We started the company two and a half years ago, and raised $7.3m in 2024 (announced only almost a year later). We've spent less than half of this amount.
Earlier this week we came to the difficult decision to wind down the project. The open-source repository remains available on GitHub (Apache 2.0) but won't be actively maintained by the team moving forward.
There are many factors at play here but if I had to pick one... an open-source company has to find product market fit twice: first for the OSS project and again for a commercial product. The AI market moves very quickly so it's easy to take a step in the wrong direction and fall behind.
I might publish a long-form reflection when the dust settles.
It might come off as trite, but I genuinely am sorry that things didn't pan out for you
Very early in my career I used to believe that I or anyone else could be a CEO.
It wasn't until working with tiny teams where the CEO/founders devoted everything in their life to the business -- often at the expense of hobbies, romantic relationships, and any shred of free time -- that I realized true CEOs are a rare breed.
When are you ask things like "what happens if the product fails?" the answer would always be "It won't."
They both relentlessly believe in, and put every ounce of energy toward, their vision because anything less would not suffice
Again as trite as it sounds, I empathize with these people in that to them losing their vision felt like losing something dearest to them
what do you mean a true "CEO"? Obviously there is a big difference between what someone like Satya Nadella does and what a CEO of a 10-person firm does.
In smaller startups, everyone is directly involved and has to punch above their weight to pull through, not just the CEO.
Also devoting everything in your life to one thing is not a mark of intelligence or skill. It is a mark of dedication but by itself means little.
And yeah, not everyone can be a CEO because most business fail very quickly. There is always an element of luck in those that survive.
But the idea that you devote 24x7 of your life hence you must be a good leader is not accurate. In fact, if you press this culture downstream, you'll tire your workers and the rest of the team.
There are personality traits inherent to successful CEO's that are in-born.
For example: I cannot imagine being a successful touring live performer. I am an introvert, I keep a rigid schedule so travel throws everything off, can't keep myself awake very late...
Could I perform the functions of a live performer? Yes, though no matter how much I "tried" the mismatch between the job and my natural tendencies is a recipe for failure.
> not everyone can be a CEO because most business fail very quickly
Not everyone can be a CEO because not everyone is cut out for it. If you think you could step into those shoes, you're either built different or delusional.
> For example: I cannot imagine being a successful touring live performer. I am an introvert, I keep a rigid schedule so travel throws everything off, can't keep myself awake very late...
These are not examples of in-born traits. While I agree that not everyone has the motivation to become a CEO, I would disagree that a person cannot learn and adapt.
> first for the OSS project and again for a commercial product.
Is there a way to reach out to you as I would like to hear what you have to say about what I am working on. You can update your HN profile to include contact information or you can reach out to me using my HN profile.
I'm basically working on a portable intelligence layer for AI that I will be open sourcing and the commerical product will be to make the intelligence layer even smarter. I can share the Show HN post that I am working on that better explains the value proposition and would love to learn any lessons you have gained while trying to sell AI tools commerically.
Edit: In case somebody calls me out it. I didn't want to use the `tensorzero` email domain incase the domain was going to become defunct soon.
> an open-source company has to find product market fit twice: first for the OSS project and again for a commercial product.
The only way this could be a 'lesson learned' is if you homehow managed to not pay any attention to what has been going on in the last 25 years with open source software companies.
I thought usually founders try to pivot till they run out of money. I wonder if that is good or bad for a serial entrepreneurs if they decide to shut it down instead of pivoting?
I feel like pivoting got unwarranted hype in the 2010s or so, possibly because Slack was an outlier in how successful they were.
Major pivoting is almost always a really bad idea. (I admit I'm doing a bit of weaseling using the "major" qualifier, but when I searched for examples online, a lot of the ones that came back weren't major pivots, just slight refinements of focus to find better product market fit). Pivoting usually carries a lot of baggage - better to just give the money back and start afresh most of the time.
He might not have had that choice. Investors can put money into a bank account, and just as easily take it out. This is what happened in the 2000 dotbomb.
I’ve never heard of this before. Anyone know if it’s uncommon?
Familiar with creditors getting divvied in bankruptcies, but not refunds to investors… oh it’s because there’s never any money left when things wind down. (We hear of retail stores where employees discover closures posted on shop doors when reporting to work.)
