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.
Everyone’s Staff
The old engineering career ladder is creaking under the weight of AI-generated code, and Jeff D’Auriemma has a provocative prescription: we’re all staff engineers now. Drawing from Tanya Reilly’s influential book on staff engineering, D’Auriemma argues that the traditional progression from writing code to managing complexity is being compressed into a single expectation. When Claude Code can brute-force implementations and LLMs are churning out production code, the careful craft of hand-writing software becomes less differentiating. What matters now? The traditionally “staff-level” skills of technical direction, cross-team coordination, and solving ambiguous problems. D’Auriemma imagines a world of “Junior Staff Engineers” who orchestrate between humans and models, vet AI-generated architectures, and triage emergent failures – essentially learning to see the forest while machines tend the trees. It’s deliberately hand-wavey and admittedly provocative, but the diagnosis rings true: if code is cheap and judgment is expensive, then every engineer needs to level up to the work that actually matters. The alternative – letting influential tech leaders cut the rungs off the career ladder entirely – is too grim to contemplate. So buckle up, because your daily standup just became a coordination layer for semi-autonomous agents, and you’re not so much managing code as managing epistemology itself.
— Jeff D’Auriemma, 6m, #engineering, #career development, #ai transformation
AGI Mythology
The tech world’s most consequential fairy tale – artificial general intelligence – has evolved from fringe concept to a half-trillion-dollar industry driver that justifies massive data centers, promises utopian futures, threatens apocalyptic endings, and fundamentally shapes how we allocate resources and regulate technology. MIT Technology Review traces how AGI went from Ben Goertzel’s 2007 book title to OpenAI’s founding mission, showing how this shape-shifting idea that nobody can properly define has become Silicon Valley’s dominant narrative. The parallels to conspiracy thinking are striking: unprovable claims, hidden truths only insiders understand, promises of salvation (or doom), and timelines that perpetually shift when predictions fail. While tech leaders like Sam Altman claim AGI will cure cancer and colonize galaxies, critics argue this mythology diverts billions from solving real, immediate problems – healthcare, inequality, climate – that require actual human cooperation rather than waiting for machine gods to save us. The real conspiracy might be that those pushing AGI hardest are the ones who profit most from keeping the dream perpetually six months away, recruiting talent and raising capital on a promise that’s just vague enough to never be disproven.
— MIT Technology Review, 24m, #ai, #leadership, #strategy
Pits of Success
Remember when your best developers would ship janky code because doing it right was too much of a pain? Netflix and Spotify fixed that problem by flipping the script: they engineered their platforms so the lazy path – the one developers take at 2 AM when they’re bleary-eyed and caffeinated – is actually the correct one. They call it the “Pit of Success” (Microsoft’s Rico Mariani coined it), where gravity pulls you toward best practices instead of disaster. Netflix slashed test cycles from 62 minutes to under 5, Spotify doubled deployment frequency, and Toyota saved $10 million in 2022. The secret sauce isn’t pushing developers harder; it’s building “Golden Paths” where security scans, tests, and dev check-ins happen automatically because they’re baked into the easiest workflow. When Atlassian implemented this approach with Snyk, they hit 100% container scanning coverage while reducing critical vulnerabilities by 39% – not through mandates, but by making security checks faster than skipping them. It turns out treating internal tools like actual products with developers as customers isn’t just nice-to-have developer happiness fluff, it’s a measurable competitive advantage that compounds over time.
— Pragmatic DX, 12m, #platformengineering, #developerexperience, #devops
Leadership Leveling
Gregor Ojstersek’s ascent from team lead to CTO reads like a masterclass in what not to do – until it becomes exactly what to do. The engineering leadership guru (whose newsletter reaches 170,000+ subscribers) maps the treacherous journey from managing one team to orchestrating entire organizations, and the plot twist? What makes you a rockstar engineer makes you a terrible manager. His first mistake as a team lead was trying to be Superman – coding the hardest features while managing stakeholders, facilitating meetings, and attempting to fix every organizational problem he spotted. Nearly burning out taught him the hardest lesson in tech leadership: your value isn’t in the code you write anymore, but in the code your team ships. The progression is brutally clear: leading one team means learning to let go of the keyboard, leading three teams transforms you from player-coach to full-time coach, and leading five-plus teams? That’s when you discover your real team isn’t engineering – it’s the executive suite. Each level demands shedding another layer of control, until success becomes entirely about what your people can build, not what you can.
— Engineering Leadership Newsletter, 8m, #leadership, #management, #scaling
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