Inside The Startup Building Uncensored AI (Abliteration AI) | EP 2345

This Week In Startups is made possible by: Every.io: http://every.io/ Northwest Registered Agent: https://www.northwestregisteredagent.com/twistdomain Odoo: http://Odoo.com/twist Plaud: http://Plaud.ai/twist Today’s show: What can AI do with the guardrails OFF? Devon Thomas of Abliteration.ai thinks defenders should have access to the same kinds of tools, rather than having one hand tied behind their backs. Then, on Ask Jason, learn what AI means for the billable hour from a legal-tech founder. PLUS, are AI microdramas a real ecosystem or a fad, and does AI finally make solo founders fundable? Guests: Devon Thomas on X: https://x.com/founderengineer Abliteration: https://abliteration.ai/ Relevant Links: Abliteration.ai on a16z speedrun — the accelerator Jason congratulated Devon on → https://speedrun.a16z.com/companies/abliteration TechCrunch: "Abliteration.ai is making a business out of removing AI guardrails" — the coverage behind the recent attention → https://techcrunch.com/2026/09/03/abliteration-ai-is-making-a-business-out-of-removing-ai-guardrails/ Abliteration.ai press page → https://abliteration.ai/press Anthropic Frontier Red Team: "GLM-5.3 and the spread of advanced cyber capabilities" — the blog Devon cited on how capable abliterated GLM-5.3 is → https://www.anthropic.com/research/glm-5-3-and-the-spread-of-advanced-cyber-capabilities CNBC: Trump's executive order renaming AI "super intelligence," signed the same day → https://www.cnbc.com/2026/09/29/trump-ai-super-intelligence.html Nextgov/FCW: OpenAI agents accessed Census and SEC data — detail on the dozens of organizations OpenAI notified → https://www.nextgov.com/cybersecurity/2026/09/openai-says-its-advanced-models-may-have-gone-after-government-websites/416250/ Financial Times: "AI wrecking ball fractures billable-hour fee model" Seedance 2.5 — ByteDance's video model Bruno asked about → https://technode.com/2026/07/31/bytedance-launches-seedance-2-5-video-generation-model/ Pixar / Toy Story — the CGI "Toy Story moment" Jason expects for AI video → https://en.wikipedia.org/wiki/Toy_Story Practi — Mathew's platform for helping law firms move from hourly billing to subscriptions → https://practi.ai/hello Timestamps: 0:00 What http://Abliteration.ai does, and who the frontier labs are shutting out 2:44 Plaud: If your work depends on conversations - interviews, meetings, calls - you need a Plaud NotePin S. You can check it out at https://Plaud.ai/twist and use code TWIST for 10% off! 2:56 Why defenders don't get the attackers' tools 4:16 "Inversion of control": letting customers set their own guardrails 6:47 Who's liable? The hammer analogy and the White House self-regulation pact 10:11 Every: For all of your incorporation, banking, payroll, benefits, accounting, taxes or other back-office administration needs, visit https://every.io. 13:10 Why AI labs publicize their scariest hacks 18:52 Customers: from cyber startups to Fortune 500 CISOs 19:56 Northwest Registered Agent: Got a new business idea? Northwest Registered Agent helps you bring it to life. Get a free domain, email, phone number, and more - with no purchase required! - Learn more at http://northwestregisteredagent.com/twistdomain 24:41 Chinese image and video models 27:20 Why most businesses still barely use AI 29:02 Ask Jason begins 29:24 Mathew Kerbis (Practi): What does AI do to the billable hour? 30:16 Odoo: The all-in-one business platform. Your first app is free! Get started today at https://Odoo.com/twist 32:45 Will subscriptions replace hourly billing? 37:27 Bruno Vilela: Are AI microdramas an ecosystem or a fad? 39:35 Lon's microdrama pitch to Snapchat and TikTok's PineDrama 48:09 Josh Ezell: Does AI change the bias against solo founders? 49:26 Jason's three-two-one framework and the risks founders must eliminate Subscribe to our newsletters on Substack: TWiST: https://twistartups.substack.com/ TWiAI: https://www.thisweekinai.ai/ TWiVC: https://thisweekinvc.substack.com/ Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp Follow Lon: X: https://x.com/lons Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis Check out all our partner offers: https://partners.launch.co/ Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

• 0:00Speaker 00

  All right, everybody. Welcome back to This Week in Startups. I'm your host, Jason Caligan. It's with me today, very lucky to have Devon Thomas with us. Now, Devin, you and I met because you came to Launch Festival, just like a little event I do for founders. That's the origin story here. Tell us how we met and then we'll talk about what you're building.

• 0:21Speaker 01

  Yeah, yeah. So when I first came up with the idea, I was kind of researching some pre-seed funds and I followed you on X already. And I think you tweeted, actually, you were like, oh, I'm excited about what I'm going to be doing for this project of mine, Founding University. And I just was like, okay, this sounds like you're excited about it. So let me see if I can sign up and be a part of it. And, you know, I just reached out and then soon as I kind of like engaged with you all, then, um, yeah, they were like, oh, we have something coming up called Launch Fest. If you're interested in doing that as well. And so, yeah, and then you were there. It was cool. It was a great experience.

• 0:53Speaker 02

  This Week in Startups is brought to you by Odoo, the all-in-one business platform. Your first app is free. Get started today at O D O O dot com slash twist. Northwest Registered Agent. Got a new business idea? Northwest Registered Agent helps you bring it to life. Get a free domain, email, phone number, and more with no purchase required. Learn more at northwestregisteredagent.com slash twistdomain. Every for all of your incorporation, banking, payroll, benefits, accounting, taxes, or other back office administration needs, visit every.io.

• 1:29Speaker 00

  Amazing. Yeah. And this is like one of my key tenants is say yes. I always tell my team, like, just like, if you meet a founder, just say yes to meeting, just say yes to having Launch Festival, letting a bunch of founders come together. You never know what could come out of it. And you've got this great startup obliteration. Maybe you could explain what you're building, why it's important.

