alt Hacker NewsVCs think, 'Apps are risky, infrastructure is safe,' so they invested in AI infra.
"infra is safe" Hmm, but that wasn't a good idea. because if an open source infrastructure project like TensorZero gets shut down this quickly, won't they start to realize that those investment theories are also risky?
The difficult thing about AI infrastructure is that, unlike other industries, it will not become fragmented. It will likely remain tied to specific big tech models. What does this mean? It means that because AI models are not yet standardized, the infrastructure itself is actually riskier. In other words, the privatization of standards is happening.
The challenge with AI infrastructure is that an independent, stable standard layer has not formed, unlike in other software infrastructure markets such as databases, web servers, cloud, and containers. Over time, those ecosystems developed relatively standardized interfaces and operational layers. But the LLM ecosystem is still evolving rapidly. Models themselves change fast, APIs differ, pricing differs, context windows, tool calling, structured output, evaluation, fine tuning, caching, routing, everything keeps changing.
So even if an infrastructure startup tries to build a common abstraction layer across multiple models, before that common layer can stabilize, big model or cloud providers like OpenAI, Anthropic, Google, AWS, or Azure can just absorb the same functionality directly. In the end, AI infrastructure is at high risk of becoming an attached feature of model providers rather than solidifying as an independent layer.
But if a startup that raised 7.3 million dollars fails this quickly, who would trust and invest in such things? That aside, it seems AI startups are all the rage these days. I also want to learn AI and get funded like that. Does anyone here trust me enough to invest? About one hundredth of that would probably be enough
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A few comments.
> VCs think, 'Apps are risky, infrastructure is safe,' so they invested in AI infra.
First off, this isn't even infra in the infra sense of the word. Infrastructure implied something physical, a pure software product can almost never be considered 'infra'. A tool maybe, but not 'infra'.
VCs can also be irrational and driven primarily by personal connections rather than reason. I didn't do a deep dive in this project/leadership, but often who you know is some important than what you produced. There's a reason why a lot of VCs go for the old motto of "I'd rather invest in an A team with a C product; than invest in a C team with an A product".
I also believe the same. Many VCs are obsessed with moat that they clearly got wrong. To me the value created at app layers are so much that gives them the flexibility to diversify their infra layers. Good harnessed do not depend on a specific model provider or memory layer or etc that when it is taken down like anthropic fable they get no risk exposure. Many even after growing train their own model like what cursor did with composer. There’s many more examples in other verticals like manus, superhuman, fireflies, lovable, replit, cursor, nouswise, cline windsurf and kilo but many are concentrated in coding because again I think VCs have preferred this definition of moat.
Infra is perhaps somewhat safe but realistically it's a really low margin capital intense business long-term unless you can lock-in customers with hundreds of services like AWS. So not a lot of space for a huge ROI.
> are all the rage these days
Are they? Overall it seems kind of tame compared to 2020-21 since VCs are somewhat risk average outside of a few outliers. Funding looks much more concentrated these days.
Tell me you haven't talked to a VC.
A better model for VCs is: companies are finding tons of budget to allocate to new AI spend. Besides the labs, who is going to be able to capture some of that spend while they're actively looking to spend it?
Nobody at the seed stage is investing in things they think are "safe". They are investing in things they think have huge upside.