BREAKING: Luca Ferrari CEO of Bending Spoons
1. Key Themes
Buy-and-hold-forever is a structural moat, not just a philosophy
Bending Spoons has completed 50+ acquisitions and never sold a material business, using integration itself as a defensive strategy that forecloses exit options.
"If you integrate it with all the other businesses you have bought, it's gonna be extremely difficult, if possible at all, to sell it to someone else."
Bigger deals, not more deals, is the scaling strategy
Because transformation effort is roughly fixed regardless of deal size, Bending Spoons is pushing toward fewer, larger acquisitions rather than volume.
"We prefer to acquire 5 or 10 businesses each year, but bigger, than 50 smaller ones... So far, we see no end in sight. There's no obvious saturation point."
Centralized proprietary infrastructure is the real value driver
A shared platform of 50+ internally-built tools (data, A/B testing, payments, recruiting, AI orchestration) is what makes rapid integration and margin expansion possible.
"It's difficult to know exactly how much we're saving by building this in-house, but I'd wager it's at least $100 million a year in costs."
AI is transforming operating leverage, not just product features
95% of code is now AI-written, and every employee has a permissioned AI agent ("Alt Spooner"), driving revenue per employee from ~$1M to ~$4M in 2-3 years.
"We end up using open-weight models we self-host, so these are basically free, for 99% of the requests and tokens, and the frontier models... for maybe 1% of the requests."
Old, "unfashionable" brands are mispriced assets, not dying ones
Legacy platforms (AOL, Evernote, etc.) retain massive usage that the market undervalues because they aren't culturally "hot."
"We have half a billion (500,000,000) monthly active users. So if half a billion people using these products every month is a graveyard, then sure, let's call it that."
2. Contrarian Perspectives
The 2021 VC bubble was an investor failure, not a founder or company failure. Ferrari defends founders who raised at peak valuations (e.g., Airtable at $11B, later sold to Bending Spoons at $1.285B) as behaving rationally, and blames the incentive structure of venture capital itself.
"When investors are ultimately incentivized by managing as much capital as possible as opposed to actually delivering strong returns... then you will get hype cycles... If anybody made a mistake there, it was the investor, certainly not the company."
Vendor lock-in to frontier AI labs is a competitive weakness, not a shortcut to being "AI-enabled." Most companies default to buying expensive frontier-model access to look sophisticated; Ferrari argues this is inferior economically and strategically to building an independent, self-hosted model-routing layer.
"The easy approach is hand over the keys to one of these companies and buy their more expensive product. It will make you come across as AI-enabled faster and more easily, but it will be much less effective, certainly way more expensive."
AI's biggest danger isn't capability growth — it's that we're systematically underestimating current systems, and nobody is seriously addressing it. Rather than raising alarm about a specific technical risk, Ferrari argues the real gap is inaction, comparing the surgical precision of AI misuse unfavorably to nuclear weapons.
"I don't think anybody has done anything truly meaningful to make it safer... Maybe an interesting question that people haven't asked is why are we failing to do something about it? People are asking what we should do. Nothing is happening."
3. Companies Identified
Bending Spoons (NASDAQ: BSP) — Milan-based serial acquirer of digital products (AOL, Airtable, Vimeo, Eventbrite, Evernote, WeTransfer, Brightcove, Tractive, Remini, komoot, Harvest, StreamYard, Meetup). Central case study of the article as a buy-and-hold-forever operating model powered by proprietary tech and AI.
"Bending Spoons acquires digital businesses, installs them on a shared proprietary platform, and holds them permanently... more than 50 acquisitions and never sold a material business."
AOL — ~40-year-old legacy email/internet brand acquired by Bending Spoons. Cited as proof that "old" brands retain outsized relevance.
"To the company's knowledge the 5th most used email provider in the Western world... a decade of better-funded, better-covered email startups probably do not add up to 5% of AOL's activity."
Airtable — SaaS company that raised at an $11B valuation in 2021, later acquired by Bending Spoons at a $1.285B enterprise value. Used as the central example of the 2021 valuation bubble and its aftermath.
"Investors ultimately got back approximately all the money they had put in, plus more."
Miro — Recently agreed acquisition target (post-IPO) at $1.355B, signaling continued large-scale M&A appetite.
Amazon, Google, Meta — Referenced as comparably acquisitive tech giants to push back on the "Bending Spoons = private equity" comparison.
"Amazon, Google and Meta have all made hundreds of acquisitions and raised prices repeatedly, which makes the category unhelpful."
4. People Identified
Luca Ferrari — Co-Founder & CEO of Bending Spoons. Central subject of the interview; source of all strategic, cultural, and AI-related insights above.
Howie (Airtable, unspecified last name) — Referenced as disciplined founder/leadership at Airtable during its 2021 raise and eventual sale.
"If anything, Howie and the team were incredibly disciplined."
Francesco Patarnello — Co-Founder & Head of M&A at Bending Spoons, featured in Part I of the series (not deeply covered in this piece).
Matteo Danieli — Co-Founder & VP of Product at Bending Spoons, featured in Part I.
Valentina Jerusalmi — General Manager of AOL at Bending Spoons; cited as an example of frontline AI usage (using her "Alt Spooner" agent to diagnose and fix a bug in one day).
"She spent about 3 minutes, the lead spent an hour or two reviewing, and the bug shipped the same day."
5. Operating Insights
- Build tools where the pain is felt, then centralize. Bending Spoons lets whichever business unit needs a tool build the first version; a platform team only takes over once it's proven useful — avoiding "academic" over-engineering.
"When you have experienced the pain of a certain problem, you're far more likely to develop an actually useful solution, as opposed to taking a more academic angle."
- Hire for care over raw intelligence, and structure the org so top talent can move internally rather than leave. This drove voluntary churn down to 0.6% (vs. ~5% industry-good) and let revenue per employee jump 4x.
"We'd rather work with slightly less intelligent people if it comes down to that, but they have to really care... That employer brand can only exist if you structure your company like Bending Spoons."
- Institutionalize truth-seeking through mandatory experimentation. Running 3,000+ documented experiments a year forces decisions to be evidence-based rather than ego-based, and is credited with expanding the company's capability range (iOS → web → enterprise → hardware).
"Most people don't actually seek the truth. They seek pleasure or comfort, and they wanna just confirm that they're right and they're good."
6. Overlooked Insights
- The AI model-routing architecture is a quietly massive competitive advantage. Burying it under the "95% AI-written code" headline is the detail that Bending Spoons self-hosts open-weight models for 99% of requests and only pays for frontier/closed models on the hardest 1% — a cost-structure insight that most AI-native companies are not replicating.
"We end up using open-weight models we self-host, so these are basically free, for 99% of the requests and tokens."
- The predictability filter quietly excludes an entire asset class (AI startups) despite Ferrari's personal enthusiasm for AI as a technology. This is a sharper acquisition-discipline signal than it first appears — he's essentially saying the current AI venture boom (86% of US VC dollars in H1 2026, $355.9B of $412.7B) is unbuyable under his own investment framework, not because AI lacks value but because of unprovable growth trajectories.
"When something is growing 100% a year, you only have one or two years of history, it's very difficult to know whether they'll be growing at 100% in three years or at 12% in three years, and that changes everything."