00:18:47 · Ev Randle, Molly O'Shea
That's largely abstracted, but you're still monetizing this thing which is based on inference, and what that allows is it removes any sort of rate limiter that you have on your potential to grow, and it's the enabler to these unbelievable revenue growth rates that we're seeing time and time again with all these new AI companies. [00:19:07] S1: What do you think is gonna happen with the proliferation of agents? [00:19:10] S0: I think, so obviously, it's interesting because on one hand, I think that, I always cringe a little bit whenever a word or a term becomes over product marketed, so know, FDE's is certainly a version of this, I think agents is absolutely a version of this. [00:19:31] S1: What about AI?
00:19:32 · Ev Randle
[00:19:32] S0: Yeah, well I mean AI, that's at least this umbrella term, but you know, it's like when, I think when private equity firms are telling all of their portfolio companies to say that they sell agents, that's when you know it's like okay, the term is cooked. We need to move on from this term onto something new or something different. I think all of that said, it is still fundamentally the greatest both product innovation and business model innovation that I think we've seen since the start of SaaS, and since the cloud business model. And the reason for that is because it is the underpinning of how we move to this idea of selling work or actually replicating what a human being is doing when they're trying to complete a task. And on the business model side, as I mentioned, it allows a buyer of software to move their mental framing from like, oh, I buy a license to oh, I buy intelligence on tap, or like a white collar activity on tap, or some activity that created some economic output for my business on tap via an API or via software product. And so it unlocks this new price for value equation for buyers that allow them to think about software and the budget that they have for software in a whole different way. I think one of the things that we got insanely excited about when we were first tracking the rise of coding agents was when Cloud Code, even when it was still Cloud CLI but when it became Cloud Code, we were talking with developers and companies within our portfolio, and they're like yeah, we have developers that are spending $3,000 per month themselves, like each on Cloud Code. So it's like wow, okay, that's $36,000 per developer, and oftentimes in the SaaS era, if you had a $50,000 ACV, that okay, but instead of having a $50,000 overall contract value with this customer, you were now getting that per developer, and it was still growing. And so it was just this idea that like wow, this could actually become not a 200 ks line item for the average company, but a $20,000,000 line item for the average customer and average company.
00:21:47 · Molly O'Shea, Ev Randle
[00:21:47] S1: Or for some. [00:21:48] S0: Or for some 500,000,000 a month. 500,000,000 [00:21:51] S1: a month. [00:21:51] S0: A month. That's a different era of technology, and so I think even though I'm so annoyed at the whole agent thing because now it's just the only thing that you can see when you go online, and it's been marketed to death, it represents the most important both like product slash technology, and then also just like raw revenue and business model shift we've ever seen probably in maybe the history of technology, and I think that was one of the reasons, and we can go into Gumloop if that's interesting. That was one of reasons we also got really excited about Gumloop.
00:22:25 · Molly O'Shea, Molly O'Shea
[00:22:25] S2: Sorcery is brought to you by Brex, the financial stack trusted by more than 30,000 companies, including one in three venture backed startups in The US. Nearly 40% of startups fail because they run out of cash. REX is literally built to help founders avoid that. Unlike traditional banks that let your money sit idle, chipping away at it with fees, REX is designed to help you spend smarter and move faster. Their all in one solution combines checking, treasury, and FDIC protection into one powerful account. You can send and receive money globally at lightning speeds, get 20 times the standard FDIC coverage through their partner banks, and even high yield from day one. With same day and even same hour liquidity, access your funds anytime. Companies like Scale AI, DoorDash, Service Titan, HIMS, Anthropic, Flexport, Robinhood, and Plaid trust and use Brex. Start today at brex.com/sorcery. That's brex.com/sorcery. Turing is training the next generation of AI with tasks that require real expertise and real world judgment. That's why companies like NVIDIA, Anthropic, Salesforce and Gemini partner with Turing. Turing builds realistic reinforcement learning environments and data systems based on real operational traces, the kind of infrastructure Frontier Labs need to train superintelligence. Visit turing.com/sourcery. [00:23:55] S1: Yeah, explain Gumloop.
00:23:57 · Ev Randle
[00:23:57] S0: Yeah, so Gumloop is an independent third party software platform that does a collaborative AI agent and AI automation canvas for enterprises. And what that basically means at like a very simple level is that all of, like we first saw it in coding and coding agents where developers, like with OPUS 4.5, coding agents got to a place where developers felt like they could do a vast majority of their day to day job by offloading the work, not just like tab to complete like we saw with Cursor, but like actually offloading a bulk of their work to coding agents in Cloud Code Codecs or Cognition or any of these other products. And the thesis was what we've seen in code is going to happen in most white collar job functions, and eventually probably most blue collar job functions as well, but the average white collar worker is going to be doing an immense amount to automate the rote redundant work in their day to day via agents and via AI automations. So that's what Gumloop provides. It's a platform for enterprises and every single employee within an organization, not just developers, not just salespeople, not just marketers, every single employee within an organization can create, can iterate on, and can collaborate on both just like very simple automations like you do with like a Zapier back in the day, but then also full on AI agents that they can build and use cross functionally across the organization to do all sorts of things, both triggered by someone talking to them in Slack or Microsoft Teams or running in the background without anyone having to trigger them at all. And obviously there's going to be, and there already are great products like Cloud Cowork and the news around OpenAI combining Codex and ChatGPT into a productivity product that are gonna have big businesses in this general category as well, but we think that there's an immense amount of, and this goes to, you talk about how routers are becoming a popular term as well in the agent space, we think it's really, really important that there's a third party independent vendor for two reasons. One is which the models are actually pretty jagged. The models at any given point are good at different things, and so Gemini is like the best multimodal model. Claude typically has the best coding model.
00:26:10 · Ev Randle, Molly O'Shea
Although now a lot of people think GPT 5.5 is actually better than the latest Opus model at coding. And then you have open source models which typically have immense value for the cost that you're paying for the inference of those models. And so there's great models for all these different tasks, and you do need to have a third party vendor that's sort of watching out for the customer and not just saying, know, in some of these enterprises, you have employees checking the weather with Opus four point eight. [00:26:40] S1: I know. I well, I was talking I've talked to a couple of companies about this already, and, like, how do you control spend on on your tokens and the token maxing debate and all that kind of stuff? Because, like, I know when I'm like prompting Claude or whatever I'm using, it's usually the dumbest, like it's not, it's a small fix. I could probably just go in myself, but look, the tool is magic. So I want to do it myself and make that small fix. But you do that over huge pieces of content or whatever [00:27:12] S0: And thousands of employees. [00:27:13] S1: And thousands of employees, and it clearly aggregates very large bills and great revenue sources for something. [00:27:18] S0: That's right. I'm like asking Opus four eight what I should have for lunch. You know, it's like, it's probably not that's probably not the best use of of our inference budget.