This is super common with startups and is usually called an orderly shutdown. You don’t want to wait until you are insolvent, but stop when there is enough money left to pay all outstanding liabilities as well as the people that will shut down the business entity, do a final tax return and so on. Then whatever is left eventually gets paid back to investors, who usually have a liquidation preference requiring this as well. The alternative, running truly out of money, no one shutting down anything, a ghost entity that continues to accumulate taxes and penalties, creditors chasing whoever they can get a hold of, is much worse. Just because everyone quits doesn’t mean the entity ceases to exist.
It's pretty common. If a startup winds down before it runs out of money, it typically returns whatever is left to the investors. We didn't have any debt.
It actually happens a lot. Sometimes founders may pivot when the original thesis isn't working out, but a lot of times the prudent thing to do is to just say that it didn't work out and return investors' money.
Honestly, I was close to flagging this story because the title is deliberately manipulative - it makes it sound like the founder did a rug pull. But I was really glad to see the founder come in to these comments and just say we tried, but the market shifted under us. Happens all the time.
When I was in university I unsuccessfully attempted to start a company with two other students. We had a small amount of capital from a single investor. We did not pay ourself any salary. We had spent money on incorporating the company and buying a couple of iPads, and not yet spent money on marketing etc.
When after a few months we accepted that it wasn’t going to work, our investor got basically all his money back.
It was pocket change amounts compared to the sums of money that they deal with in Silicon Valley. But the point is the same anyway, the investor got back basically everything.
I had a similar thing happen, made a startup when I was 18 and incredibly dumb. Half my money and half an investors.
Ended up having to wind it down because it was a stupid idea and I realised quite quickly after spending money on it. Was a small amount of money but a lot for me. Luckily the investor never asked for money back.
Wound down my second one too but lost no money.
Then came into some money through a software sale about 7 years later, and offered to pay the first investor their full investment back, which was about half the money from the software sale (my only sale ever).
They really appreciated it but declined and instead said no, they want to invest in me AGAIN in the next one.
Felt really nice to have someone believe in you so much they would open themselves up to money risk again rather than take their initial investment back
LinkedIn is the worst platform to get accurate news as everyone is only incentivized to hype themselves up. Lots of examples abound in r/LinkedInLunatics
The title makes it sound like they just did a seed round, but the seed round was announced in August of last year [0].
Their website landing page is now also showing the software is no longer maintained. No mention of why they made this decision, my best guess is they burned through their seed money and were unable to attract further investments.
The company was started in January 2024, so the seed financing is likely a roll-up of two years of fundraising. $7m for ~30 months of running an AI startup in NYC is not that unusual.
$7m actually isn't a whole lot, especially if they hired a (larger) engineering team. Assuming their cali based, that's easily 150-200k per engineer, a team of 20 easily eats through that. Idk the specifics, but I don't the organization was fradulent, it could also be that they're going commercial and no longer want to maintain their oss stack
150-200k is also just the employee’s salary, the actual cost to the company is significantly higher, you need to multiply that by something like 1.5 to get the fully loaded cost, people are expensive!
> very confident you'll be able to use them to justify another raise soon
That is indeed how the VC funding game is played. If you don't raise another round, you are dead anyway, so you spend down your seed round to try and justify that following round...
Were the thousands of commits and hundreds of feature branches over the last 9 months just to keep up appearances, then? Were the 850 people who forked it in on the scheme, too?
You can call it a bait but where is VCs due diligence for this. Most VCs where out there defending their infra layers investment. Just look at YC batches and see the inflated number of infra startups.
"Failure" is the expected median though. You can't due-diligence your way out of "startup ran out of runway"!
The discussion here isn't about funding, it's that there's a presumptively useful community tool which got abandoned because its owners took their toys and went home when the money ran out (instead of making a sincere effort at transitioning to community governance). That's on the IP owners being selfish jerks and/or grifting losers. It's not the VC's fault.
Part of the social contract of putting a free software project up for public use and convincing Microsoft to host it for free (!) is indeed that you're going to maintain it in good faith for the people who consume it, and that if you can't you'll make a good faith effort to help the people who do.
There are good and bad ways to extract yourself from maintainership obligations. This is the bad way.
No, there is no social contract here. Microsoft gives free hosting because it's cheap and also provides a path to their paid offerings. People share stuff they work on for fun, to help flesh out their resume, to get help, etc. There's no reason for a maintainer not to drop a project in a heartbeat if it becomes the slightest bit of a burden.
Also read the link. This is apache 2 licensed. Even in whatever imaginary world where there is such a social contract, there is thankfully a legal contract that includes disclaimer of warranty.
