TL; DR: Sabotaging AI — Food for Agile Thought #516
Welcome to the 516th edition of the Food for Agile Thought newsletter, shared with 40,359 peers. This week, Jenn Spykerman addresses unknowingly sabotaging AI according to a 1944 manual, masquerading endless committees, perfectionism, and cautious delays as good governance. Leah Tharin challenges claims that LLMs can stand in for real customer insight, warning that dashboards can fuel strategy theater, while John Cutler connects prioritization to strategic leverage and power dynamics. Jing Hu reframes AI failure stats as early-stage noise, and Duncan Brown warns that AI favors the visible over the messy, human glue that makes effective teams work.
Next, Chetan Kapoor shows how eBay uses feature flags as discovery tools to validate demand early and surface usability issues. Kyle Poyar critiques popular SaaS pricing models and shares fixes that avoid complete overhauls. Ethan Mollick maps the current AI landscape with practical guidance on tools, tiers, and tactics. At the same time, Zvi Mowshowitz highlights key takeaways from Karpathy’s AGI views, and James Shore reframes engineering accountability through product bets instead of features and deadlines.
Lastly, Anthropic’s Claude receives “skills” as modular guides for specialized tasks, now open-sourced on GitHub. One author explores how great teams grow through targeted support and bold delegation, and Jeff Sauro and Jim Lewis dissect NPS claims, separating useful signals from misleading noise. Charlie Guo calls out the creeping signs of AI-generated content and its cost to authenticity. Finally, Karen Dahut presents Google Skills, a vast new learning platform for AI and tech upskilling.
