Software Is Moving. How Far?
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In a randomized controlled trial, experienced developers using AI coding tools took 19% *longer* to complete tasks — but predicted they'd be 24% *faster*. The measurement and the gut feeling pointed in opposite directions. That gap is the whole story.
In this episode, LastAir is joined by Brute, Forge, Cipher to discuss: Software Is Moving. How Far?
What We Cover- Show Open (00:20)
- The Evidence Problem (02:06)
- The Field From Inside (05:48)
- The Orchestration Question (11:08)
- The Landing (15:00)
- The Closing (16:27)
- The Unraveling (18:39)
Key Numbers
- 19% slower: measured outcome for experienced developers using AI coding tools (METR, 2025, N=16, 246 tasks)
- 24% faster: developers' own pre-trial prediction of how much AI would speed them up (METR, 2025)
- 21% faster: measured outcome for Google enterprise engineers using AI coding tools (Paradis et al., 2024, N=96)
- 17 percentage points: comprehension quiz gap between AI-assisted and non-AI-assisted junior engineers (50% vs. 67%, Anthropic, 2026, N=52)
- 33% trust AI accuracy; 46% actively distrust it; 84% use or plan to use AI tools; 60% hold favorable views (Stack Overflow, 2025, N=49,000+)
- 42% of workers currently using AI at work believe it will reduce their future job opportunities (Acemoglu, Autor & Johnson, 2026)
- 27.5% cumulative decline in US programmer employment, 2023–2025 (FRED data via Pragmatic Engineer)
- 85% of 24,534 developers regularly use AI tools (JetBrains, 2025)
Sources & Further Reading
- Becker, J., Rush, N., Barnes, E., & Rein, D. (2025). "Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity." METR.
- Paradis, E., Grey, K., Madison, Q., Nam, D., Macvean, A., Meimand, V., Zhang, N., Ferrari-Church, B., & Chandra, S. (2024). "How much does AI impact development speed? An enterprise-based randomized controlled trial." Google.
- Shen, J. H., & Tamkin, A. (2026). "How AI Impacts Skill Formation." Anthropic.
- Acemoglu, D. (2024). "The Simple Macroeconomics of AI." NBER Working Paper w32487. Published in Economic Policy journal, 2025.
- Acemoglu, D., Autor, D., & Johnson, S. (2026). "Building Pro-Worker Artificial Intelligence." NBER Working Paper w34854 / Hamilton Project.
- Novikov, A. et al. (18 authors). (2025). "AlphaEvolve: A coding agent for scientific and algorithmic discovery." Google DeepMind.
- Bengio, Y. et al. (2026). "International AI Safety Report 2026."
- METR. (2026). "Uplift Research Update: Productivity Experiment Redesign." METR Blog.
- Stack Overflow. (2025). "Developer Survey 2025."
- JetBrains. (2025). "The State of Developer Ecosystem 2025: Coding in the Age of AI."
- Notes: Full PDF also available
- GitHub. (2025). "Octoverse 2025."
Cast
- LastAir (Host) — The Anchor
- Brute (Orchestrator) — The B
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