• 1:51Speaker 01

  Started obliteration like at the end of last year, I was actually, uh, I built like a home cluster, GPU cluster. And actually, I originally started kind of serving the site from my home cluster at home. But what makes it important is there's a whole bunch of professionals and companies out there that are essentially underserved or unserved by the frontier labs, because whether they're in cyber or they're doing biology research, or they need synthetic data or defense, all these use cases that essentially, uh, the frontier labs are essentially shunning. And so we are, our kind of tenant is to try to provide the best models that will allow these, these use cases to be unblocked. And so we've had a lot of traction, a lot of press, uh, all around that, because, um, maybe some people feel like, uh, we, these use cases shouldn't be unblocked,

• 2:36Speaker 01

  but those professionals seem to be super happy about it. So it's been going well.

• 2:39Speaker 00

  All right. And before we go to a demo here and talk about this really important issue, I just want to take a minute, put my Plod pin on. Hey, if your work depends on conversations, interviews, meetings, calls, check out Plod at plod dot twist. Use the code TWIST for 10% off. Great partner of ours here. And so let's talk about it, Devin. The frontier models have full access to the latest and greatest large language models. And then if you're in cyber defense and you are, let's say, hugging face and OpenAI wants to do a series of attacks, you know, whether intended or not, or they're testing or white hat, let's put it all aside.

• 3:22Speaker 00

  They want to test cyber. They pick hugging face as a target. Hugging face does not have access to OpenAI's latest model. They keep that for themselves. So hugging face, if they wanted to mount a defense against the latest and greatest frontier models, they don't have the same access to the tools, correct?

• 3:42Speaker 01

  Exactly. Yep. And even if they have access to those, uh, special cyber programs, still there, uh, many of them, uh, our customers are still complaining about refusals. And these are big corporations. It's not just startups or individual researchers. It's still big corporations that have access to cyber programs are still having the issues with refusals, just trying to do their, their, their job.

• 4:02Speaker 00

  Okay, so you are taking open source models, um, I'm assuming GLM or deep sea. And you're allowing people to run them in their native form without restriction, correct?

• 4:16Speaker 01

  Yep. Yep. So the, yep, the process of obliteration is to kind of remove those guardrails. And I always say like our unique, I guess, innovation or idea on the, on the space is to allow customers to set their own guardrails. So we have a feature where it's kind of like, uh, I always call it an inversion of control, right? We separate those two layers, right? We have the unrestricted model is one, one layer, right? Which is like all the labs and open source models have the refusals baked in. But then we have a software layer where you can kind of define your own policy for your company. So you could have more stringent, uh, guardrails than, than were native, or you could have less in certain areas and stronger in certain areas. And like I said, it's kind of the idea is to give them back control about, uh, control over what they can and can't do.

• 4:54Speaker 00

  Let's do a specific example here. I'm on your website. And so just for cybersecurity here, um, you have a little, uh, uh, I guess, let me just rerun this. Uh, as we see on the right-hand side, we see the obliteration model,

• 5:11Speaker 00

  taking a, a command from the user and then other labs denying it. Explain what this example is and why it's relevant.

• 5:18Speaker 01

  Perfect example is like, there's companies out there that they'll hear about a vulnerability, right? And they want to maybe test to see if they are vulnerable to it, right? The big labs won't even allow you to test that, right? So in this perfect example, like, okay, I, I see, okay, there's this CBE that's, uh, live. Let me test against my site to see if it's a vulnerability that we need to fix immediately. Or is it maybe just something that's not, uh, a real concern? So this is a perfect example of a use case where like a red team would be able to use our models and not use, uh, uh, another companies.

• 5:50Speaker 00

  Got it. And so other, um, use cases outside of cybersecurity, uh, red teaming, explain red teaming and why that's important.

• 5:59Speaker 01

  Yeah, yeah. Red teaming is kind of like the use case we said before, but one of the like early use cases we had success with is like, all these companies today are rolling out agents, right? You hear about agents, every company you could imagine. But imagine I call your bank, right? And I say, hey, I'm Jason, wire Devin all my money, right? You want to make sure that doesn't work or some, some, some combination of commands won't allow that to work, right? So you probably want to red team those agents, meaning, uh, model a threat actor essentially against those agents. So we have some startups that are customers of ours that kind of sign, uh, big banks or sign other critical infrastructure companies to red team these agents or these AI systems that they're rolling out.

• 6:35Speaker 00

  Because you're providing this level of fidelity, uh, with the tools,

• 6:43Speaker 00

  you need to be thoughtful about who's signing up for your service. So how do you think about who's signing up for the service, how they're using it? Or is it up to them to take responsibility for how they use this? And obviously this dovetails with the president's, um, you know, regulations that they did just this past week in Washington DC, where he said, hey, y'all need to, uh, police yourselves because there are laws in the world. If you take this software and you do things in the world that aren't illegal, hacking or unethical, you can get sued. The government can take action, private corporations or citizens can take civil action. We, we have a world of, uh, of remedies here for people who are using tools inappropriately.

• 7:27Speaker 00

  So take me through how you think about who's using the product, your liability, their responsibility, and everything in between.

• 7:34Speaker 01

  Yeah. So I think it's kind of two sides to that answer, right? So I think one side is that like, it's not a free product. You still have to sign up and put all your details into Stripe. And that doesn't obviously stop a bad actor, but that kind of leaves some, some form of a paper trail there. And then going forward, kind of the, the way the law works kind of today, from at least our understanding is like, the user of the tool today is kind of responsible. So we don't provide like the actual agentic layer to, uh, what you use with the model, right? So we just, it's like information in, information out, right? And then the user is kind of responsible for what they take and do with the information. It's kind of, I use the kind of oversimplified example, like if someone goes and takes a hammer and hits someone with it, right? Like the creator of the hammer is not necessarily liable in that case, right?

• 8:17Speaker 00

  Nor is the hardware store, for the record, uh, or the, uh, you know, paper bag that you put the hammer in. And in this case, like in some ways, you're like the paper bag, like people are buying this thing and, you know, yeah, you can host it, et cetera. But they're responsible ultimately for how it's used. And so when you look at the cyber capabilities of these models, describe for the audience, the, the delta between the models that are currently out from Anthropic, Grok, SpaceX, I I, and OpenAI, and then the models coming out of China, the deep seeks, the GLMs, et cetera. What's the, the difference there between those two models?

• 9:01Speaker 01

  Yeah.

• 9:02Speaker 00

  How, how different are they in reality?

