You’re reading The Steady Beat, a weekly pulse of must-reads for anyone orchestrating teams, people, and work across the modern digital workplace – whether you’re managing sprints, driving roadmaps, leading departments, or just making sure the right work gets done. Curated by the team at Steady.
AI’s Implementation Gap
McKinsey’s latest survey reveals a curious paradox: 78% of organizations now use AI in at least one business function, yet more than 80% aren’t seeing meaningful bottom-line impact. The gap between adoption and value isn’t mysterious, it’s organizational. Companies are treating AI like a technology problem when it’s really a workflow problem. The winners are doing something different: they’re redesigning how work actually gets done, not just sprinkling AI on existing processes. CEO oversight of AI governance correlates most strongly with EBIT impact, especially at larger companies. These organizations are also more likely to track KPIs for AI solutions, establish clear adoption roadmaps, and hire specialized roles like AI compliance specialists. Meanwhile, the workforce impact remains murky. 38% expect little change to head count, though financial services leaders anticipate reductions. The real story isn’t about the technology’s capabilities; it’s about the organizational muscle required to capture value. Most companies are still treating gen AI as an experiment rather than an operational transformation, checking outputs inconsistently and implementing best practices sporadically. Until organizations fundamentally rewire their operations around AI rather than bolt it onto existing structures, the gap between adoption rates and business impact will persist.
— McKinsey & Company, 12m, #ai, #transformation, #leadership
Nodding Isn’t Agreement
Here’s the thing about engineering meetings: everyone’s nodding, but half the room is already planning their workarounds. Silent disagreement is the productivity killer that doesn’t announce itself until deadlines slip and suddenly nobody remembers being “aligned.” The pattern is depressingly familiar: you leave a kickoff meeting thinking the path is clear, only to discover weeks later that someone’s still building features in the old system because they weren’t sure the new one was stable yet. The problem isn’t that people disagree, it’s that they don’t feel safe saying so out loud. Watch for the warning signs: the “yeah, makes sense” that leads nowhere, the quiet room where only three voices speak, the endless “what about” questions that circle without landing, the public agreement followed by private venting, and the dreaded “let’s take this offline” that never comes back online. As you climb the ladder, your job shifts from writing code to driving alignment – and that’s where technical brilliance alone hits a wall. The solution isn’t demanding agreement; it’s creating clarity about where agreement exists and where it doesn’t. End meetings with written next steps, follow up one-on-one with the quiet ones, and most importantly, reward disagreement instead of punishing it. Chase clarity, not harmony.
— The Hustling Engineer, 5m, #engineering, #leadership, #coordination
The Learning Loop
Software development isn’t an assembly line, and LLMs won’t change that fundamental truth. This piece cuts through the productivity hype to remind us why code generation tools are great at getting you started but terrible at making you smarter. The core argument: writing software is an act of learning – observe, experiment, recall, apply – and no AI can do that learning for you. Sure, LLMs excel at boilerplate, environment setup, and translating plain English into specialized syntax across countless languages and tools. They’re phenomenal brainstorming partners. But the moment your requirements deviate from the standard path, that initial velocity evaporates into a maintenance nightmare. The author draws a sharp parallel to low-code platforms: both offer ephemeral speed that masks a hidden cost: you get functionality without internalized knowledge. The real capability in software isn’t how fast you can generate code, it’s how deeply you understand the system you’re building. Agile taught us this twenty years ago with its emphasis on iterations, pairing, and continuous learning. LLMs are powerful leverage, but only if we remember that shortcuts bypass the essential learning required to build systems that actually last.
— Martin Fowler, 8m, #engineering, #ai, #leadership
Systems Over Hustle
Most managers are drowning in meetings and firefighting because they’ve never built the infrastructure that makes strategic thinking possible. Gaurav Jain maps the escape route with six foundational systems that separate reactive managers from strategic leaders. Vision and Alignment gives your team a reason to care beyond just managing tasks. Prioritization and Decision Making creates objectivity so you can say no gracefully and invest time in what moves the needle. Risk Management helps you spot weaknesses before they bite – slowly at first, then all at once. Problem Solving teaches you to ask better questions instead of jumping to answers that fix symptoms while missing root causes. Team Development builds trust and psychological safety, because great teams aren’t born, they’re built. Feedback and Communication ensures your guidance actually lands instead of creating the illusion that communication happened. The path to strategic leadership isn’t working harder or attending more meetings, it’s building systems that free you from constant firefighting. Start with whichever system addresses your biggest pain point today, because you can’t think long-term when you’re perpetually stuck in reactive mode.
— The Good Boss, 7m, #leadership, #systems, #strategy
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