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The Analog Foundation Paradox: Why Manual Skills Matter More in the AI Era0m 26s
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The Analog Foundation Paradox: Why Manual Skills Matter More in the AI Era

Build better judgment: train with analog methods (notes, paper prototypes) so you can evaluate and steer AI output with a sharper critical eye.

Sep 29, 2025 0m 26s

Gillian Salerno-Rebic and Maria Burke

Expert Insights

Gillian Salerno-Rebic and Maria Burke, founders of North + Form, stress the importance of solid foundational skills in the era of AI-assisted software development. Despite the technological advancements, they implore newer tech professionals not to overlook the value of manual, non-digital methods in understanding and crafting good software design and empathetic user research.

Gillian and Maria shed light on:

  • The importance of maintaining traditional methods of note-taking and design.
  • How analog skills can significantly enhance software design understanding.
  • The critical role of empathetic understanding in an increasingly AI-augmented working environment.
  • The need for a balanced approach to AI adoption.
I teach at the University of Texas at Austin and I always encourage my students take handwritten notes. Do a paper prototype, be as analog as possible. 'cause you are still learning for the next 3, 4, 5, 6 years about what good design is, what good research is, how to be, you know, have that empathetic lens.
— Gillian Salerno-Rebic and Maria Burke, Founders, North + Form

THE NEW DEFAULT angle

Action points balancing traditional methods with AI-assisted ones:

    • Protect analog methods: Despite the lure of technology, maintain and encourage the use of traditional skills, like hand-drawn prototypes, among your software engineering and design team.

    • Train with empathy: As AI takes on more tasks, develop a different type of 'AI literacy', focused on understanding from an empathetic standpoint. This can help the team better assess AI decision-making and user requirements in the design process.

    • Balance old and new: Adapt a blended methodology that balances new AI-assisted workflows with old, manual ones.

    • Continuous learning: Foster a mentality of life-long learning to keep abreast with AI advancements without letting go of foundational skills.