Gm Fintech Architects —
Today we are diving into the following topics:
Summary: In this article, we examine how AI is transforming the org chart itself, shifting companies from Amazon-style two-pizza teams toward “AI-native” pods of 3–5 people with dramatically higher productivity. We compare Klarna’s failed AI substitution strategy, which cut headcount from 5,500 to 3,400 before quality issues forced rehiring, with Coinbase and Ramp, which are reorganizing around AI augmentation and orchestration instead. Coinbase cut 700 employees while moving toward one-person product teams and AI-generated code, while Ramp built an internal AI harness used daily by 99.5% of employees across 350+ workflow skills. We also explore how firms like Box and Plaid are being repriced as AI infrastructure companies because they control permissioned enterprise data that agents need to operate.
Topics: Anthropic, Coinbase, Brian Armstrong, Klarna, Sebastian Siemiatkowski, Bloomberg, Gartner, Ramp, Eric Glyman, Glass, Manus, OpenClaw, Anthropic Cowork, Polsia, Box, Aaron Levie, Dropbox, Plaid, Visa, Perplexity, Mint.com, Sam Altman, Dario Amodei, Sequoia, Y Combinator, Amazon
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Long Take
The third version of the org chart
A few months back, we talked about Zero Human Companies, and the AI Economic Autonomy curve:
While there are efforts to build completely human-less organizations, the economy is still full of us humans running around. The messy work now is in transforming existing companies into their AI-first counterparts. This is such a big opportunity that Anthropic is working with the entire private equity industry to do it.
One place where we are also starting to see the impact — besides the headline numbers — is in the way people build and organize companies.
The org chart itself is a technology.
The Waterfall approach built big hierarchical software development monoliths that ruled the early tech era. This transitioned to lean teams deploying Agile methodologies, then Agile moved to the Amazon-designed two-pizza team. This operating structure has built every modern fintech.
But things are shifting yet again.
McKinsey’s Martin Harrysson and Natasha Maniar called the next version in late 2025: “AI-native roles essentially means we’re moving away from the two-pizza structure to one-pizza pods of three to five individuals.” Half the team, same output.
On May 5, 2026, Brian Armstrong added ammunition to the argument by firing 700 people.
What Coinbase actually did
Coinbase cut just 14% of its 4,951 employees.
In part, this is the market-cycle for a business that is still largely correlated with trading volume — Q1 earnings expected are at $1.70B revenue (down 26% YoY) with EPS down 86%. But it is worth paying some attention to how leadership talks about AI implementation in a modern fintech/crypto company, and what is expected in terms of per-employee productivity going forward.
Engineers at Coinbase now ship in days what teams used to ship in weeks, and the shift is accelerating. Armstrong is restructuring the business so there is a maximum five layers of seniority below the CEO and COO. There will be no pure managers — every leader carries an individual contribution role, which means they must be a player-coach who understands modern tooling. Cross-functional “AI-native pods” replace traditional teams, with experiments in one-person pods folding engineering, design, and product into a single role.
Coinbase, a $7B revenue public company, is running one-person product teams.
In September 2025, Armstrong had posted that 40% of daily code at Coinbase is AI-generated, with a target of 50% by October. On Stripe co-founder John Collison’s Cheeky Pint podcast, he admits firing engineers who refused to onboard Cursor and GitHub Copilot within a week of the enterprise license going live: “some of them didn’t and they got fired.”
V1 was substitution, and it failed
However, Coinbase isn’t the first fintech company to use AI as a reason for layoffs.
Remember that Klarna ran the textbook AI-cost-cutting experiment in 2024, suggesting incredible future productivity? We thought this looked a bit too much like a credit cycle crunch, not innovation.
CEO Sebastian Siemiatkowski announced the OpenAI-powered AI assistant had handled 2.3 million conversations in its first month — two-thirds of all customer chats — doing the work of 700 full-time agents.
Headcount went from 5,500 to 3,400
Projected profit improvement: $40MM
Resolution time from 11 minutes to 2
This all collapsed on contact with reality.