The right kind of AI sceptic

2026-06-12 · Source: The Engineering Manager · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, long

Summary

The article distinguishes between two types of AI skeptics and enthusiasts, arguing that the *manner* in which one holds an opinion on AI is more crucial than the opinion itself. It identifies "scepticism as a conclusion" (informed by experience) versus "scepticism as an identity" (inherited without firsthand exposure), and mirrors this with ungrounded enthusiasm. The author highlights the dangers of ungrounded positions, citing instances like Klarna's premature claims about AI replacing 700 support agents and vague corporate metrics on AI-generated code. To foster informed perspectives, five practices are recommended: actively using AI tools, differentiating between capabilities and speculative claims, articulating specific skepticism, defining what would alter one's view, and engaging with robust counterarguments. These principles also apply to team leadership, encouraging an environment of experimentation and outcome-driven discussions rather than enforced beliefs.

Key takeaway

For software engineers and engineering leaders evaluating AI tools, your approach to forming an opinion is paramount. Avoid adopting views without firsthand experience; instead, actively use AI tools on real problems to earn your perspective. Be specific about AI's limitations and capabilities, and openly consider what evidence would shift your stance. This fosters genuine engagement and informed decision-making, preventing ungrounded enthusiasm or dismissal from hindering team productivity and innovation.

Key insights

The critical factor in AI engagement is *how* one holds their view—informed by experience versus adopted as identity—not the view itself.

Principles

• Scepticism or enthusiasm should be a conclusion, not an identity.
• Separate observable AI capabilities from speculative predictions.
• Define what evidence would change your current AI perspective.

Method

Form an informed AI opinion by using tools hands-on, distinguishing capabilities from claims, making skepticism specific, identifying conditions for changing your mind, and engaging with strong opposing views.

In practice

• Use AI tools like Claude Code or Cursor for real work.
• Analyze UX with AI-powered friction logs.
• Share AI experiments, including failures, with your team.

Topics

• AI Scepticism
• Informed AI Opinion
• AI Tool Adoption
• Engineering Leadership
• Cognitive Biases
• Organisational Culture

Best for: Director of AI/ML, Software Engineer, Consultant

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• Why opinion on AI is so divided — Divergent AI perceptions stem from a "jagged frontier" of capabilities and varied user experiences.

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Editorial summary, takeaway, and curation by AIssential. Original article published by The Engineering Manager.