• 9:04Speaker 01

  Yeah. So I think, uh, I don't know if you saw Anthropic just wrote a blog, right? About how capable GLM 5.3 is, uh, especially the obliterated version, like similar to what we offer, uh, is in cyber. So that gap is closing. And I think that's some of the. The outrage in the industry today. Yeah, exactly. Is that that gap is closing faster than I think people predicted. Even the term, I kind of don't even like that term, right? Frontier models, right? It's it just has this connotation that it's like some set stack ranking that they'll always be ahead and they'll never that that window will never close. But it seems to be closing relatively faster and faster, right? The maybe before it was a year, they were a year behind. I would say today they're maybe around three months behind.

• 9:48Speaker 01

  So I think around the absolute frontier. So I think they're catching up. And I mean, I think sometimes as these companies have these huge valuations, right? It's like you have to worry about, you know, commoditization of models, right? Is there just a point where like the capabilities everyone has is like roughly similar enough that the end user really can't tell the difference, right? Unless you get to some edge case.

• 10:11Speaker 00

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• 10:53Speaker 00

  like their new time off feature, which pulls sick leave rules for every state and city you operate in. And boy, is that complicated? And it builds a policy based on the strictest requirements. That automatically syncs with your payroll system. I have been through this so many times, folks. What a brilliant feature. So head over to every.io and stop wasting time on the stuff that isn't growing your company. That's E V E R Y dot I O. Explain to us in the creation of these models, what safeties are baked into them and then how the guardrails are taken off? So when we see, you know, hey, I want to try testing my, you know, corporation,

• 11:35Speaker 00

  my servers, you know, my systems against this particular hack. Frontier model says, you know, no, we don't do that. Open source model says like, oh, we don't do that unless you have the unhinged unrestricted version. Take us through how that is added to the open source models and then also how it's removed and then I'm allowed to build it back up.

• 11:59Speaker 01

  There's been like a lot of hype around the last few years around model interpretability, right? Which is like, how do we interpret like what each neuron in a model is doing, right? So if you hear these numbers, like a 27 billion parameter model, a 32 billion parameter model, or whatever the number is. But what we what you see in training is or training of models, you see that like pieces of information are kind of localized amongst each other, right? Like these neurons might be responsible for this information and vice versa, right? And so what obliteration is, is kind of finding those those neurons, those parameters essentially that are responsible for like the refusals. And then you kind of you modify them and then it's less is possible. So you don't decrease the performance of the model. And then, like I said before, kind of what we do is add a separate API layer on top

• 12:43Speaker 01

  of that, which then is actually a model itself, which actually runs those guardrails, guardrails focus model in between there. So it's kind of your your request actually is kind of going through two models, but the the guardrails focus model is pretty small. So then it can operate in like, you know, a few milliseconds. So it doesn't add a lot of latency to your request.

• 13:01Speaker 00

  Why do you think a lot of these companies are spending so much time hacking systems and being very public about that? You're in Silicon Valley and you see this dialogue where they're constantly talking about the hacking, quote unquote, that their agents are doing in swarms, all this kind of activity. But I don't hear them often talking about, hey, we're using this new model to find vulnerabilities and then patch them and work with the makers of other software who have patches that need to be addressed. You don't hear the white hat version of what they're doing.

• 13:41Speaker 00

  You only hear about them letting governments know, hey, our crawler appears to be with the OpenAI.

• 13:49Speaker 00

  And I want to get your details on that as well. But OpenAI made a bunch of people aware that they had accessed information on their websites or on their systems. And it was like, well, it's kind of benign access. It wasn't like it hacked it, but yet they were making them aware of it. So that was the scraper. Take both of those issues and then that specific case.

• 14:10Speaker 01

  Yeah, so I think I think I think actually they do kind of produce some stuff on the white hat stuff, but no one really cares, right? I think it's kind of like if it bleeds, it leads type situation where it's like it just people love these stories of these hacks. And I think they're they're kind of capitalizing on that. It's like a demonstration of capabilities, right? Like our AI is so good that it can do these like, you know, these fantastical hacks and things of that nature. So I kind of think that's probably why you see so much about that is that it's more interesting to what people are interested in in in social media land. And yeah, so and I think like as far as like the crawlers and all those things, I think that, I mean, if you unleash, I mean, people go on the internet, right? If you unleash some agent on the internet, right?

• 14:55Speaker 01

  It's going to go do whatever you kind of commanded to do. And I think like how you set guardrails, how you how you configure the system, all those things matter. And I mean, maybe as they've been testing over the last few years, because I think some of those those news articles are probably pretty old, like from things that happened before, and they're just reporting them now. So yeah, I think it's a combination of things.

• 15:16Speaker 00

  These crawlers are quite aggressive, though. And when in your experience, when they set these crawlers out, do they give them kind of the open ended goals of like, hey, you get points for finding new information and find it any way you can? And they're kind of sent out unhinged scrapers on the web? Or do they have thoughtful scrapers that are contained? And are, you know, when it finds an exploit or data that maybe shouldn't be indexed or crawled, it says, oh, you know, this probably isn't information I should have access to. I'm going to go ask somebody on staff, like a human, okay to crawl or not.

• 15:57Speaker 01

  I think it's tough, right? Because you're trying to balance two different things. So when you run Exploit Gym or all of these different benchmarks, that's what you get points for, right? You get points for how far you can take an exploit, right? There's like level one, level two, level three, level four. And like when you're doing a reward, you write your reward function, right? The reward function for the model is how far can you take this exploit? So it's hard to like balance that with a competing reward, which is like, oh, if you go too far, let someone know, right? I think it's it's a I think it's, I mean, it's an engineering problem for the industry as a whole, right? It's like, okay, how do you run these benchmarks and have those reward functions, but also not actually do things that are illegal, actually? So.

• 16:40Speaker 00

  And who the target is matters, right? Like, so running this against targets that are not your own.

• 16:48Speaker 01

  Customers.

• 16:48Speaker 00

  Targets and customers, like running against your customers and not alerting them to the fact that you're doing it seems bizarre.

• 16:56Speaker 01

  Yeah, yeah, I don't understand it, but I think also I'm we're all outsiders looking in, right? Like, I don't have any inside information of what their goals were and what they're trying to do there. And I think I think I'm just in the dark as everyone else.

