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.
Chaos Theory
Organizations are messy garbage cans where problems, solutions, and decision-makers collide randomly — a reality that makes AI adoption brutally complicated. Enter the “Bitter Lesson” from AI research: every time humans try to encode their hard-won expertise into AI systems, brute computational force eventually beats them. Chess grandmasters spent centuries perfecting opening strategies, only to watch AlphaZero learn from scratch and demolish them all. Now we’re seeing this play out in enterprise AI, where companies spend months mapping chaotic individual workflows before deploying any AI system. But what if that’s backwards? New AI agents like Steady’s Echoes skip the careful process mapping and focus directly on outcomes — define what good output looks like, then let AI find its own path through organizational chaos. This could mean all those undocumented workflows, informal networks, and broken processes that make CEOs put their heads on tables might not matter. Instead, what if we simply collected context, describe desired outcomes, and point agents at the former to help us get to the latter?
— One Useful Thing, 8m, #ai-adoption, #process-mapping, #organizational-theory
Deep End
Congratulations, you’re now responsible for humans instead of code. Scott Kosman delivers the unvarnished truth about first-time management: your job isn’t to do the work anymore, it’s to enable others to excel at theirs. You’ll miss the dopamine hit of closing tickets, but your impact shifts from visible commits to invisible systems that make everything else possible. You’re going to screw up — repeatedly — and that’s not a bug, it’s a feature. Because the goal isn’t perfection, it’s “f*ck up better each time.” Whether your boss is brilliant or toxic, don’t let their leadership style dictate yours. Most importantly, management is emotionally expensive, so protect your energy like you protect your production servers. You’re not expected to have all the answers — just the humility to admit when you don’t and the curiosity to figure it out together.
— Scott Kosman, 4m, #management, #leadership, #career-transition
Reality Check
Stack Overflow’s 2025 Developer Survey delivers a sobering splash of cold water on AI’s hype cycle. While 84% of developers use AI tools (up from 76% last year), nearly half actively distrust their accuracy. The most telling finding? 66% are frustrated with AI solutions that are “almost right, but not quite” — that maddening gap between promise and reality that turns productivity gains into debugging marathons. OpenAI’s GPT dominates usage, but Claude Sonnet climbed to second place in both desirability and admiration. Meanwhile, Python surged 7 percentage points in adoption, cementing its role as the AI era’s lingua franca. The survey’s 49,000 responses from 177 countries reveal a developer community that’s pragmatically embracing AI while maintaining healthy skepticism. The message to team leaders? Your engineers aren’t AI-resistant; they’re accuracy-obsessed. (AI for teamwork, anyone?)
— Stack Overflow, 8m, #ai-tools, #developer-productivity, #team-leadership
AI Coding Slowdown
A study by nonprofit METR tracked 16 experienced developers fixing real bugs for $150/hour and found something shocking: devs using Cursor were 19% slower than those coding without AI. The researchers watched 146 hours of screen recordings and discovered that while AI reduced time spent coding, it ate up even more time in waiting, reviewing output, and dealing with “IDE overhead.” However, developers still believed they were 24% faster, even after experiencing the slowdown firsthand. Only one developer — who had 50+ hours with Cursor — actually saw meaningful gains. AI expert Simon Willison’s take cuts to the heart of it: the learning curve for AI-assisted development is steep enough that most developers actually perform worse while climbing it. The lone speed demon, PhD student Quentin Anthony, offers sage advice: treat AI tools like actual tools with specific use cases, not magic bullets. His biggest insight? Context switching kills productivity, and AI forces constant mental gear changes that can knock you out of “the zone.”
— The Pragmatic Engineer, 5m, #productivity, #ai, #engineering
Teamwork for the AI Era
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With Steady, teams deliver better work 5X faster, without tedious meetings, misalignment, or coordination chaos.
Learn more at runsteady.com.
