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Markos Mylonakis
Most companies' AI strategy is accidentally creating new bottlenecks, not removing them. Right now there's a lot of excitement about using AI to blur functional boundaries. Engineers picking up design work. Designers writing code. Marketers producing compliance reports. This is genuinely valuable — it builds empathy, increases autonomy, and unblocks teams. I'm all for it. But the discourse is disproportionately focused here, and that's a problem. AI gives domain experts the ability to operate at 10x within their own function. It also gives outsiders the ability to contribute to that function at roughly 1x. Both matter. But one is a step change, the other is a rounding error. If your main AI play is getting people to do other teams' work, you're pouring ~1x effort into areas already heading toward 10x. Meanwhile, the functions those people actually own — their day job — are still stuck at 1x. You didn't eliminate a bottleneck. You relocated it. A company where engineering runs at 10x but product, design, legal, and marketing still operate at 1x is still a 1x company. Throughput is set by the slowest part of the system, not the fastest. The highest-leverage question every function can ask right now isn't "what other team's work can I do with AI?" It's "what does my own work look like when I'm 10x at it?" By all means go wide across functions. But the real ROI with AI today is in going deep within each and every function to unlock that 10x across the entire company.
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