Enterprise AI workloads will split across proprietary and open-source models
Matt Murphy · Will Open-Source Threaten Anthropic's Business & Do Margins Matter in a World of AI | Matt Murphy · Jul 27, 2026 · at 26:37
Matt Murphy is a partner at Menlo Ventures. He is forecasting how corporate AI infrastructure and vendor selection will evolve as companies optimize for cost, speed, and intelligence.
0:00 / 0:33exact quote · 33.0s
▶ Watch the full episode on YouTube → 720p mp4 · rendered on demand · StarZero watermark
“So I think, you know, you're going to have the combination of something like that, a family of models from Anthropic, and then a set of open source models and things that you train with your own data, and you're going to look across that whole tapestry and say, hey, I'm using 50% this, 30% that, 20% this, and that's, those are the kind of optimizations that happen at scale, and that's the stage of market that I think we're just entering into, which makes it a lot more fascinating, frankly, because there's going to be so many Kind of second and third order companies that, that spike and take off versus, you know, the whole market being concentrated.”
quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →
More from Matt Murphy
Open-source models will not displace top foundation models like Anthropic
“I think the foundation models, let's say specifically Anthropic, have such special models. This can be hard for somebody to just kind of say, I've used open source with my data. It's going to be functional and positive for some amount of what you're doing, but…”
Small stakes in massive outliers beat high ownership in mid-sized exits
“You have to be in the big outliers to drive great returns, and you're better off being in them at a very small percent than owning a large percent of a company that exits for three to 500. Those just aren't going to move the needle.”
Lovable scaled from zero to $300M ARR within one year
“Where you see a company go from zero to something like three hundred million in a year. I think we intercepted them around, well, we kind of got, tried to get in when they were around 30, 30 of error, but we around, we did was around one 50.”
AI compute costs cap startup gross margins at 60% to 70%
“You know, a lot of companies, just because of the cost of computing inference, it's harder to say you're going to be an 80, 90% gross margin company anymore. But, you know, great companies are, you know, 60, 70% gross margin.”
Using Anthropic drives higher retention and revenue than open-source models
“What's happening is companies see this, like, yes, I can get lower cost, but if I use Anthropic, it actually increases my customer retention. I generate more revenue. I get users to Engage with the platform more. And that is what the data is suggesting now wit…”