Mission Accomplished: How AI Finally Put Design Ahead (and Why That’s a Problem)

Mission Accomplished (Sort Of)

For decades, the mantra was simple: “We need design to be a quarter ahead of engineering.”

It sounded reasonable — aspirational, even.  But if we’re honest, no one ever really saw it happen - at least I didn’t. Somewhere along the way, design system support became the first thing to go, followed by user research. We shipped things untested, created one-off components, tolerated inconsistencies, and told ourselves speed was strategy. And if I am being VP of Design-level honest, it worked - the product moved forward, users saw improvement, ARR increased, and money was raised.

But it also created a cycle:  Iteration became triage.  Fix the loudest complaints. Patch the biggest pain points. Move on to the next thing. We invested heavily in the feature factory but called it something else - efficiently producing motion without meaning. It wasn’t malicious. It was survival. Businesses need revenue, customers need features, and “someday” was always when we’d clean up the mess.

Fast-Forward to Now with AI

2025: 94 feature enhancement pull requests are waiting for review first thing Monday morning. And new client features requested on Monday are ready for testing by Wednesday. Design, product, and engineering are all finally “ahead.” Mission accomplished. Honestly — it’s exhilarating. Everyone in the entire organization suddenly has agency. Ideas no longer die in backlog purgatory. Momentum finally beats meetings. The old frustration is gone: No more product managers juggling unread DMs while designers chase specs and engineers question priorities. The pipeline has become beautifully frictionless: Idea (AI) → Design & Code (AI) → Test it (AI) → Ship it (some AI). We should celebrate this. It’s an incredible achievement. But speed doesn’t guarantee that the idea was good, or that the design was right, or that the code was coherent. What it guarantees is that we can learn faster — if we stay human enough to interpret what we’re seeing.

The New Question

So now we have to ask: How do we make sure the inputs to AI are the right ones? How do we preserve human qualities — taste, intuition, judgment, context — while letting AI do what it does best: ingest, process, and execute?

Queue up your sci-fi channel. That’s where a cyborg metaphor comes in.

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The Cyborg Fusion

AI isn’t replacing humans; it’s fusing with us. We’re not competing with the machine — we’re becoming part of it. A single, symbiotic system where human intuition directs machine precision. But the cyborg only works when the inputs are clean. When we’ve codified our thinking, our brand, and our logic into systems that machines can interpret. And right now, many teams haven’t done that work. They cut design systems years ago, deprioritized UX research, and reduced design ops to “we’ll figure it out later.”

Now those missing structures are coming back to haunt the machine. We’ve built incredible AI-powered creation pipelines, but we’ve starved them of guidance. The result? A new kind of chaos: synthetic consistency that looks right but feels wrong. Speed that excites everyone and scares us a little. You see, we’ve introduced ghosts into the machine.

Design Systems as the Cyborg’s Operating Interface

A design system isn’t just documentation anymore — it’s the loading mechanism for efficient cyborg operations. It’s how we teach AI what “good” looks like: how our brand behaves, how interactions should feel, what our hierarchy means. When your system is healthy, your AI knows the language of your design. When it’s brittle or outdated, the machine hallucinates structure.

If you want harmony between human and machine, you need:

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-Design Systems – the grammar of your product language.
-Research – the empathy layer; real data, not vibes.
-Ops Integration – unified flow between design, product, and engineering.
-Clarity of Brand – the shared intention behind every decision.

These aren’t optional anymore. They’re how we feed the cyborg.

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The Human Role: Curator and Sensemaker

The irony is that AI has finally achieved the dream: design is ahead, product is ahead, engineering is ahead. But if we don’t bring discernment to what’s being built, “ahead” just means “faster toward somewhere.”

Our new role as designers, strategists, and product leaders isn’t just to create — it’s to curate. To feed the system better inputs. To build the infrastructure that helps AI design with integrity. To ask better questions about purpose and outcome. AI doesn’t need more prompts. It needs better context.

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The Path Forward: Cyborg Design

If we want AI to accelerate us — not replace us — we need to think like cyborg architects. We design the human–machine workflow itself: what the AI should do, what the human should decide, and how the system learns between them. It’s time to treat design systems, research and product workflow as core inputs, not afterthoughts. It’s time to rebuild the brand and operational clarity we traded for speed.

Because in the age of AI, clarity is scalability. Structure is power. And systems are how we live longer. The future isn’t human or AI. It’s human + AI, aligned by design. Here's a wonderful example of Cyborg Design @Zapier where ex @Mailchimp brand superstar Joe Montefusco works his magic.