Sorry but this is an outrageous perspective, at no point does git init / git push am I committing myself to a social contract, in fact there’s probably a license that states no warranty and no support is to be expected… maintainership obligations gtfo if you’re not here paying for support
While most startups fail eventually, failure in less than a year with over 7 million dollars is not the expected median. It’s the exact sort of thing that due diligence is supposed to prevent.
Also the whole project is open source. If you want, you could take it over.
That's why either VCs confused moat with bot farms and farmed stars over solving genuine problems or they just blindly invested based on founders track record no matter what. To me both are really by product vibe coding hype and chatgpt killing wrappers.
The project name, its community center and hosting environment, the active participation and consent of the copyright holders of the software was withdrawn. This is a dead project, we can all see it. If you want to use it and contribute and get help, you have no where to go.
"It's still open source because you can fork it if you really want" is a specious and unhelpful attitude, and it tells me that you, like the owners of this thing, are not to be trusted to manage such a thing.
The project is Apache2 licensed. You can literally do anything you want with the code. Stop trying to push guilt on people for no longer providing free services.
the only reason to ever fork a project in earnest is because the original project owners are not willing or able to cooperate or accept patches. in other words you fork because you have nowhere else to go. exactly the situation we have here.
The report says, the CEO and founder, is a Ketamine addicted weirdo, who does Nazi salutes in public, is know to have at least 24 kids, and lives in an isolated farm in Texas, with at least 5 to 7 female partners, and got sued for calling a guy who saved kids a Pedophile.
Do you understand that when you raise money it doesn't go into your personal account?
Its not like you can move this money in your retirement account and sail into the sunset.
About one year ago, I created an LLM gateway with metrics, provider fallback and switching, tools support, injecting, etc. etc., and unique features like acting as an MCP tools client and server, all streamed, with low latency.
It was a simple project in terms of technical complexity. I didn't publish it as I counted several similar projects in the field.
Putting $7.3M into such a project would make sense only in the case of a precise growth plan with already declared customers and an promising sales funnel. There is no technical moat.
The calculus in “buy or build” has shifted for me over the last six months especially. If I can make an agent build it, I get the version that’s tailored for me.
> It was a simple project in terms of technical complexity.
That’s the thing, though. The version I build for myself sheds all the features that get in my way. I don’t share them either because they’re only useful for me.
Perhaps in the future big tech projects will be delivered with a common “core” and the expectation that agents fill in the use-specific stuff.
> The calculus in “buy or build” has shifted for me over the last six months especially. If I can make an agent build it, I get the version that’s tailored for me.
I feel like this is really going to change the software industry moving forwards. Historically it was tedious and time consuming to actually develop tailored dev tools which is why so many organizations relied on third party solutions. When nowadays you can easily half bake something in a few hours and get it working, tailored _specifically_ to your needs.
> Perhaps in the future big tech projects will be delivered with a common “core” and the expectation that agents fill in the use-specific stuff.
I suspect so, the headless / "api/cli only" tools like CRM are pretty big right now and I don't think we've seen the end of that trend, probably more like just beginning.
Just use Plexus [1]. The maintainer is not trying to be a hero or raise seed dollars or even really trying to promote it. He's just making an excellent, useful product. (Unaffiliated, just a happy user). It's not a full-on "LLMOps" platform (whatever that is), it's just a proxy that works very well and has some nice features.
VCs 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
> 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.
Due to the echo chamber effect, our opinions get reinforced, which can lead to biased conclusions, so it gives me pause. But your comment is so eerily similar to my own thoughts that I'm writing this reply.
I agree that most people misunderstand the concept of a 'moat' and become obsessed with that misunderstanding. People tend to think that only technical 'coding skills' which they can easily understand constitute a moat. But in reality, the moat is the entire workflow across the product's lifecycle, including coing skills. In that sense, infrastructure workflows are nothing more than 'the most easily replaceable consumables.' The essential purpose of infrastructure is to pursue 'standardization,' which paradoxically means a state of 'zero switching costs' where customers (app developers) can switch at any time to a better API or a big tech built in feature. Pure technology that doesn't latch onto the messy real world domains of customers will inevitably be absorbed without resistance by massive capital.
In some ways, customer lock in at the application layer, or even the fan culture around a product, creates emotional lock in. The end user app that provides a specific workflow integrated into users' daily routines can overcome even technical inferiority through 'experience' and 'emotion.' Technology can be copied, but the user identity attached to a tool is what I think a real moat is.(That is also the reason I love Windows.)
