Earn your scepticism

2026-06-11 · Source: The Engineering Manager · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, long

Summary

The article critiques the polarized online discourse surrounding AI, distinguishing between those who see it as transformative and those who view it as mere tooling. It argues that the critical factor is not whether one is optimistic or skeptical, but how that view is formed and held—either through hands-on experience and inquiry or as an unexamined identity. Ungrounded skepticism, often inherited, is contrasted with earned skepticism based on direct engagement. Similarly, ungrounded enthusiasm, exemplified by overblown claims like Klarna's 700 agent replacement or unverified AI code percentages, can damage organizations and fuel cynicism. The author proposes five practices for holding an informed view: actively using AI tools, separating verifiable capabilities from speculative claims, making skepticism specific, identifying what would change one's mind, and seriously engaging with strong opposing arguments. For leaders, this means fostering curiosity and experimentation, sharing personal discoveries, and focusing on outcomes rather than mandating positions.

Key takeaway

For engineering leaders navigating AI adoption, prioritize fostering a culture of informed inquiry over enforcing specific AI stances. Encourage your teams to gain hands-on experience with AI tools and critically evaluate their real-world impact. By modeling intellectual honesty—sharing both successes and failures—you cultivate a flexible environment where team members can develop earned opinions, leading to more effective and grounded AI integration rather than compliance or cynicism.

Key insights

Holding AI views through hands-on experience and intellectual honesty is crucial, not just the view itself.

Principles

• Skepticism as a conclusion differs fundamentally from skepticism as an identity.
• Ungrounded enthusiasm is as risky as ungrounded dismissal in AI adoption.
• Intellectual honesty demands updating views based on evolving evidence.

Method

Actively use AI tools for real work over sustained periods, separate capabilities from claims, make skepticism specific, ask "what would change your mind?", and engage with strong opposing views.

In practice

• Experiment with tools like Claude Code or Cursor for personal and team productivity.
• Leaders should share AI experiments, including failures, to foster team curiosity.

Topics

• AI Adoption
• Intellectual Honesty
• Critical Thinking
• Engineering Leadership
• AI Tools
• Organizational Culture

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

Related on AIssential

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