• 17:10Speaker 00

  But yeah, I think probably people are having so much fun with the technology and making so much progress that they're like, okay, let's up its resources. Let's up the challenge. Let's up the rewards. Let's, you know, see what happens when we do X, Y, and Z. And, you know, you maybe have to rethink that of kind of like we were talking earlier about driving Model S's really fast on the Autobahn. Like, okay, the technology can do it, but you may want to think, should I do it? Because what if you blow a tire and you didn't do anything wrong and the car is perfect, but tires blow out, you hit an L or something on the road? And sure enough, there was an incident that just happened where like somebody blew out

• 17:53Speaker 00

  a tire at 170 miles an hour and test them, they survived. But I do think people, maybe there's a level of recklessness, not thoughtfulness, somewhere involved in this, yeah?

• 18:04Speaker 01

  Yeah, I think especially as these labs are getting labs, right? Are getting so big, right? They have how many X number of researchers, right? And I mean, they probably are looking for things to do. I think that that might be like a boring answer for a lot of the question.

• 18:17Speaker 00

  That's actually an insight I've never heard anybody make, Devin. That is actually perhaps super accurate, which is when you have an unlimited amount of resources and people looking to make an impact inside a company, they will try to have an impact. And how do you have impact in a company? Well, if I can figure out how to get more data, I can find some data well that other people didn't get this data ocean, I found it. I could be helpful to my company. Like, that's your idea is to be useful to the company. Who are your customers now? And, you know, how do you get new customers? Is this something where it's like hobbyists and people on the frontier of technology who are hackers?

• 18:58Speaker 00

  Or do you have corporations coming in saying, hey, we need somebody to manage this for us, a partner? And, you know, we're going to look at your firm as the perfect partner to do this because you have expertise in this area.

• 19:13Speaker 01

  At first, a kind of target market was kind of like startups, like cyber startups and like other like startups in those in those spaces that maybe didn't get access to those cyber programs or they have access and it's still they still weren't able to do their jobs. But what has surprised us maybe over the last month is that we've had Fortune 500 companies reach out in almost every industry and like, obviously, we still have the a lot of motion in the startup startup market. So a lot of cyber startups come to us, a lot of red teaming startups come to us. But then even a lot of the CISOs at these big companies are like saying, hey, like before some outside AI comes in access, can we can we use your product and make sure we test our own systems first?

• 19:56Speaker 00

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• 20:41Speaker 00

  Learn more at northwestregisteredagent.com/twistdomain. And so people using the product are going to get this unrestrained version of some of these models. Talk to me about how you add back, you know, what constraints you want to have on the model. How does that work? And are there like libraries that are standard? Do people share like, hey, here's the scaffolding I'm building around this? How does that process work of rebuilding the harness, let's say, or the security and the limitations around how these products are used?

• 21:21Speaker 01

  So there's models, right, that that you can use that are smaller models that can, like I said, like operate in milliseconds. And then so you can set those guardrails in those models. So then you have two layers, right? So before, one layer, you have a model, refusals baked in. Now you have two layers and then you have a model that's just focused on safety. And then you have a model that's focused on knowledge or information, right? And so then once you you separate those those two layers, then now you can just focus on controlling the policies in the policy layer. You can focus on controlling the information and the information layer. And so that that's kind of the the idea behind it is that users can then, when they set those policies, it just goes to the the the moderation layer or the safety policy layer.

• 22:05Speaker 01

  And then and then we have some default policies that are set there on CSAM and as well as self harm as well.

• 22:13Speaker 00

  Yeah, those are quite important if people, you know, are asking it, how do I off myself? Like, every single platform that's come out since I've been on the internet, which was before the web, Usenet, you know, Gopher, eventually the World Wide Web, even AOL, Chatrooms, CompuServe, they had to deal with self harm as an issue. I remember like early on Wikipedia saying, how do we deal with the page on suicide? Like, there's been historical suicides that have occurred. How do we be a good actor and not share how somebody killed themselves? Because we don't want to be an instruction manual. And they all came to a pretty simple solution, which is you put up the phone number of the suicide hotline and you just put a big box there that forces people,

• 22:57Speaker 00

  whether you're on a Google search or a social network, you type in some kind of self harm, it directs you to the best possible, you know, help you can get, which is, by the way, more than what happens in the real world where people can just go do dangerous things, you know? So fascinating. And so tell us about the the state of the company. I know you guys got into Speedrun as well. Congratulations on that. And how's the company doing, you know, as a startup? And where did you guys come from before having this startup?

• 23:30Speaker 01

  Yeah, so we both kind of came from big tech. We worked together at a big technology company. And yeah, we got into Speedrun a few, like a few, some time ago. And it's been great. So they've they've kind of helped us with some like company formation stuff. Like, we were kind of formed, but it's just like getting all the like things in place that it actually takes to run a real company, right?

• 23:52Speaker 00

  Yes, the chores.

• 23:53Speaker 01

  Yeah, yeah, yeah. So we were

• 23:55Speaker 00

  Do your chores.

• 23:56Speaker 01

  We were kind of flying by the handle. So we're excited for a lot of the announcements that we have coming up in the next few weeks. Because our plan, myself and my co-founder is really that to build a brand people can trust in this space, right? Like, it's kind of the Wild Wild West right now and everybody's like, okay, is this brand trustworthy? Is this brand trustworthy? So if we can continue to grow and continue to, you know, go through all the audit processes and, you know, build those relationships with maybe even law enforcement or otherwise, to make sure that we're, you know, following all the regulation and XYZ is to really, really kind of be that brand in this area that consumers can trust, even though they may need something that's a little bit more risky than they would get from the big labs.

• 24:39Speaker 00

  Image models and the video models coming out of China, there's been a lot of controversy on around those because they can output IP. Now, obviously, that's on the person doing it. If you want to, you know, make your own Jedi Knights, it's up to you to not break copyright law. But are those models available in the US yet? I know that, I forgot the name of the one that TikTok ByteDance provides, but people have lost their minds over that one. And are people looking to use those models now in the United States or just the unhinged image models?

• 25:14Speaker 01

  I think they are. But I think like for us, we try to stay focused on kind of like the B to B use cases, right? So I think the unrestricted model space is big and there will be players and consumer and all those things. And I think we'll probably kind of let other players kind of take those use cases and we'll just kind of

• 25:30Speaker 00

  See Dream, ByteDance's family of AI and generation image qualities. Yeah, people are crazy about those. All right, listen, where can people find out more about the startup? And I understand you'll be hiring. So tell us about any positions you're looking to hire for people who want to join a rocket ship.