The example you gave, Cursor's Composer, is exactly the case I'm talking about. I think Cursor is inferior, and I don't think its Composer model feature is all that great either. But Cursor has a passionate fan base, and users who choose Composer as the best value for money no longer care about absolute technical performance or benchmark scores. They are captivated by the 'speed of experience' of code being completed quickly as they intended, and the 'frictionless workflow' the tool provides.it's not the company that builds the best AI model that wins, but the company that wraps 'good enough technology' in 'great UX' and dominates users' habits. That is how apps dominate infrastructure, and that's the moat you and I are thinking about.
That said, this conclusion is probably too hasty and has many flaws. Still, your thoughts are so similar to mine that I'm leaving this reply. Thanks for the great comment. Have a good day
Our investors aren't looking for safe, they're looking for a small chance in funding the next Databricks or similar. Most times it doesn't work out unfortunately, but that's part of the game.
(Also, we raised the capital in 2024 and didn't burn most of it.)
First of all, I respect your decision. I apologize for speaking too hastily about your choices. What I was trying to do was simply talk about how incredibly fast AI infrastructure changes. I also understand your respect for investors looking for the next Databricks. But the reason I wrote what I did is because the confidence expressed in the README ended so early. That said, such confidence isn't necessarily a bad thing. Isn't it said that victory belongs to challengers like you, not cynical people like me? I feel bad about that part. Still, I have no intention of withdrawing my skeptical view about whether AI infrastructure can succeed as an open source startup. I'm very sorry it came across as if I was mocking your failure. That was not my intent. I was simply trying to leave a comment saying that AI infrastructure has a different direction from traditional infrastructure.
I wish you success. I wasn't trying to mock your failure, and I'm truly sorry if I made you feel bad. I don't want to be a cynical person who mocks others' challenges. I apologize again for that. I was just expressing that something doesn't seem right from my current perspective. I hope your next challenge goes well.
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.
You're right. Looking at recent indicators, there are more stable investments than I thought. But please understand that, as a human, I haven't achieved ROI in terms of marriage, relationships, a stable job, etc., so my perspective might be mixed with a bit of envy
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.
Sometimes people don't realize that 'professional' ideals and 'reality' are different.
What you're talking about seems like 'ideal' investing, not real world investing at all. Of course, the VCs in your country and the VCs in my country are different.
It's like in software, where everyone says you should write maintainable code within the norms, but in reality, most people don't do that
that investing in 'potential' is the basic principle of VCs. They call it the power law. But when you look at actual investment portfolios, it seems quite rare for people to follow only that principle. I guess you don't think so. Of course, I agree that ideal venture investing follows the power law. But in real world investing, there are pragmatic investors who operate somewhere between the ideal and reality. We always project ourselves onto the 'ideal,' but I don't think there are only people who are immersed in that ideal. Of course, no VC would invest in someone like me. I've met with VCs three times in my career, but they all turned me down. Haha.
Anyway, I wasn't trying to mock your profession. Here's what I think. Most VCs and investors have their own success formula. There will be VCs who succeeded by investing in infrastructure. But the question is whether that same success formula applies to AI startups right now. Of course, from your perspective, it might look like 'this clueless kid is just being cynical without knowing anything.' I partly agree. But that's not the core of my argument.
What I'm trying to say is that those success formulas themselves need to be reconsidered.An insider from up there came out and talked about the next 'Databricks,' believing that's the kind of potential they're looking for. All of them do. Everyone wants to be the first investor in a goldmine. I don't think this is just about greed
The question is whether the traditional infrastructure investment logic holds here. I think most current AI infrastructure tools are closer to 'temporary patches' that exist before the functionality gets internalized.
Let's say infrastructure is like a concrete building. Traditional IT infrastructure basically has a standards committee, and once that committee sets things, changes are extremely rare. It's a kind of 'lake.' But AI infrastructure right now is different from one to another; even the ecosystems differ—the Chinese ecosystem is different from the US ecosystem. It's a flowing 'river.' I just think the question is whether the old grammar can be applied in this situation.
You probably have more money, more investment experience, and more success than I do. I only have a lot of failure. But apart from that, the issue is simply that 'potential' in growth potential ends up being data measured against past examples, and the question is whether that data still holds up now. Anyway, I might have been slightly sarcastic earlier, so I apologize for that. Someone as successful as you, please bear with it a little.
