In the short run (about 6 to 12 months), AI will augment and increase coders' productivity rather than replace them.

Judge the period from February 2025 to February 2026. TRUE: evidence from that period shows that AI mainly raised software developers' productivity (field studies, firm reports or developer surveys showing productivity gains) and did not cause large-scale replacement. That means no substantial drop in employment of software developers or programmers clearly attributed to AI (BLS or equivalent employment data, credible labour-market studies). MOSTLY TRUE: augmentation dominates, but there is some modest, AI-attributed reduction in hiring of entry-level or junior coders, or the evidence on productivity gains is mixed in size. MIXED: credible evidence shows significant AI-attributed displacement, such as clear declines in coder employment or hiring tied to AI, alongside augmentation, with neither clearly dominant. Rigorous studies finding no productivity gain or a slowdown also count towards mixed. MOSTLY FALSE: replacement effects (AI-attributed layoffs or employment declines) clearly outweigh augmentation, though some productivity gains exist. FALSE: AI substantially replaced coders in this period, with large AI-attributed employment declines, and there is little evidence of productivity augmentation.

Set before the research began.

1. E1 The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers Kevin Zheyuan Cui, Mert Demirer, Sonia Jaffe, Leon Musolff, Sida Peng, and Tobias Salz (academic working paper; authors at Princeton, MIT, Microsoft, Wharton) · June 2025

   “when data is combined across three experiments and 4,867 developers, our analysis reveals a 26.08% increase (SE: 10.3%) in completed tasks among developers using the AI tool.”

2. E2 The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers Kevin Zheyuan Cui, Mert Demirer, Sonia Jaffe, Leon Musolff, Sida Peng, and Tobias Salz (academic working paper; authors at Princeton, MIT, Microsoft, Wharton) · June 2025

   “Notably, less experienced developers had higher adoption rates and greater productivity gains.”

3. E3 We are Changing our Developer Productivity Experiment Design METR · 24 February 2026

   “Our early 2025 study found the use of AI causes tasks to take 19% longer, with a confidence interval between +2% and +39%.”

4. E4 We are Changing our Developer Productivity Experiment Design METR · 24 February 2026

   “Based on conversations with study participants, we believe it is likely that developers are more sped up from AI tools now — in early 2026 — compared to our estimates from early 2025.”

5. E5 The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers Cui, Demirer, Jaffe, Musolff, Peng and Salz (academic working paper; authors at Princeton, MIT, Microsoft, Wharton) · June 2025

   “Though each experiment is noisy, when data is combined across three experiments and 4,867 developers, our analysis reveals a 26.08% increase (SE: 10.3%) in completed tasks among developers using the AI tool.”

6. E6 The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers Cui, Demirer, Jaffe, Musolff, Peng and Salz (academic working paper; authors at Princeton, MIT, Microsoft, Wharton) · June 2025

   “Notably, less experienced developers had higher adoption rates and greater productivity gains.”

7. E7 Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence Brynjolfsson, Chandar, Chen (Stanford University / NBER; ADP administrative payroll data) · 26 August 2025

   “We find that since the widespread adoption of generative AI, early-career workers (ages 22-25) in the most AI-exposed occupations have experienced a 13 percent relative decline in employment even after controlling for firm-level shocks.”

8. E8 AI and Job Postings: From Destruction to Creation? - Indeed Hiring Lab Indeed Hiring Lab · 8 July 2026

   “US software development job postings have grown by almost 15% since the launch of Claude Code in late February, 2025, while overall job postings fell by 7% over the same period.”

9. E9 Announcing the 2025 DORA Report | Google Cloud Blog Google Cloud (DORA research program) · 23 September 2025

   “AI adoption is near-universal: 90% of survey respondents report using AI at work. More than 80% believe it has increased their productivity.”

10. E10 Fact-Check: Did AI Replace Software Engineers? What the Data Shows (2026) - IoT Digital Twin PLM IoT Digital Twin PLM · 24 October 2026

    “No. US government data show roughly 1.7 million software developers in 2025 and a projected 10 percent growth through 2035.”

A combined field experiment with 4,867 developers found a 26% increase in completed tasks with an AI tool (E1). The 2025 DORA survey reports that more than 80% of respondents believe AI raised their productivity (E9). Against this, METR's early-2025 study found AI made tasks take 19% longer (E3), although its February 2026 update says developers were likely more sped up by early 2026 (E4). On replacement, Indeed reports that US software development postings grew almost 15% since late February 2025 while overall postings fell (E8), and payroll data show a 13% relative employment decline among workers aged 22–25 in the most AI-exposed occupations (E7). Taken together, augmentation dominates, with mixed evidence on the size of productivity gains and a modest early-career decline, which fits the mostly-true criterion.