How to Become a UX Generalist

Step 1: Map Your Dependencies

You can't eliminate bottlenecks if you don't know what they are. Review your last 2 weeks of work. Look at your calendar, Slack messages, emails, and project timelines. Find every instance of "waiting for..." or "blocked on [team]" or "asked [person] for this on Monday, still waiting."

Rank by frequency and delay time. Make a simple list: What you're waiting for, how often, average delay, estimated hours lost per month. Pick the top 3 bottlenecks. These are your targets.

A product designer might discover: data queries (3x/week, 3-day delay) = 36 hours/month lost. Engineering feasibility checks (1x/week, 2-day delay) = 8 hours/month lost. Copy/content (2x/month, 1-week delay) = 16 hours/month lost. Total time lost to waiting: 60 hours per month.

Step 2: Learn Just Enough, Just in Time

Pick ONE blocker from your list. Use Claude or ChatGPT to learn the basics. Ask AI to explain the fundamentals. For example: "I'm a designer who needs to run basic SQL queries. Explain the fundamentals I need to know to query a database for user behavior data."

Then attempt the actual task with AI assistance. Pick a real, low-stakes example from your work. A designer learning SQL might start with: "I need to see how many users clicked the signup button last week. Here's our database schema. Write me the SQL query." Claude writes the query. You run it. You get the answer in 10 minutes.

Aim for good enough to unblock, not expert-level. Your goal is 80% quality in 20% the time. You're not replacing the specialist. You're unblocking yourself on basics so they can focus on complex work.

Step 3: Bring Your Lens to Execution

Once you can execute in an adjacent discipline, embed your professional lens in how you prompt, iterate, and evaluate. Generic prompts produce generic outputs. Lens-embedded prompts tell the AI what perspective to adopt.

For UX professionals, that might look like: "Act as a UX professional. Before jumping to solutions, clarify the context and real problem. Consider analogous products we can learn from. When working on interfaces, prioritize leveraging existing components over creating new ones. Check whether this adds visual clutter or breaks consistency across the platform."

The lens persists. Designers who code still think like designers, bringing design thinking to technical decisions. PMs who prototype still think like PMs, bringing product logic to user flows. That diversity of perspective applied to shared capabilities multiplies organizational creativity.

Common Blockers

"I don't have access to the tools." Ask once for read-only access. Frame it as exploring to better understand your data/systems, not doing someone else's job. Most teams grant read access easily because it doesn't risk breaking anything.

"What if I do it wrong?" Start with low-stakes tasks. Verify output with the expert the first time. Build confidence. Ship imperfect work immediately over waiting 3 days for perfect work.

"This feels like I'm doing someone else's job." You're not replacing them. You're unblocking yourself on basics so they can focus on complex work. Most specialists appreciate this. They want to work on interesting problems, not repetitive requests.

Why This Works

Every time you wait for another team, you're making a trade: 3 days of waiting for a 10-minute task. Before AI, this made sense. If you weren't a specialist, you literally couldn't do the work. Now AI eliminated the technical barrier. You can write SQL with Claude's help, prototype with Cursor, build dashboards with AI assistance.

The barrier isn't technical anymore. It's psychological. The professionals thriving right now aren't the ones protecting their specialty. They're the ones eliminating their own blockers.