What AI Can Do Is Not the Same as What It Should Be Allowed to Do
It is convenient when a product recognizes the situation and suggests what to do next. But bringing a useful menu to the front is very different from requesting a service on your behalf.
That boundary kept appearing in this week's articles: interfaces that adapt to context, agents that execute tools, and the roles people should retain after automation. The more a system can do, the more precisely we need to decide what to entrust to it.
This week, we're looking at automation with clear places for human intervention. This is not about adding a confirmation button to every step. It is about separating suggestions from actions and making room to stop or correct things when they go wrong.
Here are three key points from this week's articles👇
This Week's Signal
1️⃣ Understanding the situation is not permission to act
Situation-Centered Design: Designing Priorities Beyond Fixed Flows proposes bringing relevant actions forward while preserving familiar structure and choice. After an accident report, for example, a product could highlight emergency support, but requesting roadside assistance still requires separate confirmation. This is a design proposal, not a proven outcome. Even so, the distinction is clear: whether the system's inference is correct and whether it may act on that inference are different questions. The design also needs to explain what prompted the change and what happens when the user declines.
2️⃣ Finishing a response is not the same as finishing a task
Build Your Own AI Agent: From 50 Lines of Python to MCP breaks an agent down into a loop of decisions, tool execution, and observing results. That structure changes the states an interface needs to show. The model saying what it plans to do, the program actually executing it, and the result being checked are distinct states. Treating a fluent final response as proof of completion can hide failure or an action that never ran. Users need to know how far their task has progressed, whether it is awaiting approval, and whether it needs another attempt before they can confidently choose their next step.
3️⃣ What authority people retain matters more than their mere presence
Should UX Design Remain Human Work? introduces a different approach to protecting entire professions from automation: defining a minimum level of meaningful human participation. It separates direct involvement in relationships, final responsibility, and opportunities to learn through work. Having a reviewer is not enough by itself. If that person can only acknowledge the result without changing or stopping it, their participation means less. One way to read the article is that deciding which tasks to automate should go hand in hand with documenting the responsibilities and choices people retain.
Reads That Make It Clearer
- A UI/UX Design Workflow for Using AI While Preserving CreativitySeparates AI-generated hypotheses and reviews from evidence gathered from real users. It is useful for mapping which stages to delegate and which decisions to make yourself.
- How to Tell Design Decisions as a Story in UX InterviewsFocuses on the choices made under constraints rather than just what was built. It invites a closer look at where evidence of your contribution remains after automation.
This Week's Popular Tools
- GestaltPinterest's design system. A useful reference for accessibility and interface rules across languages and reading directions.
- OrbitKiwi.com's travel design system. Explore recurring booking-flow challenges involving dates, currencies, and itineraries.
- Cash App Design SystemA public design guide connecting product character not just to color and typography, but also to motion and tone of voice.
- GardenZendesk's design system. Covers patterns that help users continue working, including error guidance and preserving input.
- BladeRazorpay's design system. Alongside components, it offers references for distribution, contribution processes, and tracking adoption.