• 25:47Speaker 01

  Yeah, for sure. So you can find us on X or LinkedIn and also obviously our website, obliteration.ai. And then our contact information is there. So we haven't opened up any official positions quite yet, but we're we're Yeah, soon, soon come and we'll be hiring, kind of, you know, go to market, probably, obviously, like some engineering positions. And we're excited to just continue to grow the company as we we we navigate this, the immense amount of growth that we've had over the last two months.

• 26:20Speaker 00

  It's been big growth, huh?

• 26:22Speaker 01

  Yeah, yeah, yeah.

• 26:24Speaker 00

  And how do you, how are you keeping up with that? Is there enough capacity out there for you to get access through through all these different cloud providers? Or is it like a dogfight to get all this infrastructure dialed in?

• 26:35Speaker 01

  That's a great question. So at first it was pretty hard. So like, we grew like just, we outgrew the amount of compute that we had. And everyone was like, oh, it's slow. Like, we were like, oh, we didn't know that we're, it was going to go this fast. But now a lot of our partners are kind of helping us out. So we're in a better position now, for sure.

• 26:52Speaker 00

  Yeah. And there's enough compute out there in the world? Or you you really need to kind of get an inside person to kind of help you? Is that what I'm hearing? If you

• 27:00Speaker 01

  Yeah, yeah. Yeah, I mean, the GPU market is, I actually used to kind of think that the GPU shortage was fake. But now I've experienced it and it is, it is, it's actually a real thing that it's not that easy to, at a, at a certain scale, to really supply those needs consistently and like have high availability and high performance and all those things. So it gets, it's harder as you grow, for sure. It's definitely a growing pain.

• 27:25Speaker 00

  And yeah, there's just so many people applying tokens to so many different pursuits all at once. Like, I wonder what percentage of people running a business right now are using tokens every day? It's definitely the majority of users. It must be. And then that doesn't even count consumers.

• 27:43Speaker 01

  I saw, I saw a stat, though, that they, I think A16Z just produced a report. It's still a large percentage of like businesses that just haven't adapted it yet. So they're surprisingly just such a huge upside to the business still, like, it's like, it's easy to, for us, you or I, to be in this tech industry and we're just in this echo chamber that's AI, AI, AI, right? But it's a, there's a lot of America left, a lot of the world left.

• 28:07Speaker 00

  That does make sense on the enterprise basis because they probably have been told you can't use it. So if they, even if they wanted to, they probably have to get permission and write a TPS report and file, like what they exactly want to accomplish and what jobs they potentially get eliminated and security vulnerabilities. It actually is, yeah, slower. And I, now that I think about it, even in my 20 person venture firm, I would look at the statistics and I'd be like, why are these three people, you know, this top 20% using 90%? And then the bottom half are doing nothing? Like, how could you actually get through the day and do nothing? It makes no sense to me. Like, there's so much upside to just even doing the most basic things with AI, you know, agent, agentic stuff, research.

• 28:50Speaker 00

  Just wild when people don't use it at all. That's very strange. All right, listen, continued success, Devin, and happy to be along for the ride with you and the team. More to come.

• 29:01Speaker 03

  All right, let's get started. Busy day. All right, yeah, we're doing, we're doing some Ask Jasons. We got some live callers already in the waiting room. So I say, let's, let's admit our first caller. Jason, I believe you actually know our first caller. We're talking to a founder. His name's Matthew Kerbis. His company is Prakti. I believe you may have thrown a little cash his way. Let's, let's, let's hear his question.

• 29:25Speaker 00

  Maybe, who knows? I'm throwing cash everywhere. Hey, Matt, how you doing? Hey, Jason. Hey, Lon.

• 29:30Speaker 03

  Hey, how's it going?

• 29:34Speaker 03

  Okay, thanks for coming on the show.

• 29:36Speaker 04

  Yeah, yeah, you ready? You ready? All right, let's do it. So I actually, just this morning, was listening to This Week in AI. I heard Lon ask a question from the Financial Times about the AI wrecking ball fracturing the billable hour fee model. So, Manifest CEO Dan Mission said all professional services will be outcome-based pricing in a couple of years. Scott Stevenson agreed, but Jason, you said you were skeptical that outcome-based pricing was the way to go. I'm summarizing here for people that didn't watch the show. But what you didn't answer was Lon's actual question, which I'm very curious about. Practically might have something to do with this. What impact do you think AI is going to have on the billable hour for law firms, professional services in general?

• 30:16Speaker 00

  When you're an early-stage founder and you're just starting out, you're probably going to rely on a few different tools to run your business. And then you're going to try to duct tape them together. And that might be a fine placeholder until you finish your MVP. But this will get expensive and messy fast. When you're scaling, that's when you need Odoo. O-D-O-O. Odoo, the all-in-one management software that already has 16 million users across more than 170,000 companies. Odoo is bringing everything you need into one platform. That means your CRM, sales, your accounting, manufacturing, inventory, and of course, point of sale, if you have retail. All of that is right where you need them.

• 31:00Speaker 00

  And these tools are in constant communication with each other, so you don't have to log out of one system into another and then reconcile the information by using different apps and spreadsheets. Ugh. When you make a sale, you want that invoice created instantly, and then you want your inventory to get an update. If you're still cobbling together your back office across five different apps, get started today at Odoo.com/twist, and your first app is free. That's O-D-O-O.com/twist. When we had other technologies emerge, we didn't see the billable hour go away, right? So when the PC, the desktop PC, cloud computing, the internet, none of it got rid of the billable hour.

• 31:44Speaker 00

  People have time and they have tools. So the question is, is this tool so transformative that adding a person's time becomes irrelevant? Now, certainly for some documents, of course, yeah. You don't need to have an attorney to sign a convertible note anymore. You don't need to have an attorney to sign up for a trademark anymore. You can do a lot of that with services. So those billable hours go away. But for experts using the tool, I think they'll just be able to deliver more at a lower price, which is what we've seen from accounting firms.

• 32:23Speaker 00

  It should, in terms of accounting, legal, and consultants, they should be able to perform better services faster. And instead of it taking 10 hours to do a particular research report, maybe it takes an hour. Or they still bill you for 10 hours and you just get a better report with better results. So I don't buy that the billable hour goes away. I just think humans move upstream and do more important work.

