You’re reading The Steady Beat, a weekly round-up of hand-picked articles and resources for people who make software products: designers, engineers, product managers, and organizational leaders. Brought to you by the team at Steady.
By the Numbers - Teens and ChatGPT
26 — The percentage of U.S. teens who have used ChatGPT for schoolwork, a striking 100% increase from just 13% in 2023, according to a new Pew Research Center survey.
79 — The proportion of U.S. teens who say they’ve heard of ChatGPT, up 12 percentage points from 67% in 2023, showing the AI chatbot’s rapidly growing cultural penetration.
54% — Just over half of teens believe it’s acceptable to use ChatGPT to research new topics, while only 18% think it’s OK to use it for writing essays (with 42% firmly against this application).
26 — The percentage point increase in ChatGPT awareness among teens in the lowest-income households (jumping from 41% to 67%), compared to just an 11-point increase among teens from higher-income families.
— Pew Research Center, 5m, #chatgpt, #education, #teens
Code Hallucination
Unlike hallucinations in text (which can silently torpedo your reputation), phantom code functions announce their falseness by immediately crashing when executed. The real danger lies in code that looks perfect, runs without errors, but subtly fails to deliver the intended functionality. As Simon Willison points out, your job as a developer remains unchanged: manually test everything, never trust code you haven’t seen working, and remain appropriately skeptical even when the AI produces beautiful-looking solutions. If hallucinations are bogging you down, try different models, feed examples into context, or stick with boring, established technologies that models know better.
— Simon Willison’s Weblog, 5m, #ai, #software-development, #hallucinations
Prompt Engineering Design
Alex Klein argues that the rush to implement AI has created a dangerous misconception that AI doesn’t need design, just engineering. Klein introduces the metaphor of “wire prompts versus cloth prompts,” channeling Harlow’s monkey experiments to illustrate how technically functional AI (wire) fails against AI designed with human needs in mind (cloth). The piece challenges the industry’s current approach, suggesting that no matter how magical AI seems, it remains useless without thoughtful design intervention. As Klein pointedly observes, steering AI models isn’t like traditional software engineering where specific code yields predictable outcomes - it requires continuous refinement through an iterative design process.
— UX Collective, 12m, #prompt-design, #ai, #product
Tasty Software
As software becomes increasingly commoditized (especially in the AI era), simply building something functional is no longer impressive—it’s expected. The real competitive edge now comes from developing good taste, argues Emil Kowalski. Just as cars evolved novelties to products differentiated by design details, software needs that same refinement. But taste isn’t subjective preference; it’s a trainable instinct. Kowalski offers a three-part recipe for developing this crucial skill: immerse yourself in great work (study what the best in your field create), analyze why certain designs feel exceptional (move beyond gut reactions), and practice relentlessly while seeking quality feedback. Expect a gap between your taste and your abilities at first—that frustrating chasm is actually proof you’re on the right track. As Anu Atluru aptly puts it: “In a world of scarcity, we treasure tools. In a world of abundance, we treasure taste.”
— Developing Taste, 5m, #design, #product, #taste
Tech Debt Is Dead?
In a refreshingly honest take on tech’s most overused justification for refactoring code, this piece argues we should replace the ambiguous concept of “technical debt” with “optionality” from finance. Rather than framing engineering work as paying off an abstract debt (which often breeds distrust from non-technical stakeholders), we should think about creating flexibility in our systems. Just as an open train ticket becomes more valuable during disruptions, well-designed software becomes more valuable in volatile business environments. But beware overinvesting—the author confesses to once building a perfectly architected integration that got scrapped before ever launching. The future of engineering isn’t just shipping code (AI can do that) but cultivating optionality: knowing when and how to make systems extensible while still delivering immediate value.
— LeadDev, 7m, #tech-debt, #leadership, #development
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