00:11:01 · Adam Miller, Michelle Gilmore, Georgie Healy
[00:11:01] S5: Mhmm. [00:11:01] S1: Right? The possibility that there are enough factors that exist here. So I'm not sure we can rationalize or justify valuations that are created for the purpose of a construct that is they see in this context. But perhaps we could talk about the... Is it proportional to the opportunity that exists before us, which is global, which is a different pace than we've ever seen, which is talent being created faster than we've ever seen it before? What do you guys think about that? [00:11:36] S4: Microsoft's a trillion dollar company. It owns OpenAI. I think it could be a trillion dollar company. I think there could be multiple trillion dollar companies from AI. And I was a VC during a similar period. What did we see come through? Crypto? The metaverse? Some other bullshit? I'm not surprised they had down rounds, but AI, I feel that we can all agree on, has already transformed our lives. I would be surprised if we didn't have multiple trillion dollar companies.
00:12:08 · Daniel Palmer
[00:12:08] S3: I also think something we're seeing here that's potentially a little different from other periods of software is that a lot of the things being built now, I have a platform level where the TAM is massive, or they're sort of fundamentally shifting very verticalised industries in ways that make products that are actually way more horizontal, whether intentional or not, and therefore the average market I think these companies are addressing is actually a lot bigger than we're used to in VC and in tech recently. And so I think that makes a really big difference. I also want to add like, I think a really good point about betting on people, like we discussed earlier with Miro, that's particularly unique to AI, is that we're so early in this technology that the use cases are not actually clearly defined yet. I think even in Agencik AI, which my company focuses on entirely and has for multiple years now, still we're very slowly discovering the really key use cases for authentic automation. And so I think it is really important to have a good team, the right company set up that can move and adapt quickly, and you don't know what big new models coming out tomorrow, or new NCP self framework is coming out tomorrow, and so investing in people and investing in companies that have proven their ability to be really good at executing and really good at being nimble, I think is more important than ever in this current period.
00:13:49 · Adam Miller
[00:13:49] S5: Thanks for tuning in so far. We make these documentaries to uplift and celebrate startup culture in Australia. But apart from the documentaries, we've actually got a special offer for the founders that are tuning in up to six months free of Notion Business if you follow our link. This is the new Notion dashboard, which is tailored just for startups. It's got pre built AI agents, OKRs, calendar scheduling, product roadmaps, investor update schedules. This is all situated in one place just for start ups. We run our start up on Notion literally almost our whole start up and it's quite a lot of fun. You should too! So hit the link at ntn.so/satinandadam for up to six months free with a Notion business plan. This could save you up to 12 ks of tool costs. Which startup founder doesn't want that? And now, back to the video.
00:14:36 · Sachin
[00:14:36] S2: I think something that Adam and I have spoken a lot about is it's probably one of the most intense times ever to be a founder because like in no time in history have things changed this fast. Like new models come out and sometimes it changes a bit like a lot of businesses get eradicated, lot of businesses get built. In this kind of context of how we build great companies in AI, I think there's still a lot of question marks about where value will accrue. But I think a lot of people have started to kind of maybe confirm the thesis that a lot of the foundation of AI, the price will trend towards electricity. And a lot of interesting stuff will be built on the application layer. I still like, in my opinion, I think these companies are still going to be big companies in their own right. But what do we think about this thesis of AI becomes like electricity, and then it enables all these new worlds like light bulbs or electric cars or, you know, the things that electricity does?
00:15:32 · Michelle Gilmore, Sachin, Adam Miller, Xharmagne Carandang
[00:15:32] S1: I I think from an analogy point of view, this one makes me twitch a little bit because, if we transfer it into the application layer, what we're saying is that supplier A and B will both be able to just turn on a line bulb. Right? So AI is way more complex. But if we just do use that analogy for a moment, I think that it being available to anyone and becoming cheaper and a commodity, you know, if that... If we play with those notions, I think that's really interesting. And we're trying to understand what pricing looks like. You know, we don't have playbooks like traditional SaaS companies did. Right? I mean, I sometimes drool over the simplicity of a traditional SaaS company. Like, wow. That... I'm sure it was hard at the time. But as you said, this intensity, I think that there is no playbook, which is incredibly inspiring and exciting, but also we're trying to play with notions of will quality be the thing that determines a price continuum? You know, do I pay for higher quality, which means I am going to choose a different provider or providers? And in what context does quality matter and in what context does it not? [00:16:54] S2: I was thinking in what timeline? It's like sometimes I get myself in loops where I'm like, Oh, but we'll get to AGI of five years, and then I'm trying to figure out pricing in Asia, then I step back and I'm like, Oh, wait, this is the least of my worries. [00:17:08] S5: Yes. There needs to be some sort [00:17:09] S1: of discipline around how... When we go there and when we don't. But they are connected, [00:17:14] S0: I think.
00:17:14 · Xharmagne Carandang, Michelle Gilmore, Adam Miller, Sachin
[00:17:14] S0: I think. [00:17:14] S1: Right? And you do have to think in those concentric circles. At Juno, we are making bets on quality. So having done the job that Juno does for fifteen years, I'm fairly certain that I can make better subjective decisions on what good looks like in this context of interviewing humans. So doing user research, doing market research, having done that all over the world, I'm confident that I will make a better decision on that than someone that's got much more money than us, to your point, Xharmagne. I think that was a really interesting point. But how do we educate a market on what quality looks like in this context, and how do we apply values to that, and how do we do that really quickly? Right, so that we can stay alive and generate revenue and increase our valuation and keep growing. [00:18:09] S0: Yeah. Because what I like about this is that, say, it becomes a commodity, then we can focus on what actually matters, which is what is the customer trying to get out of it rather than we charge by tokens, whatever. It's like we charge, say at Lorikeet, if we answer the customer's question in a quality matter [00:18:27] S5: Yeah. [00:18:27] S0: Kind of thing. And that means our incentives start to align with our customers. I think that's great. [00:18:32] S2: Yeah. The SaaS incentives are just so you don't rip them out. [00:18:35] S0: Basically. Yeah.