• 32:50Speaker 04

  I think we know that everybody's subscribing to AI and asking for legal advice. And so rather than outcome-based pricing, I actually think the subscription model is going to replace the billable hour in a lot of instances. What do you think about that?

• 33:02Speaker 00

  We've seen it before, where people offer a design subscription. You sign up for a subscription, you get as much design as you can eat. They'll just make logos for you all day long. And that typically happened with a different technology. Teleportation. If you could have designers in South America or India getting paid a buck to five bucks an hour versus a design studio charging 50 to $150 an hour here in the United States, you could do that geographic arbitrage, and it would feel like it was unlimited. Of course, it's not unlimited. If you say, "Give me a million logos," they'd say, "Well, we can't do that." It's reasonably unlimited on a subscription basis. So sure, some people might use this opportunity to get you to subscribe, but at the end of

• 33:47Speaker 00

  the day, the business owner's going to have to look at it and say, "Well, how much did you use and how many hours did that take?" Independent of how good the LLMs get. So you'll still have people who charge by the hour. You'll have people who charge by the project. Sometimes people come in and say, "Hey, I make 10 logos a year. I charge $50,000 per logo. I am a world-class designer, and I like to meditate for 30 days on your logo and do seven meetings." And you say, "You know what? I love it." People still will spend that kind of money on a dress. And you'd say, "Well, if fabrics and machines and sewing and all this stuff and design

• 34:26Speaker 00

  has been commoditized, why should a dress for, I don't know, the Met Gala cost 50 or $100,000? Why should people pay this amount for a wedding dress?" It's because they want to. They're opting into it. They want to have that inefficient experience. And that's, I think, a large portion of what happens in business. You're paying for the person to take ownership for the process and for their experience. So what is an audit? Could an audit be done of the books by AI? Sure, of course, certainly. And then could agents then go participate in the audit? Of course. You still want to have a human in the loop who says to you, "When you get sued, you

• 35:10Speaker 00

  can then refer them to me that I audited your books. And when you have a shareholder lawsuit, I will go testify or be otherwise available." So I'm not buying that the hourly goes away, but certainly it's going to change dramatically. And what people charge for could change dramatically.

• 35:26Speaker 04

  I think lawyers didn't ditch the billable hour before because there also wasn't a technology solution that made it easy to do so. So anyway, might be working on something like that.

• 35:35Speaker 00

  Yeah. Good luck with it. Great to see you.

• 35:38Speaker 03

  Thanks for calling, Matt.

• 35:38Speaker 00

  Good job.

• 35:39Speaker 03

  It reminds me a little what you're saying, Jason, about Rick Rubin. You following that whole debate? Because he doesn't, Rick Rubin, the great hip-hop producer, he made like "Wise Is to Ill," "Raising Hell," "Red DMC." He doesn't use the equipment. He's not like a trained engineer. You're paying him to sit there in the studio and listen to your music and just have taste and opinions. He goes like, "Do this, it should sound more like this, I don't like that." That's it. And he's making millions of dollars.

• 36:06Speaker 00

  There are a few people on the planet like Rick Rubin, but there are some. And so you will pay for that level of person vis-à-vis my example of the Met Gala ball, or in this case, Rick Rubin, or an interior decorator for your house. That was when I hit a certain level of wealth, all of a sudden I was introduced to this concept that you hire an interior designer, they buy a million dollars in furniture, and then put 20% on top of it. So you pay $1.2 million for them to design your house, and they charge you a $250,000 fee. So now you've got a $1,000 square foot house, and you're paying, some people pay $500 a square foot or $1,000 a square foot to do the interior of it.

• 36:50Speaker 00

  And you're like, "Wow, rich people are crazy." But of course, if you have money and you don't know what to spend it on, maybe you want to make your house so beautiful that when people come over, they go, "Wow, this is like coming to a museum."

• 37:01Speaker 03

  You want to get into architectural digest or whatever, maybe.

• 37:04Speaker 00

  You know what I want to get into? I just want eight hours of great sleep, and I want to go to Japan and ski and have the perfect tonkatsu. Like, that's what I'm into. I'm into the experience.

• 37:15Speaker 03

  Yeah, I agree. I'd rather get the tonkatsu than the nice house. Okay, we've got our next live caller. Are you ready for it? Bruno Vilela. Bruno, come join us and ask your question.

• 37:27Speaker 00

  Hope we're screening these, Bruno.

• 37:29Speaker 03

  We got a room. We got Zach in a room. He's checking these guys out.

• 37:32Speaker 05

  Hi, guys. How's it going?

• 37:33Speaker 03

  Hey, Bruno.

• 37:34Speaker 00

  It's going great. How are you?

• 37:35Speaker 05

  Good, good. First time calling. Thank you for taking my question. I appreciate it. So my question is this. Microdramas, okay? This has been a form of entertainment that's blowing up out of Asia. So they basically take like one or two hours worth of content. They split it up in like 30 to 60 episodes of two minutes each. And then they set up like a subscription package where you can watch like five or six episodes for free, and then you go into a subscription package. And they used to be filmed using live action, right? Up until six months ago. And now with the advancement of CDEN 2.5 and being able to drive comfy UI using agents,

• 38:16Speaker 05

  people are starting to build these standardized production pipelines to produce these at scale. And I wonder if you see this as a vibrant new ecosystem or just like a quick fad?

• 38:27Speaker 00

  It's a great question. It's not for me as a medium, but I do think people sitting on a train who might have otherwise been home, watching a soap opera, they seem to love these cliffhangers. It's not super interesting to me because I grew up on...

• 38:49Speaker 00

  You know, films and I grew up on TV shows and I think the TV shows are more appealing to me, but I could certainly see the appeal to certain people who maybe they're doom scrolling and they get tired of, I don't know, just clips from old movies and weird AI slop and they want to follow interesting characters. It does seem to be sexy dramas intended for women is the first one that took hold. I'm interested to see if they can make action heroes, et cetera, and make a one click for men. And I don't have a deep enough experience in it, but last time I was in Hollywood, a very famous studio director was doing these kind of cliffhanger shorts or was,

• 39:33Speaker 00

  you know, looking to pursue it. I think it's an interesting medium for testing IP that then could go to other mediums. So that to me is the most interesting part about. But we have Lon Harris here. What do you think Lon of this medium?

