Welcome back. You're watching Squawk Box Asia. While tech and AI startups continue to take up the lion's share of venture funding, investors are getting more selective about where that money goes. Earlier this week, we spoke with Bond Capital's Anu Hariharan. He says the question is no longer just about software, but whether a company can truly compete at the frontier of AI. Take a listen.
I think it's a re-framing of the question away from are you a software company or not to are you a frontier technology company or not? You know, for the last 10 to 15 years, software companies were frontier technology companies. So, there was a lot of investor appetite for it. But now, we have something new called AI and it's being adopted by enterprises and that is the frontier. So, if you're a software company and you're able to evolve towards AI and incorporate this into your business, you're going to be just fine and you will be a frontier technology company. But just by being a software company, you don't have some God-given right to retain all of your customers every year and have 100% revenue retention.
Alfred Chuang is the founding managing partner at Race Capital, an early-stage venture capital firm based in Palo Alto, California. Of course, specializing in enterprise and infrastructure investments including Databricks, Goodnotes, Solana, and Grok. Alfred is also known as the tech pioneer who sold BEA Systems to Oracle for 8 and a half billion dollars in a high-profile hostile takeover battle back in 2008. Now, let's Alfred get your thoughts on what's going on in the tech world, AI world. A lot of questions, right? Alfred, in terms of where OpenAI goes, where Anthropic goes, and the Journal report really rattled a lot of investors in the public market just overnight, you know, suggesting that they missed the internal user growth and revenue targets. So, what are you making of all these volatilities and headlines right now?
Good morning, Shery. Thank you so much for having me back. It's always to be great to be in Asia. I think one thing that people have forgotten a little bit about AI is we're very early in the cycle. AI is 3 years old. And despite I think we saw some huge growth. I mean, ChatGPT has racked up 800 million users in the last 3 years. These are astonishing numbers and we have never seen it in any of the technological era. We're still very, very early. And I think the same report also said they are still sticking to their annual revenue target that they have. So, we're going to have to expect these companies are new in what they do. They're going to have some blips in terms of quarter-to-quarter-to-quarter performance. But I'm actually very excited, but one thing to remind I think everyone is if you look at what happened to the last generation of technology, let's say in the web, at the peak of the market, just I would say within 20 blocks of my office, there were 18 search companies and there's only one left. So, I think this is still very early stage in terms of what the competitions are doing to try to become that relevant player in the large model and where they have huge incumbents like Meta, like Google, and like Microsoft. So, we already have a lot of players that are very big and very entrenched into the customer base that are competing in this field.
You've seen so many different tech cycles, mobile, SaaS, internet. I wonder what people are getting wrong and right about this in your opinion. Is AI different in this cycle and if different, why is it different?
This has to be the most profound technological shift that I may have ever experienced since I started my career in this field. I think the reason is historically for almost up to this point, every single applications are written in a form. So, if you take an Uber, you're filling out fields of where you are, where you're going to, and what type of car do you want, and you submit a request to the server, and they send back all these are the cars available. This is the car available to you. What impactful in AI would be, it will be the first time that we're going to have a brain that will be embedded inside our application that can think for you, that could derive and complete tasks for you. And so, the modeling of a workflow is now going to be natively done. I think this is where we're heading to and then it's going to start automating a lot of things that we do. And in the future, it's going to Well, we already have some reasoning and reinforced learning in AI models. So, you'll be able to come up with tasks that you haven't even thought of and it will go and get those done for you. We never have anything like it. So, then our workflow can easily be understood by the AI and it'll be able to automate from there.
Yeah, so that's exactly where we're going to go because you're focusing on enterprise AI and a lot of software-related concerns and you knew that I was going to go there. SaaS-pocalypse. I know it sounds very dramatic, but that's exactly how, you know, the sentiment feels like right now. How do you think about that? Because some are pushing back saying, 'Look, it's Microsoft. They got the clients. They got the base, the data. It's not going to be disrupted. This is overdone.' How do you react to that?
I would say I've been waiting for this moment pretty much in my entire career. During much of my days in directly operating companies, we were the biggest supplier in terms of middleware software to these large SaaS companies. Almost all of them that are, you know, they're huge in business today. I think for the longest time, typical legacy implementation Well, implementation in enterprise for any IT type of application, we generally don't throw anything out. We have things that have been running for 20, 30 years. We kept them because the fear that in the event that we have to reconstruct a trail of events, they're available to us. Because we don't have the type of intelligence to go back to look at the old code and understand what exactly does it do and what are we still using it for. I think we may have missed a actually very important watershed moment just a few months ago that Anthropic has shipped Claude Opus 4.6. Why is that a watershed moment? It's for the first time that I saw light that now you have artificial intelligence technology that can go in and understand what an old application actually does and what are we using it for. From then, you can reconstruct new code to replicate what it does and it trimmed down its footprint dramatically, generate test cases, and then ensure that it does what it used to do. Now, we're not quite there yet, but it's shown that it can be done. So, yes, I think these legacy SaaS companies will have to rethink what their future strategy should be. Either they will have to go all in to adopt and this may require rewrite of what they have to fully embed AI into the new generation application, allow this mutation using AI for workflow automation to happen, or they can be left behind. I think this is serious.
