Bending Spoons isn't playing the typical public company game. CEO Luca Ferrari pulls back the curtain on a strategy that leverages public markets not for a liquidity event, but as a direct pipeline to cheaper debt. This fuel feeds an acquisition machine that buys and revitalizes mobile-first apps like AOL, Eventbrite, and Vimeo. And the engine running it all? An AI platform writing over 90% of their code.

Ferrari lays out a vision far removed from the usual founder exit narrative. “We chose to go public primarily to improve our access to debt,” he says. Lenders, it turns out, really like lending to public companies. More regulation, external transparency, and clear valuations make them happy. For Bending Spoons, this wasn't about raising equity; it was about supercharging their ability to borrow cheaply, allowing them to pursue “three, five, eight deals a year of relatively speaking the same scale more or less.”

Key Takeaways

  • Bending Spoons treats its IPO as a financial instrument, not just a milestone, specifically to secure cheaper debt for its aggressive acquisition strategy.
  • Their core operational advantage is extreme AI automation, with “over 90% of our code being written by AI” through in-house models and an AI orchestrator.
  • This AI-driven platform enables a high volume of M&A, targeting 3-8 deals annually to acquire and revitalize mobile-first brands.
  • The company meticulously cultivates a reputation as an "excellent acquirer" known for honesty, product improvement, and allowing acquired founding teams flexibility to depart.
  • Ruthless automation has dramatically increased core team productivity, with 'revenue per spooner' jumping from $1 million in 2023 to roughly $4 million.

The Method: Bending Spoons' AI-Powered Acquisition Machine

Bending Spoons has built a system designed to rapidly acquire, integrate, and grow mobile apps. The first pillar is their unique financial strategy. Going public isn't about cashing out; it's about making their balance sheet more attractive to debt markets. Luca Ferrari's direct quote explains it simply: “It turns out that lenders really like lending to private public companies, better regulated, more externally transparent. They like valuation, all things a lender loves.”

With cheap capital secured, the next step is a consistent, high-volume acquisition cadence. Ferrari describes a predictable rhythm: “do three, five, eight deals a year.” These aren't mega-deals; they're generally of similar, manageable scale. The magic, however, happens post-acquisition. Bending Spoons doesn't just buy apps; they plug them into a “technologically advanced platform where everything is highly integrated.” This platform is their secret weapon.

This platform relies heavily on artificial intelligence. Ferrari states, startlingly, that “we are over 90% of our code being written by AI and pretty modest expenditures.” This isn't just a marketing claim; it's a core operational reality. They achieve this with a combination of in-house AI models and an AI orchestrator. This extreme automation allows a relatively lean core team – or "spooners" – to revitalize multiple acquired products simultaneously, improving them and driving growth. Their commitment to being an "excellent acquirer" is also key. They earn a reputation for honesty, reliability, and genuinely investing effort into product improvements, which makes future sellers trust them. The proof is in their productivity: the KPI they track, "revenue per spooner," shot up from about $1 million in 2023 to roughly $4 million.

Where This Breaks Down

This high-octane model isn't for everyone. First, it demands a deep, expensive upfront investment in building out the core AI platform and in-house models. While ongoing expenditures are modest, getting to that point requires serious engineering horsepower. Second, it's tailored for a specific type of asset: mobile-first brands that can plug into a common operational playbook. It wouldn't work for complex, regulated industries or businesses with heavy physical assets. Third, maintaining a reputation as an "excellent acquirer" is fragile. One or two messy deals could sour the well and make future sellers hesitant, crippling the deal flow. Lastly, this strategy assumes a consistent supply of suitable acquisition targets, which isn't always guaranteed, especially as market conditions shift.

What to Do With This

Stop thinking about AI as a tool for a specific feature and start asking: Where can AI replace 90% of the code for an entire core function in my business? Pick one internal process that is currently human-intensive and repeatable – perhaps customer onboarding, content generation, or internal tooling development. Now, challenge your team to build or integrate an AI system that generates, audits, or executes 90% of the underlying logic for that process. Don't just automate tasks; aim to automate the creation of the automation itself. If Bending Spoons can do it for acquisitions, you can likely do it for a smaller, critical part of your own operations. Aim for a 3-4x increase in "revenue per employee" for that specific team by year-end, driven purely by this extreme AI-led productivity jump.