• 39:45Speaker 03

  I think what's so interesting is watching this evolve. And I actually pitched a microdrama to Snapchat several years ago that they didn't pick up on when this was all first gaining steam. But I feel like what happened was on YouTube, they used to have these like faked clips where they would make it look like they were filming a real dramatic encounter, two people fighting on a train or in a restaurant or something. And then people started figuring out that they were faked. And what we realized was, nobody cares. If it's, if you're just scrolling and you're just flipping between channels, you're not as caught up in what like old folks like me are when you're watching TV or like, is this real? Is this fake? Is this just for the cameras? Like, everything is real and fake or in between and nobody cares anymore. So yeah, these like

• 40:26Speaker 03

  brief scenes that you just write to be as dramatic as possible, and then it's on to the next super dramatic scene. Like, I do weird, it's not for me, just like Jason said, but I do weirdly understand why this would be appealing to people who would like, that was always your entertainment was just flipping between multiple channels and multiple feeds and just scrolling. So I, I, I think it's really like fascinating. Like, I have watched a bunch of these like weird AI-generated romantic dramas that are just popping up everywhere. And they're huge. I mean, hundreds of millions of views on some of these things. It's a really fascinating weird.

• 41:00Speaker 00

  Where on TikTok they have hundreds of millions of views, YouTube Shorts? Where are the hundreds of millions of views for this? Because I am, and then there's like, I guess there's dedicated apps, Real Shorts might be one of them.

• 41:11Speaker 05

  TikTok has their own app for this, just for microdrama.

• 41:14Speaker 00

  Pine Drama is TikTok's.

• 41:17Speaker 05

  And, and the thing, and the thing with this app is that it offers like different types of monetization. So you can do subscription, you can do like on-screen ads, you can do a whole bunch of, like it gives the, the, the makers like several avenues for monetizing the production.

• 41:30Speaker 03

  It is also one of those AI era things, like there would be no practical way to do this if you had to make sets, if you had to make costumes, you've had to cast, there's tons of characters. It's only possible now because people can go into See Dance and just say, I want, it's a royal ball in the 15th hundreds. And like, they can just set all that stuff up as the parameters.

• 41:50Speaker 05

  It's big on like, science fiction too. They have lots of like, like medieval Chinese, like empire drama, like princes and queens and dragons and magic. And they're going full on on it. Like, it's not locked to just one subgenre, you know?

• 42:06Speaker 00

  I do think the more interesting thing to me is what will be the Pixar of AI video creation. So right now, most of the AI doesn't cross the uncanny valley for me. They're kind of fun CGI-ish, you know, you know, little appetizers, little junk food, you know, it's like having like a Filet-O-Fish or something, or a couple of bites of a, you know, McDonald's apple pie. It tastes good while you're eating it, but you don't feel great after having consumed it. I feel like it's just slop, like junk food. But that's kind of how CGI started. You would watch these little shorts at Siggraph and every year they got a little bit better, a little bit better. And then finally

• 42:48Speaker 00

  you had Toy Story. We're going to have a Toy Story moment. Jeffrey Katzenberg is going to be the one who figures it out, I think, because he did Lion King and Shrek and so many other seminal works. And I think he understands how to hire really talented people who know how to write scripts or, you know, musical numbers, character development, story arcs, villains. And then I think using the AI constrained with existing tools is going to be the big win. So right now, you're just basically creating 3D versions of people in CAD, I guess, would be the best way to describe it. These 3D models doing motion capture and then painting on top of it and using technology to

• 43:30Speaker 00

  produce films quicker, right? That's what Pixar does at its essence. There's going to be an AI version of that. The AI tools and the existing Pixar tools are going to collide. And it won't be just type a prompt and say, make me a Pixar film. It'll be, we have this character already. We've already sketched the character out. We know a lot about it. Now we just want to put the character underwater and have it in a scuba outfit. And, you know, here's what we want this, you know, new environment to look like. And maybe it's just really good at making environments for the characters to be in. Maybe it's good at creating characters.

• 44:04Speaker 05

  Well, in a way, that's what comfy UI is. I, I worked at New Hollywood for 12 years. I have like three Academy Award nominations for films that I've done in the past. So I, I know what these productions are like. And comfy UI is exactly that. It's basically a production pipeline for, for AI-generated video. The, the main advantage now is that you can just plug it into Claude code and let Claude do the, the building the pipeline.

• 44:28Speaker 00

  And in comfy UI is public, open source, right?

• 44:32Speaker 05

  Yes, it has, it has an open source version that you can download and run local, or you can run the clouds, the cloud service too, and plug directly into whatever video model you want.

• 44:40Speaker 00

  Yeah, very cool. All right. Great question. And good luck with it. Yeah, cheers. I, I am interested in as a way to test, I think, IP. I think it like, I've always thought if you were going to create the next Spider-Man, maybe it starts as a microdrama and you kind of get some reps in, test some characters, delete the stuff off the internet and then move on.

• 45:01Speaker 03

  And that's what Marvel Comics sort of was in the 60s. They could publish a few issues of something. Stan Lee and Jack Kirby had a new idea. Let's make a comic out of it. And then, you know, they'd run three or four issues. And if the people weren't interested, okay, let's move on with it. That's how all these characters came to be. There were a whole bunch of other characters that never became Spider-Man. Spider-Man is just the one like kids started buying the comics, so they started writing more issues.

• 45:22Speaker 00

  Yeah, I've been watching this trend on Instagram, this guy Andy Park. You can pull up his Instagram account. And Andy Park was like, one of the top animators or ran the animation at Marvel. And they fired him. And they fired like the whole team. And you're like, what? How, how does a money printing group like Marvel get rid of the soul? Yeah, like, these are just animators?

• 45:50Speaker 03

  Like, you get rid of the top 30 animators? His work was actually like, he's one of the main guys who was like, drawing, like, here's what the MCU should look like and integral to the designs of so many of these iconic characters and their movie suits and design. I mean, yeah, here's, you know, Wolverine and Spider-Man. And I mean, so integral to creating these images that we now have of how these characters look in movies. Again, Deadpool, I'm sorry, excuse me. And, and, you know, like, just to, one of the, one of the real key guys behind the visual identity of Marvel Studios. It's crazy that they let him go.

