Changing the AI narrative from liberation to acceleration (idratherbewriting.com)

A provocative essay prompted by recent AWS tech-writer layoffs reframes the common “AI will liberate us” story into a narrative of acceleration: AI doesn’t simply free up workers by doing tedious tasks — it speeds up every actor in a system, raising the volume and tempo of work across teams, companies, and industries. The author calls this the static pace fallacy — assuming output needs stay fixed even as productivity tools improve — and argues that early gains from AI are quickly neutralized as competitors adopt the same tools. The piece links this dynamic to Kurzweil’s Law of Accelerating Returns: AI is a tool that builds more tools, creating feedback loops that compress innovation timelines and intensify competitive pressure. Technically, the essay emphasizes a key bottleneck: AI accelerates content generation but not human validation. Validation workflows — ticket creation, source identification, changelists, SME review, presubmit tests, approvals, deployment verification and release notes — impose hard limits on velocity. That means layoffs aimed at replacing humans with AI risk undermining a company’s ability to keep pace as release cadences and complexity accelerate. For AI/ML teams the implication is clear: focus investment not just on generation models but on end-to-end automation, human-in-the-loop tooling, validation, observability, and processes that scale review and quality assurance, or risk falling behind in a faster-moving competitive landscape.