UX has never been only about creating interfaces. It's about navigating ambiguity, advocating for humans in systems optimised for efficiency, and solving their problems through thoughtful design. Designers are shifting from makers of outputs to directors of intent.
One of the challenges teams face when working with large boards or displaying multiple fields on work item cards is limited screen space. This became even more noticeable with the rollout of the New Boards hub, which introduced additional spacing and padding for improved readability. While this enhances clarity, it can also reduce the number of cards visible at once.
The real cost of poor observability isn't just downtime; it's lost trust, wasted engineering hours, and the strain of constant firefighting. But most teams are still working across fragmented monitoring tools, juggling endless alerts, dashboards, and escalation systems that barely talk to one another, which acts like chaos disguised as control. The result is alert storms without context, slow incident response times, and engineers burned out from reacting instead of improving.
Well, our guest today argues that the best way is by moving to a more project-driven model of work, up and down the organization from the corporate level to individual teams. He wants us to both ruthlessly prioritize as well as stay fluid so that we're identifying strategic goals, assembling teams to go after them, evaluating as we go, and then either continuing, shifting, or disbanding based on our outcomes.
"I've never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are increasingly sparse and between. I have a sense that I could be 10X more powerful if I just properly string together what has become available over the last ~year and a failure to claim the boost feels decidedly like skill issue."
During my eight years working in agile product development, I have watched sprints move quickly while real understanding of user problems lagged. Backlogs fill with paraphrased feedback. Interview notes sit in shared folders collecting dust. Teams make decisions based on partial memories of what users actually said. Even when the code is clean, those habits slow delivery and make it harder to build software that genuinely helps people.
Scrum has a bad reputation in some organizations. In many cases, this is because teams did something they called Scrum, it didn't work, and Scrum took the blame. To counter this, when working with organizations, we like to define a small set of rules a team must follow if they want to say they're doing Scrum. Enforcing this policy helps prevent Scrum from being blamed for Scrum-like failures.
Clockwork is a Model Context Protocol (MCP) server that automatically tracks your work time based on git commits. It aggregates commits into worklog entries, calculates durations, and manages projects - all through a simple CLI interface. Automatic Commit Aggregation: Automatically collects commits since your last worklog entry Smart Duration Calculation: Estimates work time based on commit timestamps Project Management: Track multiple projects with associated git repositories
AI tools don't always boost productivity. A recent study from Model Evaluation and Threat Research found that when 16 software developers were asked to perform tasks using AI tools, the they took longer than when they weren't using the technology, despite their expectations AI would boost productivity. The research challenges the dominant narrative of AI driving a workplace efficiency boost.
Your AI pilot showed 94% accuracy improvements. The LLM is yielding solid results. You're getting defunded anyway. The reason? You solved a problem AI can solve. Your budget-holder needed you to solve theirs. Companies launch AI pilots that produce results, then stall at scale. The team's diagnosis: "They don't get it." What's really going on: These projects never earned budget-holder buy-in.
For decades, the to-do list has been a catalog of debt, a deceptively thin list of items to do, with icebergs of work hidden beneath the surface. AI transforms tasks to work that has already been done. Vibe Kanban, Gastown, & Conductor are the first instantiations of this for software developers. They have jargon-laden descriptions like "multi-agent orchestrator" or "visualizer," but they are, at heart, simple & beautiful Kanban boards of done & dusted work.
They may be spending a lot of combined time at the office and commuting, or just putting in a lot of hours both at work and at home. Fixing that problem can't be done abstractly, though. If you're going to address the balance of work and life activities, you have to start getting specific about where your time is going and where you really want it to go.
