So, if I’m following: Banks are lending to private equity firms to fund purchases of businesses.
Many of these businesses are SaaS which means their valuations are tumbling.
It seems possible that valuations tumble so much that the private equity owner no longer has any incentive to operate the business, bc all future cash flows will belong to the bank. What happens in practice then? Will banks actually step in and take operational control? Will the banks renegotiate terms such that the private equity owners are incentivized
to continue as stewards? Or, will they prefer to force a business sale immediately?
The author keeps saying, over and over, that the reason this is a good bet is because "the downside is capped and the upside is asymmetric" as if that's some ground-breaking realization.
Sorry, but obviously the downside is capped. The downside of virtually any marketing investment is capped at the cost of the media buy...And, the upside being "asymmetric" isn't some saving grace. What matters is the likelihood that you actually realize that asymmetric upside. And, nowhere in the article does he talk about Ro's estimated success likelihoods or actual outcomes.
In short, he's basically saying:
- I made a bet
- It costs me something ("capped downside")
- There's a potential payout ("asymmetric upside")
- I have no idea whether this is positive expected value
If they really only raised $1.7b, per Crunchbase, then this seems to me like a very good outcome for everyone involved except its late stage investors. And, even for the late stage investors, they're breaking even.
Words are cheap. I really wish there was a way to incentivize authors like this to put their money where their mouth is, before seeking attention for their ideas.
Surprised to see this upvoted because the takeaway is completely incorrect, and based on the anecdotal evidence of one advertiser.
As someone who spends seven figures every month on Google ads, what’s much more likely to be happening here is that the individual advertiser is either getting outcompeted or they’re executing ads poorly.
Google ads revenue in the US continues to grow every quarter. And, since advertisers will generally invest in ads until the last dollar is break even, it’s likely that the total value advertisers unlock through Google ads is growing as well. Whether that’s true or not, the notion that value generated for advertisers is “dead” is absurd.
As this incident unfolds, what’s the best way to estimate how many additional hours it’s likely to last? My intuition is that the expected remaining duration increases the longer the outage persists, but that would ultimately depend on the historical distribution of similar incidents. Is that kind of data available anywhere?
As is the case with most complex problems like this, the correct answer is: it depends.
In this case, it depends on what the crux of your business is. Sometimes the crux is building world-class technology. Sometimes the crux is customer acquisition.
If the crux of your business is customer acquisition, then an exceptional business co-founder will actually be the most important ingredient to long-term success.
This is one of the biggest weaknesses I've noticed in YC's mantra. In most industries, just building something people want doesn't lead to success - you have to excel at customer acquisition also. And, in these industries, as you business matures, you realize that customer acquisition, at scale, is actually the hardest problem to solve.
Years ago, I was lying in the grass, having a conversation with a fellow founder, when he noted how, on most days, he would forget to eat lunch because he was so engrossed with his work. I thought to myself, That's ridiculous. Everyone notices when they're hungry. This was just a thinly veiled brag about his work ethic.
Nowadays, I find myself skipping lunch every other day - out of forgetfulness.
> Why pretend to be smart and play it safe? True understanding is rare and hard-won, so why claim it before you are sure of it? Isn't it more advantageous to embrace your stupidity/ignorance and be underestimated?
I wish this were true, and I do think this mindset would be optimal if everyone adopted it. Unfortunately, real workplaces are filled with people who are confident and wrong. As a leader, if your intuition is more accurate than your peers and you care about objective success, it’s important to assert yourself.
Tldr; The reason it dropped off the first page was likely due to mass flagging. Whether these flags were coordinated at the behest of a self-interested party is unclear. However, when cases like this are reported, more often than not, it turns out to be a function of genuine flagging.
I think it's worth double clicking here. Why did Google have significantly better search results for a long time?
1) There was a data flywheel effect, wherein Google was able to improve search results by analyzing the vast amount of user activity on its site.
2) There were real economies of scale in managing the cost of data centers and servers
3) Their advertising business model benefited from network effects, wherein advertisers don't want to bother giving money to a search engine with a much smaller user base. This profitability funded R&D that competitors couldn't match.
There are probably more that I'm missing, but I think the primary takeaway is that Google's scale, in and of itself, led to a better product.
Can the same be said for OpenAI? I can't think of any strong economies of scale or network effects for them, but maybe I'm missing something. Put another way, how does OpenAI's product or business model get significantly better as more people use their service?
DeepSeek just further reinforces the idea that there is a first-move disadvantage in developing AI models.
When someone can replicate your model for 5% of the cost in 2 years, I can only see 2 rational decisions:
1) Start focusing on cost efficiency today to reduce the advantage of the second mover (i.e. trade growth for profitability)
2) Figure out how to build a real competitive moat through one or more of the following: economies of scale, network effects, regulatory capture
On the second point, it seems to me like the only realistic strategy for companies like OpenAI is to turn themselves into a platform that benefits from direct network effects. Whether that's actually feasible is another question.
Why would it matter? OP is experiencing an undesirable outcome, and assigning blame for the problem seems besides the point when the main goal is to change the outcome.
There seems to already be significant competition in the low cost ETF space. For example, Schwab’s broad based s&p ETF (SCHB) has $34b AUM.
The fact that there exists a competitive market suggests that there’s a good reason expense ratios can’t drop much further than .03%. Presumably, once you reach a certain size, there are costs associated with managing a low cost etf strategy that the end investor actually wants to pay for.
What makes you think you can beat these market rates in a way that is truly accretive to investors? Put another way, what is Schwab wasting money on that you won’t?
I doubt Schwab is just being greedy with their .03% fee. It’s necessary to cover their costs.