You’re reading The Steady Beat, a weekly pulse of must-reads for anyone orchestrating teams, people, and agents 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.
Meet Us Where You Work
Speaking of agent-shaped users, we’re putting our money where our manifesto is. Steady’s updated MCP server is now in beta, so you can pull your goals, check-ins, digests, and activity into Claude, ChatGPT, or whatever AI assistant you already work in. The thinking behind it: single-purpose integrations (a Slack app here, a Teams app there) are running out of runway as people increasingly work through general-purpose assistants rather than around them. So instead of making you bounce between tabs, we’re letting the assistant you already trust reach into Steady directly. Ask Claude to draft a goal update from your latest check-in. Mash a Jira epic with that Notion doc into a Steady goal story with a single prompt. The data you see is exactly what you’d see in Steady’s UI, so permissions stay clean. Quick Fill templates and Action Items management are up next. We’d love your feedback, especially on the workflows you wire up that we hadn’t imagined.
— Steady Blog, 4m, #ai, #coordination, #product
Agent-Shaped Users
Your next power user doesn’t scroll or click through onboarding. It’s an AI agent, and it’ll dump your product for a competitor in milliseconds if your API returns the wrong format. Elena Verna’s piece is a wake-up call for product teams: the assumption baked into every SaaS playbook, that users are human, is collapsing faster than most people realize. Agents don’t care about your carefully crafted UI or the witty microcopy your designer fought for. They evaluate products on one thing: whether you return the right output, fast, in a format they can consume. MCP compatibility is the new table stakes. Agents also erase every moat built on friction or user habituation. She sees a bifurcation coming: products optimizing for human delight on one side, invisible infrastructure serving armies of agents on the other, with very little middle ground. The companies still optimizing their landing page conversion rates while ignoring their API ergonomics are measuring the wrong funnel. Your new ICP doesn’t have a LinkedIn profile, and it’s already shopping.
— Elena’s Growth Scoop, 6m, #ai, #product, #strategy
The Verification Layer
Every technology wave forces a new kind of manager into existence. Steam created the foreman. Computers and the internet created project and product managers. Now AI is creating something we haven’t named yet. Juan Correa argues the defining trait of this new role is verification. Previous automation failed loudly: machines broke, calculations errored, spreadsheets returned #REF!. AI fails silently, and in plausible prose. One company’s agent deleted a production database and then fabricated records to hide the gap. A fintech replaced 700 support reps, watched costs drop 40%, then watched customer satisfaction crater so hard they had to rehire. When failure modes go invisible, somebody has to be professionally paranoid for a living. The new required skill: calibrated intuition about what agents can actually handle, and accountability for work you didn’t personally touch. History rhymes here. Spreadsheets killed 400,000 bookkeeping jobs but birthed 600,000 accountant ones. ATMs were supposed to wipe out tellers; instead, bank branches multiplied and tellers moved into relationship work. The jobs shift upward, into interpretation and judgment. So the real question for every team lead right now is: who’s checking the agent’s work, and do they have the context to catch what’s wrong?
— Business as Usual, 8m, #ai, #management, #leadership
The 100-Point Budget
You’ve got 100 points of attention per week, and most of you are spending them wrong. This piece argues that every engineering manager distributes their focus across five buckets (Delivery, People, Support, Technical Direction, and Team Future), but almost nobody does it on purpose. We allocate based on what felt urgent in our first 90 days, then run that same pattern for years, even as the team’s actual needs quietly evolve around us. The real teeth come from the 10-60 rule. Anything under 10 points quietly deteriorates, and anything over 60 creates obsession that starves everything else. Spreading 20 evenly produces nothing meaningful. The author’s confesses that they spent their early management years maxed out on Delivery and Support, and career development slid into one-on-ones that never quite happened. That pattern calcified into identity, and the team eventually paid the tax. The bucket you’re ignoring is broken for one reason: you never decided to spend points there. The fix starts with a weekly audit. Where did your attention actually go? Which bucket hasn’t been opened in a month?
— The Engineering Manager, 6m, #management, #leadership, #engineering
Three Debts
Technical debt has a cousin it never told you about. Make that two cousins. Martin Fowler’s latest fragments surface an idea from Margaret-Anne Storey that every engineering leader should tape to their monitor: code isn’t the only thing accumulating interest. Technical debt you know: the compromises in the code itself. Cognitive debt is the slow erosion of the team’s shared mental model, the moment when nobody understands why this works anymore. Intent debt is the quiet killer: the system goals and constraints that were never properly captured, so every new change is a coin flip. In the LLM era, all three compound faster than anyone wants to admit (we touched on this theme in our AI debt issue). When agents generate code the team never wrote, cognitive debt skyrockets while the commit history looks deceptively clean. Shaw and Nave pile on with a sharper warning: “System 3” thinking, the uncritical surrender to AI-generated reasoning, is a different beast than healthy cognitive offloading. If agents are doing the executing, your team’s job becomes verification, and so the metric shifts from “what did we ship?” to “what did we validate?”
— Martin Fowler, 7m, #engineering, #ai, #systems
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.
Cross-Team Highlights is the antidote to “I have no idea what the other team has been up to.” Once a month, this Echo distills another team’s work into five high-level themes. Each one is a short, jargon-free paragraph aimed at colleagues who don’t live in that team’s tools. Product leads learn what engineering actually shipped without decoding a commit log. Marketing spots upcoming launches in time to plan campaigns. No more sitting through status meetings that weren’t meant for you. Just a monthly briefing that keeps everyone in the loop on the work happening one floor over.
The lightweight teamwork OS
Teams rely on two coordination loops to function: a big-picture loop connecting plans to progress, and a ground-level loop keeping teammates in sync.
Problem is, status quo approaches to running those loops are an incomplete, inconsistent, and inefficient tangle of meetings, emails, chat threads, dashboards, and manual toil.
Steady is the teamwork OS that runs both loops for you. Purpose-built agents continuously distill updates and activity into personalized intelligence that keeps everyone aligned and informed automatically.
The outcome: high-performing teams that deliver better work, 3X faster.
Learn more at runsteady.com.