Talk delivered at Web Directions AI Engineer Melbourne, June 2026
When organisations talk about AI resistance in engineering teams, they usually diagnose it as technophobia, change fatigue, or job insecurity. I think they’re wrong and the misdiagnosis leads to the wrong response.
This talk argues that what most senior engineers are experiencing is fear of de-skilling, losing the hard-won expertise that defines their identity and their professional standing. When a tool can produce in seconds what took years to learn, the threat is to the thing that made the role meaningful.
Understanding that distinction changes everything about how you lead an AI rollout.
The talk covers:
- Why AI is creating cognitive debt alongside the productivity gains and why it’s invisible until it isn’t
- How flooding the development pipeline with AI-generated code makes the existing bottleneck both slower and less reliable
- Why your most cautious engineers are your early warning system
- Three practical things engineering leaders can do right now: name the fear properly, protect learning conditions, and make quality the floor rather than the ceiling
The data in this talk draws on research from Multitudes, Faros AI, METR, Tilburg University, and others.
Sources
Storey, M-A. “What I’m Hearing About Cognitive Debt.” margaretstorey.com, February 2026. https://margaretstorey.com/blog/2026/02/18/cognitive-debt-revisited/
Vaughan, D. The Challenger Launch Decision: Risky Technology, Culture, and Deviance at NASA. University of Chicago Press, 1996.
Willison, S. “Vibe coding and agentic engineering are getting closer than I’d like.” simonwillison.net, May 2026. https://simonwillison.net/2026/May/6/vibe-coding-and-agentic-engineering/
Rehberger, J. “The Normalization of Deviance in AI.” embracethered.com, December 2025. (Influenced the framing in Willison, above.) https://embracethered.com/blog/posts/2025/the-normalization-of-deviance-in-ai/
Peate, L. & Katial, V. “What matters most for AI rollouts: How you lead.” Multitudes, 2025. (Telemetry from 500+ developers, N=372 for metrics analysis.) https://www.multitudes.com/data-to-cut-through-the-hype
Peate, L. & Lei, Y. “What matters most for embedding AI: How you adapt.” Multitudes, March 2026. (N=428 survey respondents.) https://www.multitudes.com/what-matters-most-for-embedding-ai-how-you-adapt
Leo XIV, Magnifica Humanitas §100, Vatican (15 May 2026) https://www.vatican.va/content/leo-xiv/en/encyclicals/documents/20260515-magnifica-humanitas.html
Jussupow, E., Spohrer, K. & Heinzl, A. (2022). Identity Threats as a Reason for Resistance to Artificial Intelligence: Survey Study With Medical Students and Professionals. JMIR Formative Research, 6(3). https://doi.org/10.2196/28750
Leiden Declaration Working Group (2026). Leiden Declaration on Artificial Intelligence and Mathematics. Lorentz Center, Leiden University. https://leidendeclaration.ai
Xu, F. et al. “AI-Assisted Programming Decreases the Productivity of Experienced Developers by Increasing the Technical Debt and Maintenance Burden.” arXiv:2510.10165 (econ.GN), October 2025 (rev. January 2026). https://arxiv.org/abs/2510.10165
Faros AI. “AI Engineering Report 2026: The Acceleration Whiplash.” Faros AI, 2026. (Telemetry from 22,000 developers, 4,000 teams.) https://www.faros.ai/research/ai-acceleration-whiplash
Harvey, N. & Baolin, J. “Balancing AI tensions: Moving from AI adoption to effective SDLC use.” DORA / Google Cloud, March 2026. https://dora.dev/insights/balancing-ai-tensions/
Dasdan, A. et al. “Experience with GitHub Copilot for Developer Productivity at ZoomInfo.” ZoomInfo Engineering Blog, February 2025. https://engineering.zoominfo.com/experience-with-github-copilot-for-developer-productivity-at-zoominfo
Sands, M. et al. “New Grads are 1.5x More Likely to Use AI Daily.” Atlassian Teamwork Lab, April 2026. https://www.atlassian.com/blog/ai-at-work/new-grads-ai-skills-hiring-strategy
Shen, J.H. & Tamkin, A. “How AI Impacts Skill Formation.” Anthropic Safety Fellows Program, January 2026. https://arxiv.org/abs/2601.20245