Leadership in Tech
Leadership in Tech
#328 – July 12, 2026
ten practical laws for managing projects successfully
Laws of project management
11 minutes by Lucas F. Costa
Lucas presents ten practical laws for managing projects successfully. He explains that projects succeed by solving real problems, adapting to new information, and delivering working solutions early. The laws emphasize flexible planning, clear priorities, teamwork, operational readiness, and testing important assumptions first. Together, they provide simple guidance for building products that meet user needs while balancing business goals, time, scope, and quality.
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Notes on the software factory
6 minutes by Benedict Brady
AI coding agents work best when given real tools like browser access, deployment pipelines, and test runners. Adding a critic agent to review work improves quality, and pairing that with more thinking time on hard problems helps further. Memory and long-running workflows are still weak points. The whole stack, from cloud infrastructure to IDEs, needs to be rebuilt around agents rather than adapted from human-centered tools.
How do I create accountability without authority?
22 minutes by Andi Roberts
Cross-functional leaders often assume that once a commitment is made in a meeting, it will hold. It rarely does without deliberate structure to support it. Accountability in a matrix organisation must be built through precise agreements, visible records, and early conversations about competing priorities. The goal is habits the whole group owns, not just the leader, so accountability survives long after any single person moves on.
The Mario meeting
5 minutes by Michael Lopp
Companies plan compensation budgets more than a year in advance, long before anyone sees their review. At any given time, two budgets run at once: one being spent now, one being built for next year. Senior leaders must understand this full process, not just the end result. Most employees only see the final number, but the real decisions happen much earlier, in rooms most people never enter.
Raise the ambition threshold
4 minutes by Jack Vanlightly
Building software faster with AI doesn't mean building more software. Every new system adds ongoing costs to operate, secure, and maintain, and too many obligations can crowd out the capacity to build what truly matters. AI should raise the bar for what teams attempt, not lower the bar for what gets built. Companies that use AI only to clear backlogs risk being overtaken by bolder competitors tackling harder, more valuable problems.
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