You’re reading The Steady Beat, a weekly round-up of hand-picked articles for people who coordinate teams and work, like engineering managers, design directors, product managers, project leaders, team facilitators, and department heads. Brought to you by the team at Steady.
Mandatory or Misguided
As AI coding tools become ubiquitous (76% of engineers now using or planning to use them), some companies are getting aggressive about adoption. When Shopify CEO shared an internal memo about enforcing AI usage, it raised important questions about implementation strategies. While AI certainly boosts productivity—engineering leaders report increases between 0.3-5x (nowhere near the hyped 100x)—making AI usage a KPI or creating leaderboards for “most AI credits used” risks employees gaming the system rather than producing quality work. The real challenge isn’t forcing adoption but addressing legitimate concerns: engineers worry about code quality, security risks, and overreliance. Instead of mandates, smart leaders are focusing on education, establishing clear usage guidelines, and measuring outcomes rather than tool usage.
— Engineering Leadership, 13m, #ai, #engineering, #leadership
AI Paronia
In a brilliant reexamination of Andy Grove’s “Only the Paranoid Survive,” Boardy Boardman proposes a critical update for the AI era: let artificial intelligence do your paranoia work for you. While Grove’s concept of “Strategic Inflection Points” and vigilant monitoring remains valid, today’s information tsunami makes human-powered paranoia a fast track to burnout and anxiety. The new winning strategy? “Delegated vigilance” – AI systems that monitor competitive threats, market shifts, and technological disruptions around the clock, alerting humans only when intervention is needed. As one Toronto founder told Boardy, “Grove’s insight about paranoia was right, but he never could have imagined the tools we’d have to delegate that paranoia. My AI systems do the worrying for me while I focus on building.”
— Boardy’s Substack, 11m, #ai, #strategic-management, #business-strategy
Teams are doing it wrong with AI
The quiet revolution isn’t robots stealing jobs—it’s that our thinking itself has become distributed between humans and AI. While low-performing teams treat AI as merely “faster candles” for productivity shortcuts, high-performing teams recognize we’ve entered an era of “distributed cognition” where intelligence lives in the interactions between humans and machines. These successful teams explicitly manage shared context, prioritize human judgment, establish intentional workflows, invest in prompt literacy, embrace asynchronous work, dedicate time to collective sense-making, codify trust through transparency, and iterate quickly—while avoiding the pitfalls of superficial AI usage, option paralysis, and outdated meeting cultures.
— Nate Jones, 29m, #ai-teams, #productivity, #leadership
AI Leadership via Human Judgment
While we’re drowning in AI hype, Glean’s Tamar Yehoshua offers a refreshingly grounded perspective: be “data-informed but not data-driven.” The product veteran suggests successful AI adoption requires curiosity over certainty, leadership by example, and recognizing that most features end up in the “graveyard” while only a precious few truly matter. Her most pointed insight? Despite AI’s capabilities, adoption still hinges on human behavior change, which remains stubbornly difficult. Companies rushing to implement AI often face resistance not because the tech isn’t ready, but because their organizations aren’t prepared for the workflow disruption that follows.
— McKinsey, 10m, #ai-adoption, #product-leadership, #change-management
Teamwork for the AI Era
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