Notes on transformation.
Or: why hard skills got me hired, and curiosity got the work done.
The frameworks are abundant now. There are playbooks for AI adoption, change management, product discovery, organizational design. Tools have collapsed barriers that used to gate this work: Claude Code can write a working prototype while I'm in a meeting; Sigma can put a dashboard in front of a CTO before lunch. The work has never been more leveraged.
What the leverage doesn't change is what transformation actually requires of the practitioner.
I came out of MIT and the trading desk thinking the work was about hard skills. Bond pricing, options sensitivities, structured derivatives. Show me the spec, defend the math, ship the model. The market rendered judgment by the close.
My first major transformation taught me something different: slowly, and at some expense.
I was at Deutsche Asset Management on the Aladdin migration. Multi-year, multi-region program. Portfolio managers, traders, compliance officers, risk managers. New York, Frankfurt, London. I arrived with the trading-floor instinct: the new system has real advantages, the old system has limitations, here is the spec, let's go.
What I underestimated, badly, was the obvious thing. The people running the existing systems had built them. They had earned their positions through years of careful work. They had relationships with the platform, with each other, with clients who had specific expectations about how things ran. They were not standing in the way of progress. They were the reason the firm had progressed this far.
The detractors (the people I initially saw as obstacles) were often the most knowledgeable in the room. They knew exactly which edge cases would break the new system. They knew which integrations the spec had glossed over. They knew which client relationships would crack under which changes. Their resistance wasn't ignorance. It was institutional memory expressed as concern.
Treat them as obstacles and you lose. Treat them as teachers and the program has a chance.
That single shift (from logical advocacy to sustained curiosity) changed how I do this work.
The outsider with a good argument
The failure mode I see most often in technology-led transformation is what I came in with: an outsider with a good argument, walking into an organization that has been doing things its own way for thirty years. Where the existing approach has produced real results (and in financial services, the people in the room are smart enough that it has produced real results), a logical argument from outside rings hollow. It doesn't matter that the argument is correct. It registers as: this person doesn't understand what we built or why we built it.
The detractors are often the smartest, hardest-driving people on the floor. They are not the ones to convert last. They are the ones to learn from first.
The champions, and the middle
The champions are the other half. Every organization has people who have been waiting for the change: practitioners who can see what the next system enables, who are quietly frustrated by current limits, who will move quickly when given air cover. The work is finding them, supporting them, and letting them speak. They carry credibility you cannot import.
The largest group, in any transformation, is neither detractors nor champions. It's the middle: the people watching to see how this plays out before committing. They take their cues from how the detractors are treated and from how the champions are heard.
If detractors get steamrolled, the middle learns that this leadership doesn't listen, and the program slows. If champions get sidelined for political reasons, the middle learns that this leadership doesn't have the courage of its convictions, and the program loses momentum. If detractors and champions both get heard (if their disagreement is worked out openly, not in a deck), the middle learns that this is a serious effort, and they come along.
What the AI moment doesn't change
This is the part of the work that AI does not change. The tools are better. The leverage is real. The frameworks are mature. But transformation still requires the practitioner to be more curious about people than about being right.
The end game is not efficiency. Efficiency is the byproduct. The end game is people choosing to do things differently, which they will only do if they trust the person asking.
The technical work has gotten easier every year. The other work has not.
I have built systems for sixteen years now, in financial services and out: capital markets, asset management, risk, and now in AI. The technical work has gotten easier every year. The other work has not.
I write this for anyone who came up the way I did (the engineer, the trader, the analyst, the founder), for whom hard skills were the original tools. Hard skills will always matter. They are why we get into the rooms. But the work that happens once we are in the room is something else. It is closer to listening, and closer to teaching, and closer to a kind of patience I did not have when I was twenty-six.
// DG