We raised most of the capital before we had any traction. We raised on a rolling basis and had millions in the bank before we had even published the open-source repository. Ultimately we raised based on the team's background + vision.
The ~1% figure might be outdated today but it was a best-effort estimate a couple of months ago. TensorZero powered tens of trillions of inference tokens per month. TensorZero is not widely used but it was used by a couple of extreme-scale users.
Thank you, appreciate the response. It’s a great part of the HN community that there’s almost always someone around with the first-hand experience and facts.
I used it, but only briefly to evaluate it. It had some overlap with a tool I built myself, was curious if any of the extra features would be useful.
Ultimately I found the data model and UI to be both cumbersome and unintuitive. Langfuse ended up being the observability tool I went with instead over the one I built (and still use today).
Most VCs avoided application layer believing it is too risky with few player would emerge as winner over application layers calling them GPT wrapper (now called Harness) and pouring money into infra layer. Would love to see your opinion about how this thesis would turn out going forward.
Not my experience. I think most VCs thesis is around the application layer - not much around the infrastructure.
That being said, while I am biased, there is a lot of work around infrastructure so calling it "just a wrapper" massively underestimates the effort - this is purely from my own experience building this space.
Besides, if it is true how come OpenClaw is spending so much money on a open source project. Salaries alone will cost 7 digit sum for a harness and I have first hand experience dealing with companies doing exactly this.
Shameful plug - we are building cbk.ai, better known today as chatbotkit.com.
Open source powers the business of many large corporations and they give essentially nothing back - why would maintainers refuse an offer for money in this environment?
We started the company two and a half years ago, and raised $7.3m in 2024 (announced only almost a year later). We've spent less than half of this amount.
Earlier this week we came to the difficult decision to wind down the project. The open-source repository remains available on GitHub (Apache 2.0) but won't be actively maintained by the team moving forward.
Now one question that you probably get a lot and I must ask: why not pivot?
I might publish a long-form reflection when the dust settles.
Very early in my career I used to believe that I or anyone else could be a CEO.
It wasn't until working with tiny teams where the CEO/founders devoted everything in their life to the business -- often at the expense of hobbies, romantic relationships, and any shred of free time -- that I realized true CEOs are a rare breed.
When are you ask things like "what happens if the product fails?" the answer would always be "It won't."
They both relentlessly believe in, and put every ounce of energy toward, their vision because anything less would not suffice
Again as trite as it sounds, I empathize with these people in that to them losing their vision felt like losing something dearest to them
In smaller startups, everyone is directly involved and has to punch above their weight to pull through, not just the CEO.
Also devoting everything in your life to one thing is not a mark of intelligence or skill. It is a mark of dedication but by itself means little.
And yeah, not everyone can be a CEO because most business fail very quickly. There is always an element of luck in those that survive.
But the idea that you devote 24x7 of your life hence you must be a good leader is not accurate. In fact, if you press this culture downstream, you'll tire your workers and the rest of the team.
For example: I cannot imagine being a successful touring live performer. I am an introvert, I keep a rigid schedule so travel throws everything off, can't keep myself awake very late...
Could I perform the functions of a live performer? Yes, though no matter how much I "tried" the mismatch between the job and my natural tendencies is a recipe for failure.
Not everyone can be a CEO because not everyone is cut out for it. If you think you could step into those shoes, you're either built different or delusional.These are not examples of in-born traits. While I agree that not everyone has the motivation to become a CEO, I would disagree that a person cannot learn and adapt.
Is there a way to reach out to you as I would like to hear what you have to say about what I am working on. You can update your HN profile to include contact information or you can reach out to me using my HN profile.
I'm basically working on a portable intelligence layer for AI that I will be open sourcing and the commerical product will be to make the intelligence layer even smarter. I can share the Show HN post that I am working on that better explains the value proposition and would love to learn any lessons you have gained while trying to sell AI tools commerically.
Edit: In case somebody calls me out it. I didn't want to use the `tensorzero` email domain incase the domain was going to become defunct soon.
The only way this could be a 'lesson learned' is if you homehow managed to not pay any attention to what has been going on in the last 25 years with open source software companies.
The other half goes where?
We are returning the remaining capital to investors.
