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.
Red Flag Inventory
Workplace dysfunction doesn’t announce itself with a dramatic explosion – it accumulates quietly through patterns that seem individually manageable until you wake up one day and realize you’ve been slowly boiling for months. This piece maps six warning signs that signal it’s time to leave before burnout makes the decision for you. Constant reorganizations reveal leadership chasing problems instead of executing strategy, burning institutional knowledge while technical debt piles up. Fear-based management where failure gets punished rather than examined creates cultures where bad news travels slowly until small problems detonate catastrophically. Blame rolls downhill while credit flows upward, breeding the kind of defensive behavior that turns collaboration into self-preservation. Chronic firefighting becomes the norm because upstream dysfunction never gets fixed, burning out your best people first since conscientious engineers can’t help but attempt heroic rescues. Too many managers means conflicting priorities and unclear authority, forcing people to navigate organizational politics instead of shipping work. And watch the tenure distribution: either everyone stays forever because they can’t leave, or everyone flees quickly for obvious reasons. If you’re checking multiple boxes on this list, trust your gut. The best time to leave a toxic company is before it convinces you that dysfunction is normal.
— Blog 4 EMs, 6m, #leadership, #management, #culture
Plausible Isn’t True
AI can confidently explain why your code broke, suggest an architecture fix, and even generate the implementation – all while being completely wrong. Addy Osmani makes the case that as AI gets better at sounding authoritative, human critical thinking becomes more valuable, not less. The trap is treating LLM outputs like verified answers instead of plausible hypotheses that demand verification. A confident-sounding explanation isn’t the same as a correct one, and the gap between those two is where projects derail. Osmani’s framework is deceptively simple: anchor your thinking in the classic questions that force rigor. Who are the stakeholders affected by this decision? What problem are we actually solving versus the one we’re rushing to fix? Where does this solution need to work—sandbox or production? When are we making decisions under stress that bypass deliberate thought? Why is this happening, and have we drilled past symptoms to root causes? How do we validate evidence instead of accepting convenient explanations? The pressure to move fast makes confirmation bias lethal – we grab the first answer that fits our mental model and ship it. But diverse perspectives, evidence-based reasoning, and willingness to challenge assumptions separate teams that ship confidently from those that ship bugs wrapped in plausible explanations. AI amplifies your judgment; it doesn’t replace it.
— Addy Osmani, 8m, #ai, #engineering, #leadership
Beginner Again
Mid-career product managers face an uncomfortable truth: the expertise that got you here won’t keep you relevant unless you’re willing to become a beginner again. Jeff Gothelf uses the cautionary tale of “Steve,” a graphic designer who watched his career evaporate because he refused to learn digital tools, betting instead that his traditional skills would remain valuable. Sound familiar? AI is product management’s Photoshop moment, and the PMs coasting on pattern recognition and frameworks built for the pre-LLM world are writing their own retirement letters. The path forward isn’t complicated, just humbling. Read what’s actually happening in the industry instead of relying on what you already know. Enroll in courses that force you to engage with AI capabilities hands-on. Experiment with tools like ChatGPT, Claude, and emerging design platforms until you understand their edges, not just their demos. The advantage mid-career professionals have over fresh grads isn’t necessarily deeper expertise anymore – it’s context about how organizations actually work. Large enterprises adopt technology slowly, which creates a window to lead by example rather than get swept aside. Model the learning behavior your teams need to see. The choice isn’t between staying an expert or becoming obsolete; it’s between defending what you knew yesterday or building fluency in what matters tomorrow.
— Jeff Gothelf, 5m, #ai, #leadership, #transformation
Own the Line
If you can’t put your work on a graph, you might not be solving a problem that matters. This piece makes a simple case: senior professionals distinguish themselves by owning a metric visualized over time, turning abstract claims about impact into undeniable evidence. The brilliance isn’t the graph itself, it’s what the graph forces you to do. Saying “I reduced page load time by 15%” invites skepticism and followup questions. Showing a declining curve with scale, history, and volatility answers every question before it gets asked. Graphs create accountability because they expose whether you’re actually moving the needle or just appearing busy. They provide instant feedback on problem selection – if the line isn’t changing despite your effort, you’re either solving the wrong problem or using the wrong approach. The anti-pattern? Owning too many graphs, collecting gobs of dashboards you show opportunistically instead of focusing relentlessly on the few metrics that genuinely matter. Engineers might track incidents, page performance, or bug escape rates. PMs and designers could own retention curves, support ticket trends, or revenue attach rates. You don’t need to move the metric solo; monitoring tenaciously and following up consistently is enough to demonstrate senior-level performance. Stop explaining your impact in paragraphs. Let the curve do the talking.
— Stay SaaSy, 6m, #strategy, #leadership, #productivity
Echo of the Week
Echoes are AI agents in Steady that automatically gather and deliver work context to teams on a schedule—answering recurring questions about progress, capacity, and coordination so you stop burning hours assembling the same information manually.
Weekly team kick-off automatically generates a pre-meeting brief every Monday at 10:00 AM containing last week’s work organized into themes, current team goals, upcoming absences, and even an ice-breaker question. It enables teams to skip status updates during meetings and spend time on strategic discussion instead, making kick-offs more efficient and collaborative.
Stop Drowning in “Work About Work”
Your team loses 21 hours per person, per week slogging through status meetings and hunting for context across chats, docs, and dashboards.
Steady’s AI agents eliminate this coordination tax by continuously delivering personalized guidance on what’s happening, what’s next, and what needs attention across the whole team.
Join the thousands of teams staying in sync, avoiding burnout, and moving 3X faster with Steady.
Learn more at runsteady.com.
