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AI accelerates development: METR data and myths

The article analyzes the evolution of METR studies on AI's impact on development speed: from slowdown to acceleration. Analyzes Block and Klarna cases, where AI layoffs led to rehiring. Highlights growth in IT vacancies and salaries, risks of vulnerabilities in AI code.

Myths of AI layoffs: real numbers from METR and Block
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AI in Software Development: Real Data vs. Layoffs Myths

A July 2025 METR study found that 16 experienced developers using AI tools worked 19% slower on real open-source tasks. Confidence interval: +2% to +39%. Subjectively, developers estimated a 20% speedup.

February 2026 update: newer models, more participants. For returning developers: 18% speedup (interval: −38% to +9%). For newcomers: 4% speedup (−15% to +9%). The authors note only weak evidence of improvement—but the trend is shifting toward acceleration. Wide confidence intervals underscore the effect’s instability.

The first study went viral; the second went largely unnoticed. This illustrates media’s selective narrative framing.

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Block and Klarna Case Studies: Layoffs—and Rehiring

In February 2026, Block Inc. laid off 4,000 employees (40% of its workforce). CEO Jack Dorsey attributed this to 'intelligence tools.' Shares surged 24%; market cap rose $8 billion. Yet 2025 revenue stood at $24.2 billion—flat YoY—while net profit halved. Gross profit per employee rose from $500K (2019) to $1M (2025), but that trend began years earlier.

Piper Sandler analysts flagged rising transaction losses (from 11% to 18%). Block quietly launched rehiring efforts. Dorsey acknowledged flexibility to course-correct.

Klarna cut 700 support staff after deploying an AI chatbot. It saved $40 million across 2.3 million conversations—shrinking headcount from 5,000 to 3,000. Customer satisfaction dropped 22%. The bot failed on disputes and fraud. Engineers were flooded with tickets. The CEO admitted overreach.

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The shift toward 'Uber-style' gig work: lower pay, no benefits.

Key lessons from these cases:

  • Layoffs often deliver short-term stock boosts fueled by narrative—not productivity gains.
  • Declining quality metrics trigger rehiring—often under worse terms.
  • Forrester: 55% of employers regret AI-driven layoffs; one-third spent more on rehiring than they saved.

The Economics of Fear: Stakeholder Incentives

CEOs get immediate market reactions to the 'we’re AI-forward' story. Block +24%, Salesforce — down. Vendors (e.g., Anthropic) stoke fears of 'eliminating 50% of entry-level roles' to sell tools. OpenAI doubled its headcount to 8,000; 1.3 million AI-related jobs have been created (+13× since 2022).

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Media: clickbait headlines like 'AI Will Replace 80% of Developers.' Education: $2K–$25K courses promising 'AI-proof careers.' Consulting: Accenture tracks AI login activity for performance reviews.

Facts vs. Interpretations:

Verified data:

  • METR: trend toward acceleration—but wide confidence intervals.
  • 26.9% of production code now AI-assisted (up from 22%).
  • Lab studies show 55% speedup on routine tasks; real-world project gains are more modest.
  • U.S. IT salaries up 16.7% since 2022 (Dallas Fed).
  • 67,000 open engineering roles (+78%).
  • U.S. labor productivity up 2.7% (2025).

Interpretations:

  • Many layoffs reflect Wall Street storytelling—not automation-driven efficiency.
  • Panic serves stakeholders’ interests.
  • AI-literate developers remain highly secure.

Practice: AI’s Strengths and Weaknesses

AI accelerates:

  • Boilerplate, routing logic, database migrations, test scaffolding, and early drafts.

Example in Laravel: prototype built in 1.5 hours instead of months.

AI undermines:

  • 45% of developers spend more time debugging AI-generated code.
  • 45% of AI-written code contains OWASP Top 10 vulnerabilities.
  • CodeRabbit reports 1.7× more issues vs. human-authored code.

Recommendations:

  • Never delegate authentication or payment logic to AI without rigorous human review.
  • Use AI for routine tasks—but design architecture yourself.
  • Organized teams + AI = 50% fewer incidents; chaotic teams + AI = double the incidents.

What Matters Most

  • METR confirms a trend toward acceleration—but the effect remains unstable.
  • 55% of AI-driven layoffs are regretted, per Forrester.
  • IT salaries and job openings continue rising—despite alarmist narratives.
  • AI amplifies teams when used thoughtfully—not replaces them.
  • Manual review is non-negotiable for security-sensitive code.

— Editorial Team

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