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I know several MM/LMM funds that haven't done a deal since 2024. It's been bad for more than a few months lol. That's not to say I think the rerate and sentiment is warranted, I do think it's overblown. But as demonstrated by a founder who posted on this forum recently, I think it's more difficult because sellers are even more reluctant to accept the rerate on their assets (in some cases, understandably so). 

"If you don't have any enemies in life you have never stood up for anything" - Winston Churchill | "It's a testament to the sheer belligerence of the profession that people would rather argue about the 'risk-adjusted returns' of using inferior tooth cleaning methods." - kellycriterion
 
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I can only imagine the mental willpower that must be required to sit calmly at your desk and not exact a mighty fury upon those around you watch your managing partner at the latest conference highlighting that the team has been internally 'preparing' for AI since 2023, meanwhile your day consists of portfolio work for three enterprise software companies (20x entry multiples) with accumulated tech debt and worse terminal value risk than the public comps you have been instructed to compartmentalize as screwed for different reasons 

 
Funniest

I work out 6 days a week now, fund is imploding but life is great

 

It’s been a different experience from what I expected when I took this role, but finding some positives in the midst of an expectation reset. Our fund is pivoting investment philosophy to better accommodate a post-AI era and that has opened up new opportunities that I’m excited for. Getting more hands on, quasi-operating experience too as we look to add more value to our portcos. Just gotta keep looking for ways to build new muscles and think creatively

 

I am in a MM fund with a more value turnaround angle rather than a growth strategy (e.g. we were never paying 20x EBITDA on SW) . And it's actually a good time as seeing processes where we were outbid at NBO stage now circling back, as buyers who offered 20-30% higher valuations walk away. The main challenge now is convincing founders and PE sellers that those valuations are gone

 

There's really a few ways to look at the risks and why investors are selling off: 

  1. DIY: Few that historical software customers will now use Claude Code and other AI-assisted coding tools to build their own versions of software. I think this makes sense for really lightweight tools or things that were really just a workflow layer, but the internal cost to maintain today is still high and companies that don't have big IT teams or bandwidth to do this are unlikely to go down this path.
  2. Competition: This is personally where I'd be most concerned; the cost of developing software has come down drastically (both literally and from an expertise perspective), which creates the risk that one person with enough free time can create a competing product to yours at a fraction of the cost. The ultimate worry here is that incumbents get displaced because new software is cheaper and/or better, and that you create a race to the bottom on price. 
  3. Model Labs: This would be the risk that the knowledge or capability of your current software vendor gets absorbed by Anthropic or OpenAI and ultimately what the current vendor provides isn't much better than the model labs offer through their LLMs and so you leave. The start of the SaaS-pocalypse was with Anthropic announcing both better model development speed capabilities but also their packages / plug-ins that take a lot of the workflows away from existing vendors (e.g., Claude for Legal). 
    1. A sub to this would be the idea that the model labs actually develop software and then compete 1:1 with existing vendors but I think we're a ways away from this (their employees really only need to focus on developing and commercializing their AI). It wouldn't really be workflow software but software that pairs well with their agentic tools so like a system of record where all the information is stored that makes their agentic workflows better with the right context. 

There are probably more risks that I didn't cover, I just think of these as the main three. Time will tell if companies actually take route (1) and we'll see if any of the competitors that emerge via (2) actually start winning share. I think if you combine the fact that workflows just get shifted to model labs via (3) and then maybe you can get the supporting software cheaper via (1) or (2), then you get the storm that justifies the sell-off. 

MD, PhD, JD, MBA
 

You’re forgetting an important few

  1. margins. Incorporating AI into software/data products means software co pays for the tokens. That cuts into margins.
  2. Leverage and refinancing. You might be able to get an A&E done but it’s extend and pretend. So many of these companies generate 0 FCF, no deleveraging and dividends to speak of.
  3. PE software companies are just not great businesses and never were. They usually are bad assets spun off from a better public company, a public company that was under growing market, or a sub scale private company. Ripping costs out does not fix the top line. It’s a one time boost to earnings
  4. As others have mentioned entry multiples were elevated. But the reality is that even if sponsor paid 15x ebitda for software business, if ebitda had just grown by 10% a year for 5 years, the entry multiples has been lowered to 9x. Still high but not unreasonable. The problem is that very few sponsor companies grow clean ebitda (post cap software and other shenanigans) over time, because they usually cut costs, reduce innovation, fire the most productive sales people or otherwise cause them to quit, and that leads to top line pressure with cost optimization already completed. So you stall out. 
 

ojapar20

Sorry guys but you're all wrong.

@Ozymandia  @IsItREPE will educate us on how AI is just a useless bubble and how the macro trends in this thread are all imaginary.

Stop tagging me every time you have a thought about AI, retard 

...but is it REPE?
 

This was my first time going through a cycle. Some interesting notes, maybe...

  1. The environment a lot of these funds deployed into was insane. People were raising 8 figure VC funds for fun as a "side job", morons on twitter raising insane $ too. We had a lot of inbound about raising a fund, and ppl asking why we weren't investing more in 2020/2021. My cofounder and I are both intellectually honest and knew multiples in our specific cat were too hot to make sense, so we were net sellers. Literally met some of the dumbest people I know that had term sheets from Tiger et al.
  2. We have invested in a fair amount of software, but we didn't really overpay for anything as these were not in hot spaces. We are still going to net out far more than the S&P. I think if you did this, it has turned out ok. I actually think there's a lot of software that is unfairly beaten up right now tbh.
 

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