Author Critiques Widespread, Performative AI Use

The author Kitty Giraudel published a personal essay titled "You Cannot Spell 'Pain' Without AI" on KittyGiraudel.com describing frustrations with contemporary AI use in industry and on social platforms. The author writes that coding models such as Opus 4.5 and GPT-5.2 became genuine game-changers in late 2025, and that by 2024 AI had moved toward ubiquity in workplaces. She reports joining Scilife in October 2024 when AI adoption there was limited. The author also notes routine personal usage of AI: drafting, research, and editorial review with tools she names, including Cursor and Claude, and describes performative, AI-written content on LinkedIn as a recurring irritation.

Industry reporting and practitioner experience document a rapid acceleration in developer-focused and general-purpose foundation models since 2024. Comparable accounts note that launch cadence for models with stronger coding and reasoning capabilities compresses evaluation and integration cycles for engineering teams. For practitioners, this compressed cycle increases pressure to establish robust evaluation, monitoring, and provenance controls before deploying AI-generated outputs into customer-facing or record-keeping workflows.

Observed patterns in similar transitions show that public platforms often amplify low-effort outputs because algorithmic engagement favors clarity and brevity. This creates incentives for actors to outsource voice and interaction to models, which can degrade signal, complicate moderation, and blur provenance of authorship. Those are industry-level dynamics, not claims about any single organization's motives.

For practitioners: watch how teams operationalize guardrails for AI-assisted writing and commenting, including provenance tagging, human-in-the-loop policies, and documentation practices. Observers should also track platform-level moderation and verification features that attempt to surface when content is AI-assisted, and the ecosystem of tools that audit or watermark model outputs.

The essay is a practitioner's critique that balances personal adoption of AI with concerns about performative use and downstream effects on discourse and the open web. The piece is qualitative and experiential rather than a data-driven study, and the author does not provide organizational roadmaps or proprietary metrics.