Major pivoting is almost always a really bad idea. (I admit I'm doing a bit of weaseling using the "major" qualifier, but when I searched for examples online, a lot of the ones that came back weren't major pivots, just slight refinements of focus to find better product market fit). Pivoting usually carries a lot of baggage - better to just give the money back and start afresh most of the time.
Familiar with creditors getting divvied in bankruptcies, but not refunds to investors… oh it’s because there’s never any money left when things wind down. (We hear of retail stores where employees discover closures posted on shop doors when reporting to work.)
Honestly, I was close to flagging this story because the title is deliberately manipulative - it makes it sound like the founder did a rug pull. But I was really glad to see the founder come in to these comments and just say we tried, but the market shifted under us. Happens all the time.
The title is misleading unfortunately but that's how social media goes...
Early stage startups tend not to have a lot debt to pay off, because there aren’t many places willing to offer them much credit.
When after a few months we accepted that it wasn’t going to work, our investor got basically all his money back.
It was pocket change amounts compared to the sums of money that they deal with in Silicon Valley. But the point is the same anyway, the investor got back basically everything.
Ended up having to wind it down because it was a stupid idea and I realised quite quickly after spending money on it. Was a small amount of money but a lot for me. Luckily the investor never asked for money back.
Wound down my second one too but lost no money.
Then came into some money through a software sale about 7 years later, and offered to pay the first investor their full investment back, which was about half the money from the software sale (my only sale ever).
They really appreciated it but declined and instead said no, they want to invest in me AGAIN in the next one.
Felt really nice to have someone believe in you so much they would open themselves up to money risk again rather than take their initial investment back
I would applaud that the fact that found took bold decision to think out of the box and take action towards it.
Their website landing page is now also showing the software is no longer maintained. No mention of why they made this decision, my best guess is they burned through their seed money and were unable to attract further investments.
[0]: https://www.tensorzero.com/blog/tensorzero-raises-7-3m-seed-...
or you're incompetent
That is indeed how the VC funding game is played. If you don't raise another round, you are dead anyway, so you spend down your seed round to try and justify that following round...
I’d bet on extreme irresponsibility.
(Honestly I don’t think so here, but I predict that will happen eventually)
The discussion here isn't about funding, it's that there's a presumptively useful community tool which got abandoned because its owners took their toys and went home when the money ran out (instead of making a sincere effort at transitioning to community governance). That's on the IP owners being selfish jerks and/or grifting losers. It's not the VC's fault.
There are good and bad ways to extract yourself from maintainership obligations. This is the bad way.
Also read the link. This is apache 2 licensed. Even in whatever imaginary world where there is such a social contract, there is thankfully a legal contract that includes disclaimer of warranty.
Also the whole project is open source. If you want, you could take it over.
Yes, that's exactly what it means!
"It's still open source because you can fork it if you really want" is a specious and unhelpful attitude, and it tells me that you, like the owners of this thing, are not to be trusted to manage such a thing.
The report says, the CEO and founder, is a Ketamine addicted weirdo, who does Nazi salutes in public, is know to have at least 24 kids, and lives in an isolated farm in Texas, with at least 5 to 7 female partners, and got sued for calling a guy who saved kids a Pedophile.
You in?
It was a simple project in terms of technical complexity. I didn't publish it as I counted several similar projects in the field.
Putting $7.3M into such a project would make sense only in the case of a precise growth plan with already declared customers and an promising sales funnel. There is no technical moat.
> It was a simple project in terms of technical complexity.
That’s the thing, though. The version I build for myself sheds all the features that get in my way. I don’t share them either because they’re only useful for me.
Perhaps in the future big tech projects will be delivered with a common “core” and the expectation that agents fill in the use-specific stuff.
I feel like this is really going to change the software industry moving forwards. Historically it was tedious and time consuming to actually develop tailored dev tools which is why so many organizations relied on third party solutions. When nowadays you can easily half bake something in a few hours and get it working, tailored _specifically_ to your needs.
I suspect so, the headless / "api/cli only" tools like CRM are pretty big right now and I don't think we've seen the end of that trend, probably more like just beginning.
[1] https://github.com/mcowger/plexus
"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
> 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 agree that most people misunderstand the concept of a 'moat' and become obsessed with that misunderstanding. People tend to think that only technical 'coding skills' which they can easily understand constitute a moat. But in reality, the moat is the entire workflow across the product's lifecycle, including coing skills. In that sense, infrastructure workflows are nothing more than 'the most easily replaceable consumables.' The essential purpose of infrastructure is to pursue 'standardization,' which paradoxically means a state of 'zero switching costs' where customers (app developers) can switch at any time to a better API or a big tech built in feature. Pure technology that doesn't latch onto the messy real world domains of customers will inevitably be absorbed without resistance by massive capital.
