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~6 min read 13 Aug 2025

Which Software Businesses Will Survive the AI Era

AI Summary

Software is not dead, but not all software is equal. Evaluating a software business through six key attributes, including time to yes, implementation time, tear out time, and switching cost, reveals which products are vulnerable to AI disruption and which are protected. Bootstrappers should target low-friction, fast-utility products where distribution skill matters more than defensibility, while avoiding the trap of building Calendly-style businesses with near-zero switching costs.

Key takeaways

1

Businesses with long sales cycles, high implementation times, and high switching costs are largely safe from AI disruption. A CTO won't rip out Gitlab to save 50%.

2

Calendly-style products with instant time-to-yes, zero tear-out time, and no data moat are the most vulnerable. Any cheaper clone can immediately replace them.

3

For bootstrappers, the ideal product has fast time-to-utility, low implementation friction, and a price point low enough to skip phone sales but high enough to generate real revenue.

Original post

WILL AI DESTROY YOUR SOFTWARE COMPANY? OR: WHICH SOFTWARE COMPANY SHOULD I BUILD? I'm a software private equity investor. I look at 10-20 software businesses each week to acquire. I see good, bad, and everything in between. ***I am reposting this since apparently all the pods think software is cooked (it isn't)*** I keep getting this freaking dm 'Now that I can build ANY software company with AI (lol) what should I build?' I've also seen this nonsense going around of 'software is dead'. I'm going to address both of these here. First things first, software is not just software. Software exists across a variety of dimensions/attributes. We have to cover these as they play a massive role in which software will be 'fine' and which software is 'at risk'. This should also tell you indie b...

WILL AI DESTROY YOUR SOFTWARE COMPANY? OR: WHICH SOFTWARE COMPANY SHOULD I BUILD? I'm a software private equity investor. I look at 10-20 software businesses each week to acquire. I see good, bad, and everything in between. ***I am reposting this since apparently all the pods think software is cooked (it isn't)*** I keep getting this freaking dm 'Now that I can build ANY software company with AI (lol) what should I build?' I've also seen this nonsense going around of 'software is dead'. I'm going to address both of these here. First things first, software is not just software. Software exists across a variety of dimensions/attributes. We have to cover these as they play a massive role in which software will be 'fine' and which software is 'at risk'. This should also tell you indie builders out there which software to go after. For the purposes of this exercise, I'm going to use a darling example company to analyze these attributes: Calendly. Here are some of the attributes I think about when I look at acquiring a business: 1) 'time to yes': How long does it take to sell your software after a customer learns about it? Is it a 3-6 month sales cycle? Is time to yes instant? DO I NEED TO TALK TO SOMEONE ON THE PHONE TO PURCHASE IT? If, like calendly, I can buy it myself with my corporate card? Time to yes has knock on effects on so much: price, churn, etc. It is an important attribute to cover. Calendly's time to yes can be instant. 2) 'implementation time': Software that takes a long time to implement. I call this 'implementation time'. Others in my space call it something else. This is the amount of time it takes between wiring the money and the company actually USING the software. An example might be vertical software for a veterinarian. It could take a full month to configure the software, get all the users onboarded, work through bugs, etc. How long does it take to implement calendly? Well about 4-5 minutes. 3) 'Time to Utility': This is the time between 'the customer can actually use the software' and 'the customer has derived utility'. If we are using calendly as an example, again this near instant. If this is vertical SAAS for managing a veterinary clinic, this time might be a month or two. Sure the software is making the business run 'smoother' but the time to utility might be longer than you think. 4) 'Tear Out Time': some people call this switching cost, but I delineate the two. How long does it take a customer to 'tear it out' and switch? This is NOT the same as switching cost, although some people mistakenly (imo) lump them together. This is measured in TIME. Calendly's tear out time? Near instant for most people. 5) Switching Cost: How much does it cost me to switch? This can be a real number. Let's say I want to switch my CRM from Salesforce to Attio. Not only do I have a probably high 'tear out time', I also have to pay SOMEONE to migrate my sales data from Salesforce to Attio. There's a real dollar cost here, even if Attio claims to have the softawre to do it. What's my switching cost from Calendly to Cal? ...near 0. 6) ACV: Average contract value. Finally we get to price. How much are you charging for your software? If you are Salesforce, this could be 20k. If you're calendly? 8 bucks a month. 7) Churn: self explanatory. 8) Data Moat / Network Effects: Does your business collect data that is difficult to collect via LLM? Do you have data that drives product utility that is difficult to attain? Do you have network effects? THESE ATTRIBUTES ARE THE LENSE THROUGH WHICH YOU SHOULD THINK ABOUT SOFTWARE. Now, getting back to the question: 'will AI destroy my software company?'. Buddy, if you have high time to yes, a high implementation time, and a low time to utility, AI is unlikely to cook your software company. AI DOES NOT REPLACE A 3 MONTH SALES CYCLE AND A HIGH IMPLEMENTATION TIME. Customers are NOT just going to churn because some guy is billing half as much. CEOs value time and attention. If your software is mission critical, tear out time is high, AND switching cost is high? No one is churning. If you ask a CTO if they would tear out Gitlab to save 50%, they'd probably laugh in your face. Now: to the inverse. Let's talk about Calendly. Calendly is the perfect example of a business that I think will be in trouble due to AI. Why? (I'm a calendly customer btw) 1) My time to yes is instant. If someone comes to me with a $2 a month replacement, I can instantly say yes. 2) My implementation time is instant. I cancel calendly. I synch my email to new service. Done. 3) Time to utility is instant. 4) TEAR OUT TIME IS 5 MINUTES. YIKES! This is problematic software. 5) Switching cost: Near 0. 6) No data moat. No network effects (rly). To all you indie hackers out there: these are the types of businesses you might want to copy. Why? YOU DON'T NEED AN ENTERPRISE SALES TEAM TO SELL YOUR PRODUCT. Like it or not, even if AI can make a copy of software, spoiler alert you have to go out and SELL IT. There's a reason some B2B SAAS companies NEED venture funding: the sales cycles (time to yes, imp time, time to uitlity) ARE LONG LOL. You NEED those venture dollars to sell this software that will (hopefully) have a very low churn rate. Many of these businesses are fine. Their main problem is people above and below them in the vertical chain. Not addressing this here. What's that mean? DISTRIBUTION MATTERS MORE THAN EVER. If calendly can be copied, learning how to distribute in a low cost way becomes more valuable than ever before in software. SEO. Partnerships. Large scale cold email. Having influencers on board from day 0. These things matter even MORE. So is software dead? Hell no...but companies like calendly will surely have some problems. So to you boot strappers out there, here's what you want: 1) Time to yes can be instant. 2) Time to utility should be as fast as possible. 3) Low Implementation time. 4) Keep price low enough that someone can say 'yes' without needing to call you on the phone but high enough that can make some serious dough. 5) Hopefully find a way to get data that's hard for someone else to get. That'll help with competition and switching cost. YOU WILL HAVE CHURN. But you can also build a 5mm ARR business with 4 employees. Good luck anon

carried_no_interest

@carrynointerest

Private Equity Investor skewing towards software. Former Head of AI @ $1B+ PE fund. Former Data Scientist using AI to source deals. DMs Open

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