Rebuild, Don’t Re-platform: How AI is breaking the Private Equity Playbook
AI has flipped the script on how we think about tech debt, but the real disruption isn't happening in just engineering teams. It's happening in boardrooms where PE firms are still calculating risk based on old assumptions about what it costs to fix or modernize broken technology.
Here's what changed: Today an AI‑assisted team can spin up a clean, modern stack in less time than it takes to finish diligence.
The $30 Million Problem Just Became a Four-Month Project
Jeff Hinck from Rally Ventures put it perfectly when describing a recent deal: "If you can stand up 60% of this in four months versus replatform over three to five years and spend $30 million, that’s easy math."
He was talking about a claims processing company with massive tech debt — the kind of monolithic, cobbled-together system that PE firms encounter all the time. Multiple acquisitions, janky integrations, aspirations for automation that would never happen with the existing stack.
The old playbook said to spend years and tens of millions untangling that mess. The new reality? Rebuild it from scratch in months.
This isn't startup advice. This is math that changes everything about how PE firms should think about acquisitions, hold periods, and value creation.
The Investment Thesis That No Longer Exists
Private equity firms built their tech due diligence around one core assumption: technical debt is expensive and time-consuming to fix. You'd spend months evaluating whether a company's Rails app was three versions behind or if their database architecture would blow up your investment thesis.
That assumption just died.
"The technical nightmare that costs millions we didn't plan for" isn't a risk anymore. When rebuilding becomes faster than fixing, the entire game changes.
PE and VC Are Converging (In Ways You Didn't Expect)
The convergence isn't happening where everyone expected. Traditional buyout PE and early-stage VC remain distinct. But in the growth category — where both operate — the lines are blurring fast.
Here's why: PE firms are buying AI companies as rollups to improve their portfolio companies' tech stacks. But as Jeff pointed out, “they're not just mashing disparate systems together anymore, now they have to make everything "agent friendly."
"If you need to build in agent functionality, you could be doubling your development efforts. At that point, you'll likely ask the question if you should have started from scratch, and the answer will be a definitive yes, especially now.'"
The integration nightmare is making rebuilding look even more attractive.
The New Economics: Capital Shifted, Didn't Disappear
Here's where it gets interesting. Jeff confirmed that AI has made development dramatically cheaper, but companies still need capital — just for different reasons.
The old model: Need millions for servers, hardware, lengthy development cycles.
The new model: Development is cheap, but go-to-market and compute costs are higher than ever.
"The investment just shifted from early product development" to sales and marketing, Jeff explained. Companies like Cursor hit $500 million in revenue in 24 months but "continued to raise a lot of money because they're pushing all the marketing spend."
Translation: You can rebuild the tech stack cheaply, but you still need firepower to break through the noise.
Shifting Sands: The New Risk Landscape in Private Equity
Jeff's stark assessment resonates. While revenue ramps can be "absolutely phenomenal," signifying rapid success, the flip side is equally swift disruption. As he warns, "You could be disrupted tomorrow and you're done."
This accelerated pace necessitates a revised strategy: "You might have to make your money and then walk away from the table." Even Salesforce, a dominant force in CRM for two decades, faces an existential crisis and may lose its market leadership within 3-5 years.
This dramatic shift begs a critical question for private equity firms: Are technology cycles compressing from 20 years to a mere 3-5? If so, the traditional calculation of hold periods must be entirely reevaluated.
The Impact is Real
Jeff shared specific examples from Rally's portfolio:
One company experienced a 20% revenue lift and improved their risk modeling with focus on just one use case
A 30% uptick in team productivity in a multi-million dollar firm
Expectation across portfolio: Revenue per employee should go up quite a bit
"We're already seeing that you can move people to higher-value work when you automate time-consuming, repetitive work – and that seems to be accelerating."
What PE Firms Should Really Care About
Your tech due diligence checklist is obsolete. Stop asking whether their systems are modern. Start asking whether they have what it takes to rebuild quickly. Stop paying for legacy consultancies to give you long roadmaps of things that need to be done.
As Jeff emphasized: "There is nothing worse than trying to integrate a bunch of disparate tech stacks." Especially when you're rolling up companies across different industries with decades of legacy systems.
Focus on these instead:
Data quality and hygiene — You can rebuild the application, but you can't rebuild bad data.
Team readiness for modern development — Do they have people who can work with AI tools, and reimagine the architecture?
Market position that's worth preserving — Brand recognition, customer relationships, regulatory approvals.
Go-to-market capability — Since that's where the real capital requirement shifted.
The Bigger Disruption Question
Here's the question that should keep PE firms awake at night: Will non-tech industries get displaced by AI-native companies that can use technology more effectively?
Jeff posed it this way: "Are you going to see more companies like Chime being able to adopt these things much more effectively and actually become a very large bank?"
If the answer is yes, then buying traditional companies to optimize them becomes a losing strategy. The winners will be the ones who can build AI-native from day one.
The Bottom Line
We're not just watching technology change. We're watching the fundamental economics of business transformation change.
PE firms that thrive in the next decade won't be the ones with the most capital. They'll be the ones who understand that when rebuilding becomes faster than fixing, when integration becomes more expensive than starting fresh, when technology cycles compress from decades to years — the entire investment model has to evolve.
The companies that figure this out will own their categories. The ones that don't will be explaining to their LPs why their portfolio companies are still replatforming while AI-native competitors just rebuilt everything from scratch.
Ready to rebuild instead of fix? We help PE firms and their portfolio companies navigate this new reality using AI-first development strategies.
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