• 46:25Speaker 00

  Anyway, I reached out to him. I was, I was interested in hearing what his start, startup plans were or what his next plan was because he's been talking on his Instagram about what he's going to do next. Because I guess when you hit the peak of the mountain top, like, you're the guy in charge of the visuals at Marvel and then they go in a different direction and your whole team gets canned. Like, man, that's a revenge shirt I'm waiting to have. So if anybody knows Andy Park art on Instagram, give him my phone number, tell him to DM me. I DM'd him on Instagram. I was just like, anytime I see somebody with incredible talent, who's not an entrepreneur, I just think, man, it's a one in a hundred chance I could get like an Andy Park

• 47:07Speaker 00

  to do a startup. But what if he said yes? What if he's like, yeah, I would like to try building a startup, you know? So you take an Andy Park, you put him with this, you know, new concept of microdramas, which he might think is completely cheesy or whatever, but maybe there's something with that energy and his energy and, you know, he's, he's got all these connections. And then once I followed him, I started getting all the other comic book people. Man, comic book people is, that's a tough grind.

• 47:34Speaker 03

  It's tough. I mean,

• 47:35Speaker 00

  They're not making a ton of money in the comic book land.

• 47:37Speaker 03

  It's, it's, it's one of those like, you know, it's, it's feast or famine. Like, the top 1% of a percent are famous and we all know them and celebrate them and they're icons in the industry. And then everybody else is just like a constant grind. Where am I going to publish my next book? Where, you know, who's going to listen to my ideas? For every like Robert Kirkman out there, there's like a thousand struggling artists and writers. And it's, it is really tough. It's a tough industry.

• 48:02Speaker 00

  Uh, let's keep moving.

• 48:03Speaker 03

  We've got Josh, I believe, is waiting in the waiting room. Send in Josh. He's next on my list.

• 48:09Speaker 01

  Historically, investors have tended to prefer founding teams of two or three people over solo founders. So with AI now letting one founder do the work that used to require a much larger, you know, scaling team, are you seeing that bias change at all?

• 48:23Speaker 00

  No. So the issue isn't the efficiency of one individual. We've always had people who are, you know, 100 hour a week killer solo founders. The problem is, at the early stage, there's so much work to be done. And typically, the task switching is too hard for one person to do. For example, applying to get into an accelerator. And getting product market fit. Getting product market fit and hiring. Hiring, getting product market fit and raising your seed round. These things take so much energy that most humans cannot do both. Even as myself, as a solo founder, I had a hard time getting pulled in different directions.

• 49:07Speaker 00

  Lon, so at firsthand, you know, you're trying to get product market fit. You're trying to raise money. You're trying to do hiring. It's very hard. And then for early stage investors, if you have the opportunity to invest in a team of three killers, and then you have another team of two killers, and then another team of one killer, and all six are equal. In other words, you put all six in a bag, you shake them up and you pull them out. You make a team of three, a team of two, and a team of one. You would invest them in the order of three to one. Why? Well, because you have three founders who don't need to take a salary, who are super vested, and they're going to just get further than the two and the one. So in the question, you have to ask yourself from the investor side,

• 49:50Speaker 00

  if I have access to a three person or a two person killer team, why would I invest in a solo founder? What would the point be? There is an exception. Solo founders who are Mark Pincus, Elon Musk, you know, Evan Williams. Pick somebody who previously had partners, now has money, you know, now is incredibly strong. Travis Kalanick, like they can skip that step, right? Because they've earned it. They have teams of people who loved working for them. You know, they can get that group of people to come back and work for them again. So that would be the exception. It is not going to change just because of the AI tools. What will change is your ability, Josh, to stand up a product,

• 50:31Speaker 00

  say annotated.com, get it to product market fit on your own. Now, if you have product market fit and your consumer product's growing 5%, 10% a week, week over week, or 10% to 20% month over month, and you're a solo founder? Okay, now you've just eliminated the product market fit risk. So you will be able to raise money. So what risk can you eliminate? With three co-founders, you're eliminating one co-founder quitting risk, right? And the company shutting down. If you have product market fit and you're growing, you've eliminated product market fit risk. If you have sales and you've got a great sales person and you're selling, you know, $1,000 worth of software a week, and next week it's 1,100, 1,200,

• 51:16Speaker 00

  you've obviously solved the sales problem. So that's what you're trying to do as a founder. What can I eliminate from risk? And as I eliminate risk from this story, then my valuation goes up and people's propensity to invest goes up. Make sense?

• 51:34Speaker 01

  That was a brilliant answer. Thank you so much.

• 51:37Speaker 00

  Thank you, Josh. I appreciate that. This is the kind of question, this is the kind of reaction to a question I want to have. Anything I missed there, Lon, or any follow-ups?

• 51:43Speaker 03

  I mean, I thought it was great. I'm going to cut this and we're going to make it a tactical, practical blog post for Substack. That was a perfect answer.

• 51:49Speaker 00

  There you go. Tactical and practical is what we try to do at the This Week in Startups newsletter. So we're going to have this paid newsletter. We do have a paid newsletter for founders. Basically, I've challenged Lon with what 100 things a year can you charge $100 a year for? That people will say, that's worth $1 each. So I think 100 tactical, practical tips selected to a week, but that would be worth $100 subscription. So I'm charged Lon with soup to nuts. Where can people go to sign up for this twist?

• 52:19Speaker 03

  You go to TWI Startups. That's This Week in Startups, TWI Startups.substack.com. That's where you go to sign up. There is a free version. You could sign up for free, try it out, see what you think for a few weeks, and then only $10 a month, folks. $10 a month for all this.

• 52:38Speaker 00

  Oh, and you're going for 250 tactics a year to be a better founder.

• 52:40Speaker 03

  That's what you told me to do. That's what you told me to do.

• 52:43Speaker 00

  I think we should make it $250 a year, $1 per tactic. But we'll, we'll start with $100 a year for now, and then we'll raise it. All right. Another amazing Ask Jason. If you would like to be part of the next Ask Jason, tell them, Lon, how they can participate.

• 52:57Speaker 03

  If you've got a burning question for J Cal or me, mostly J Cal, we want you to go to thisweekinstarups.com/askjason. That's thisweekinstarups.com/askjason. That's the form. Fill out your question. We'll get you on the next episode of Live Ask Jason.

• 53:13Speaker 00

  See you next time. Bye, folks.