AI coding tools might not be the productivity boosters many believe. A new study suggests developers using AI are actually 19% slower. They feel faster, but the reality highlights inflated expectations and challenges with code context. The podcast also discusses Meta's shift towards closed-source AI, raising questions about future collaboration in the industry. With calls for further research, the conversation underscores that adopting AI isn't just about speed—it's a transformative process requiring time and adjustment.
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insights INSIGHT
AI Tools Require Workflow Shift
AI coding tools can slow developers initially due to new workflows and wait times for AI outputs.
Productivity gains depend on adapting to these workflows and overcoming distractions like social media.
volunteer_activism ADVICE
Use AI Waiting Time Wisely
Utilize downtime waiting for AI code generations productively by tackling subtasks or pondering follow-up questions.
Avoid distractions like social media during AI waiting times to maximize focus and efficiency.
volunteer_activism ADVICE
Manage Attention During AI Waits
Fill AI generation wait times with focused thinking or a small unrelated task.
Manage attention actively to avoid wasting time during AI processing gaps.
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Are AI coding tools actually making developers less productive? A new study from Meta’s AI research nonprofit, METR, claims that developers using AI were 19% slower, even though they believed they were 20% faster. In this episode of the AI Daily Brief, we break down the study’s design, explore criticisms from Emmett Shear and other AI leaders, and explain why this experiment may not reflect real-world AI coding performance. From model limitations to the steep learning curve of tools like Cursor, we explore how AI-assisted development isn’t just about faster typing, but rather a new way of working that requires time, practice, and workflow adjustments. Get Ad Free AI Daily Brief: https://patreon.com/AIDailyBrief
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