"We are mistaking the speed of generation for the speed of completion. After hundreds of hours of actual implementation, the reality looks a lot more like a shifting burden. I'm a firm believer in Josef Müller-Brockmann's principles of designing with intentionality, yet I've felt that initial rush of adrenaline when viewing the insane capabilities of each AI model."
"Ask yourself how many design docs at your company get updated after implementation starts. If the doc were genuinely useful as a design tool, you'd update it as you learn. Nobody does. The doc's job was never to guide the implementation. Its job was to get sign-off."
"You wouldn't adopt a new approach or tool without being sure it had a positive outcome for your work. AI is no different, and it doesn't get a free pass just because the discourse is louder."
"When an agent can produce hundreds of lines in minutes, and the engineer driving that agent can have fairly minimal involvement in the actual writing of the code, the intent of the change becomes the most important factor in communicating what that code is for, why it matters."
This curated resource collection for designers addresses the gap between AI's perceived capabilities and practical implementation reality. While AI models demonstrate impressive generation speeds, actual project completion requires more nuanced consideration. Design documentation often serves approval purposes rather than implementation guidance, becoming outdated post-launch. Designers should evaluate AI adoption critically, ensuring tools genuinely improve their work rather than adopting them due to industry pressure. As code generation becomes faster and cheaper, clear intent and communication become increasingly valuable for directing AI agents and maintaining project coherence.
#ai-adoption-in-design #design-documentation-practices #intentional-tool-implementation #ai-assisted-development #designer-critical-thinking
Read at Medium
Unable to calculate read time
Collection
[
|
...
]