After learning from our mistakes with the first version of the Risk Management Platform, I understood that waiting for different teams to align on different customer requirements feels responsible and safe. But in the AI era, it’s an expensive trap. This is the belief that replaced an older one, the one I described in Design Leadership Has Evolved.
This problem existed before AI. I watched it unfold slowly in almost every organization I worked in, including the years on reporting products before industrial cybersecurity. Design was always sitting between marketing and product, belonging fully to neither, each function negotiating across invisible walls. Everyone would leave a long meeting technically in agreement, but nobody was quite sure who made the call. The cost was measured in months, in rework, in products that were coherent inside each function and disconnected across the customer journey.
When agents can execute a week of work in an afternoon, that same dynamic doesn’t just drift. It can’t keep up with a design lead moving at agent speed. I have seen vague direction, fed into a well-trained agent, produce confident, well-built work going exactly the wrong way.
Clarity has to come first. Alignment is just an outcome.
Strong leaders don’t wait for alignment to emerge naturally. They make the call, hold the line, and let others orient around a decision that has been made rather than a consensus that has been negotiated.
Clarity shows up after motion
I used to think that if you framed a problem well enough, execution would follow cleanly. That’s not how complex systems behave. Clarity reveals itself after motion. Trade-offs only become tangible when something exists in the real world and people can express their opinions about it.
I learned this from watching other designers fail by avoiding anything real. Instead, I ask three questions before a project starts:
- What business problem are we solving?
- What metric are we trying to move?
- Who gets fired if this doesn’t work?
These questions felt uncomfortable at first. They weren’t design questions, but they were the questions that separated work that mattered from work that looked good and changed nothing. When someone says “we need a website refresh,” those questions reveal whether the actual problem is low conversion, confused positioning, or deals lost to competitors who look more credible. Each of those is a different project. A PM saying “make it look modern” solves none of them.
Vague direction fed to a powerful agent produces beautiful, well-engineered products that solve the wrong problem. The initial workflows implemented at Omny were technically precise but directionally wrong. The difference was a definition of the job operators were actually trying to do, which we hadn’t written down or made part of the context for both humans and AI before we started building.
Teams have to move fast to find the direction, and then let the AI agents execute. The sequence matters more than ever, because an AI agent isn’t going to know if it’s going the wrong way.
Also in March: Design Leadership Has Evolved · Ownership Beats Advocacy · Where the Capability Lives
Daniel Arevalo is Product Experience Lead at Omny Security. He builds AI-native tools and writes about design, product leadership, and what it means to direct systems that execute at a speed humans never had before.