about himself. Yeah. That's fair. Do you have any thoughts? I'm thinking kind of like, given your history with GitLab, your entire career arc, even through a crisis in your life, you've had the chance to mentor or lead, design the most effective culture, take a company

to IPO, live the American dream, have an amazing marriage of 25 years. Congratulations again. Something as simple as the hope for the future of developers. Can you wait in or do you have any thoughts at all about the I hear this this idea of this comeback to like there was a lot of people let go a lot of junior developers let go and here you just have Matt Garman CEO of AWS saying that junior developers it's stupid don't replace them with the eye like don't do that do you have any outlook or any hope for the future of being a software developer and what that might look like look I'm I'm a very lazy person I don't like tedious things And although programming seemed interesting to me, I read some of the code and I'm like standard IO.

Like I'm not going to write code that way. That seems super boring. So I never got into programming until I saw Ruby. And I'm like, wow, this is beautiful. This is the opposite of tedious. This is beautiful and it's efficient with my time. And I love this interface. And I think agentic development is another step towards this is no longer tedious.

I could just have an idea in my brain of how something should look, how something should work, and I can just write that down or even use voice mode in Kilo, and it will get done. It's amazing. It's never been a better time to create software because we can do so much more, so much quicker. and it doesn't have to take you 10 years anymore. You don't have to study computer science. You don't have to solve these lead coding problems anymore.

You can just make it yourself without any other human helping you. It's incredible. I agree. It is a fun time to be a developer. And it's the way I look at it or the way I think about it is like the state of play. There's studies on flow. Obviously, you can go back to that as neuroscience basically.

the state of play is where we learn and have the most fun, and it feels like playfulness. It feels fun to do, even if it's challenging, arduous in some cases, maybe there's a learning curve, you know, maybe there's a research phase.

You've got to get caught up on, you know, how an API or CLI works or whatever. You've got to learn things you didn't know beforehand. And because I think there's a level of learning in all of this, even if the AI knows a lot, I think you should still know just as much as well, or at least try to or strive to understanding.

it's kind of wild to be in that space where it's the state of play. It feels like very playful. Yeah. For me, a state of flow is where I don't go off and check Hector News and Reddit on the side because I'm getting bored or I have to wait. And I think 2026 will be the year of the parallel agents. And it's like the spinning plate act where you have all these agents up in the air, all these spinning plates, and you continually have to kind of shake one of them

To keep them all up in the air, you never, you never have CBOO board again or wait for them. And I think that's, that new balance will be like, I don't know, balancing, balancing on a, on a surfboard or something like that, where you also, you have to focus. And you don't have to raise. You mentioned starting 30 companies. I'd imagine you have a lot of opportunities available. Do you, do you have a place where people can go? We have a large audience, probably listening, potentially those who are chomped at the bit for either new, opportunities or a opportunity or their first opportunity or change because of just new

interests or new things that just are grabbing them are you hiring across these 30 companies what do you what do you personally need for new talent in your in your enterprises um yeah if they if they're listening to this podcast they probably like the the tech companies more than the biotech companies. So OpenCore Ventures has a portfolio on the website. And I think companies always need people who can get things done themselves and are able to go after something by themselves and get it done, get it over the finish line.

At one of the post hoc founders wrote a great article about stop collaboration. Like there's a lot of, because you now have a team of AIs reporting to you, you shouldn't also be kind of trying to partner up as much with other humans. Like you have all the ways to make it happen in order to go fast. Collaboration should never get in the way from making individual progress. It should never delay kind of trying to get something over the finish line yourself. It's great if people have suggestions and great if you ask for, if you ask for feedback, but never stop, never stop the progress and never delay because

you had to coordinate with someone else. Just use your best judgment and get it over the finish line. And I think for people who are effective by themselves, the world's your oyster. Well said. Anything else, Sid, you want to talk about with us or make sure we mention about Kilo or anything else that's on your plate that you want our listeners to know before we let you go? We touched on a lot. This is super fun. Thanks, guys. It's always fun, man.

It's been too long. We use us each other more often. I'm glad you're out there doing your thing. You've crossed the chasm, it seems, of your cancer situation. Obviously, you're still out there hunting it. So I assume the treatments will continue, the research will continue, and the hunting will continue. Hopefully that vaccine or the MRI treatment you're going to take 50-50 chance. Hopefully it lands on heads.

And you can be free from this. But it seems like you're not just surviving, but also thriving, at least from what we can tell. Yeah, for sure. With your many businesses and all your interests. So it's pretty cool. It's been great. And I'll settle for this as long as I'm having a ton of fun pushing all of this forward. And yeah, it was a bit hard to make the time when I was full-time CEO.

That's a big job at GitLab and have a little bit more flexibility in my schedule. Yeah. To be on the show again soon. Absolutely, Sid. Always welcome back. It's good seeing you. Thank you so much for sharing your story and sharing your time. Thank you, too. Bye. All right, this has been our first interview of 2026.

We hope you enjoyed it. Who else should we talk to on the pod this year and what should we talk about? Did you know we have a request form on the website? We do head to changelog.com slash request and tell us what you want to hear. We want to hear from you. Big thanks to our partners. at Fly. I.O. into our beat freak and residence. That's Breakmaster Cylinder for all of our dope beats. And thanks to you for listening. We appreciate you. That is all for now,

but we'll be back in your ear holes with our old friend Matt Ryer and his guitar on change dog and friends on Friday. Bye y'all. You know, Game on