Chapter 1: What is the main topic discussed in this episode?
Welcome to the podcast. I'm your host, Jaden Schaefer.
Chapter 2: What are the current trends in AI startup investments?
Today, I want to talk about what investors are doing in 2026 when it comes to investing in AI startups. And I think it's interesting because right now, investors are basically telling you what they aren't looking for anymore in AI SaaS companies.
It has shifted a lot, which is interesting for me being someone who has my own SaaS company, AIbox.ai, which I'm sure you've heard me talk about before, because we recently did an entire redesign of the platform where you get access to over 50 of the top AI models in one place for $8.99 a month.
Chapter 3: How important is workflow ownership in AI solutions?
But I think this is broadly speaking, pretty interesting and important for the overall AI industry, because what investors are looking for here, number one means this is what people are building. But this is also what we're likely to see more of when it comes to updates inside of the AI industry as a whole. So this is what we're going to jump into on the podcast today.
Chapter 4: What are VCs avoiding in AI startups today?
What I think is interesting is investors have poured billions of dollars into AI for the last few years. This isn't a trend that is slowing down. And I think all of this technology really has played a huge role in Silicon Valley's basically their priorities and a lot of what comes out of the global tech industry. I think even in a market right now that is obviously very obsessed with AI.
I mean, if you if you look at every basically every single company that is raising money now is no longer just a SaaS. It's like an AI company.
Chapter 5: What types of AI startups are gaining investor interest?
And so I think while every company has kind of added AI to their sales, like their pitch deck, basically for VCs, I think it's becoming a lot more selective on who's actually getting money, right? You can't just put AI on your pitch deck and get money.
So according to one of the first interviews or kind of data points I got on what VCs are looking at as far as investing in AI companies today that maybe they weren't in the past is from Aaron Holiday. He's a managing partner at 645 Ventures. And by the way, TechCrunch did a whole rundown where they interviewed a bunch of different people.
I'm grabbing some quotes there and also grabbing some data from the overall industry that we're tying together in kind of this episode in this report. But Aaron Holliday, he's a managing partner at 645 Ventures.
Chapter 6: Why are generic AI tools losing appeal to investors?
And he says that the category is still getting the most interest are AI native infrastructure. So that's vertical SaaS built on proprietary data. systems of action that actually complete tasks and platforms embedded deeply into mission critical workflows. So basically, in other words, products that own something really essential.
And there's a keyword I think he said in here that I 100% agree with. And that is, he said, AI that actually completes something. So, I think there's a lot of this, a lot of these startups that were like, hey, look, we have like a SaaS, we have a tool, and then we stuck ChatGPT on top of it. And you could chat with ChatGPT and it can give you like ideas about what you're looking at.
In my opinion, that's very, I mean, basically, that's just the original SaaS. It's not super interesting. It might give you like some ideas or help you troubleshoot or you don't need their customer support as much. But what I'm talking about when I see AI and what I think a lot of these investors are looking for is AI that actually completes something.
In the past, maybe I had to manually write a title and description for my podcast and
Chapter 7: How are pricing models evolving in the AI industry?
And today, AI can grab the transcripts of the audio file and do that for me. And if that's actually like accomplishing something for me, it's useful. Whereas if it was just like, I don't know, a chat bar on the side where it's like, you know, ask me what would be a good description for this. Type in your title and I'll give you some ideas like that is not useful.
It's not automatically doing something for me. And that example I just gave you is like very basic. I mean, I think ideally you would upload an audio file and it would fill out all of the data and automatically find the best time to post it and look at your calendar and blah, blah, blah, blah, blah. Like it's just going through and automatically doing stuff.
That is what they're looking for, not a chat bar on the side. Okay, so what are they less interested in? What are investors less interested in investing in AI right now? And what that is, is thin workflow layers. So generic horizontal tools, light product management software, and surface level analytics.
If an AI agent can replicate the core value quickly, I think investors are not seeing this as very defensible. So maybe even some of my previous examples weren't the greatest because In a sense, what they want tools to be able to do is have some sort of custom data set, some sort of deep integration into something that's super, super critical.
And it's not something that just like a chat GPT or Anthropic can replicate easily. And the reason being, Anthropic right now is rolling out all of these new tools, right? They're doing like Anthropic for finance and Anthropic for legal. And basically, you have a company like even Harvey AI, who's raised a ton of money. And I'm hearing, you know...
anecdotal stories from people who are saying like, you know, I've used Harvey for my law firm and now I'm using Anthropic just rolled out Anthropic for legal and I don't need this whole other tool. I just use my Anthropic account and all of a sudden this is, you know, just as good as Harvey. So It's really interesting what is actually being seen as defensible today.
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Chapter 8: What is the future outlook for AI startup investments?
So Abdul Abdirhan of F prime added that vertical software without any proprietary data moats is no longer super compelling. So they actually want you to have a data moat, maybe you ran a you know, an an FAQ legal website. So you have all of this data on, you know, legal FAQ questions. I've seen some startups do this.
And that is like a proprietary data moat where maybe you have, you know, information that no one else has. Or maybe you have information because you have a company and you can see what your users, you know, what their behavior is. And so that could be a proprietary data moat. But basically, you want some sort of data that your competitors can't just easily knock off and clone.
Igor Ryabinsky of Altol R Capital said that basically was arguing that shallow product depth is a really red flag, a big red flag. He said, if your differentiation mostly lives in UI and automation, that's no longer enough. The barrier to entry is dropped, which makes building a real moat a lot harder.
I think for new companies, that means that building around, you know, true workflow ownership and a really clear understanding of the problem from day one is super, super important. Massive code bases are not an advantage anymore, right? Just being like, look, we have this massive code base we've worked on for a long time.
Speed, focus, adaptability, all of those things, I think I would argue are much more important. And even pricing models are shifting a lot like these kind of I think there's a lot of software today that has like these really kind of set in stone pricing per seat or per subscription.
These are looking a lot weaker compared to the consumption based approaches where it's like, look, we just need to use like X amount of tokens every month, which is kind of the approach that I'm doing at AI Box, where you get an account and you can just get more tokens. The more you pay, the more tokens you get. We have a bunch of like apps and tools you can use.
And if you use them a lot, you pay a lot. If you use them a little, you can be on a low subscription tier and pay a little for them. Jake Sapper, who's the general partner at Emergence Capital, he's kind of trying to frame the shift that's going on right now. And he's like just showing you what it looks like through the lens of developer tools.
So he pointed to the contrast between Cursor and Cloud Code as kind of where things are going. He said one owns the developer's workflow, the other just executes the task.
um which i think is basically shows that increasingly developers are choosing execution over process right like they don't just want you to own the workflow they want you to actually get the thing done which is what cloud code is doing really really well right now it's the number one tool we use at ai box so the shift i think that we're seeing right now is a lot of big implications if agents are doing the work then a lot of the traditional kind of workflow stickiness is becoming a lot less relevant in the past getting humans to operate inside of your software
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