In some ways, customer lock in at the application layer, or even the fan culture around a product, creates emotional lock in. The end user app that provides a specific workflow integrated into users' daily routines can overcome even technical inferiority through 'experience' and 'emotion.' Technology can be copied, but the user identity attached to a tool is what I think a real moat is.(That is also the reason I love Windows.)
The example you gave, Cursor's Composer, is exactly the case I'm talking about. I think Cursor is inferior, and I don't think its Composer model feature is all that great either. But Cursor has a passionate fan base, and users who choose Composer as the best value for money no longer care about absolute technical performance or benchmark scores. They are captivated by the 'speed of experience' of code being completed quickly as they intended, and the 'frictionless workflow' the tool provides.it's not the company that builds the best AI model that wins, but the company that wraps 'good enough technology' in 'great UX' and dominates users' habits. That is how apps dominate infrastructure, and that's the moat you and I are thinking about.
That said, this conclusion is probably too hasty and has many flaws. Still, your thoughts are so similar to mine that I'm leaving this reply. Thanks for the great comment. Have a good day
(Also, we raised the capital in 2024 and didn't burn most of it.)
I mean it. I'm sorry once again
> 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.
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.
What you're talking about seems like 'ideal' investing, not real world investing at all. Of course, the VCs in your country and the VCs in my country are different.
It's like in software, where everyone says you should write maintainable code within the norms, but in reality, most people don't do that
that investing in 'potential' is the basic principle of VCs. They call it the power law. But when you look at actual investment portfolios, it seems quite rare for people to follow only that principle. I guess you don't think so. Of course, I agree that ideal venture investing follows the power law. But in real world investing, there are pragmatic investors who operate somewhere between the ideal and reality. We always project ourselves onto the 'ideal,' but I don't think there are only people who are immersed in that ideal. Of course, no VC would invest in someone like me. I've met with VCs three times in my career, but they all turned me down. Haha.
What I'm trying to say is that those success formulas themselves need to be reconsidered.An insider from up there came out and talked about the next 'Databricks,' believing that's the kind of potential they're looking for. All of them do. Everyone wants to be the first investor in a goldmine. I don't think this is just about greed
The question is whether the traditional infrastructure investment logic holds here. I think most current AI infrastructure tools are closer to 'temporary patches' that exist before the functionality gets internalized.
Let's say infrastructure is like a concrete building. Traditional IT infrastructure basically has a standards committee, and once that committee sets things, changes are extremely rare. It's a kind of 'lake.' But AI infrastructure right now is different from one to another; even the ecosystems differ—the Chinese ecosystem is different from the US ecosystem. It's a flowing 'river.' I just think the question is whether the old grammar can be applied in this situation.
You probably have more money, more investment experience, and more success than I do. I only have a lot of failure. But apart from that, the issue is simply that 'potential' in growth potential ends up being data measured against past examples, and the question is whether that data still holds up now. Anyway, I might have been slightly sarcastic earlier, so I apologize for that. Someone as successful as you, please bear with it a little.
“TensorZero is used by companies ranging from frontier AI startups to the Fortune 10 and fuels ~1% of global LLM API spend today.”
One percent seems like a lot. Anyone on HN use this?
The ~1% figure might be outdated today but it was a best-effort estimate a couple of months ago. TensorZero powered tens of trillions of inference tokens per month. TensorZero is not widely used but it was used by a couple of extreme-scale users.
Best of luck with whatever you do next!
Ultimately I found the data model and UI to be both cumbersome and unintuitive. Langfuse ended up being the observability tool I went with instead over the one I built (and still use today).
https://github.com/TensorOne
That being said, while I am biased, there is a lot of work around infrastructure so calling it "just a wrapper" massively underestimates the effort - this is purely from my own experience building this space.
Besides, if it is true how come OpenClaw is spending so much money on a open source project. Salaries alone will cost 7 digit sum for a harness and I have first hand experience dealing with companies doing exactly this.
Shameful plug - we are building cbk.ai, better known today as chatbotkit.com.
https://github.com/BerriAI/litellm/
Wasn't GitHub once a place for humans? Now we could rename it SkyHub.
PS: Someone won't become a trillionaire with this attitude.