#7 | Sunday reads for EMs
My favourite reads of the week to make your Sunday a little more inspiring.
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Leading your engineers towards an AI-assisted future
tl;dr: If you're getting pressure from leadership about AI adoption but don't have a plan yet you’ll want to read this. The key insight is using "Aligned Autonomy" - set clear experimentation goals with metrics, give teams autonomy on how to achieve them, then progress through phases: Experimentation → Adoption → Impact measurement. Focus first on building organisational muscle around trying tools and sharing learnings.
Moving from an orchestration-heavy to leadership-heavy management role
tl;dr: Many managers get stuck because they think their job is just executing plans handed down from above, but senior roles require you to identify problems, design solutions, and set direction yourself. The mental shift is moving from "How do I prioritize this backlog?" to "What problems should we even be solving?" If your leadership chain is still running strategy for your team, that's a red flag that signals you're not operating at the expected level.
Measuring the impact of AI on software engineering – with Laura Tacho
tl;dr: AI time savings are much smaller than the hype suggests because developers only spend 20-25% of their time actually coding, so even big coding productivity gains translate to modest overall improvements. More importantly, lines of code and acceptance rates are terrible metrics - focus on measuring developer experience first, then layer on AI tools.
People > Principles > Process > Product
tl;dr: The natural urge when joining a team is to fix the product first, but this approach backwards and creates unsustainable change. Get the people and team dynamics right first, then establish shared principles for decision-making, then fix processes that support those principles - only then tackle product improvements. It's like Formula 1: the best car is useless without the right crew, and quick product fixes without proper foundation just create the illusion of progress.
The Precise Language Of Good Management
tl;dr: Most managers use dangerously vague language that creates misaligned expectations and destroys trust. When someone asks "How am I doing?" don't wing it - say you need time to gather thoughts and come back with specifics. Replace "You're doing great" with "You showed impressive persistence through three requirement changes" and "promotion soon" with "80% likely in 9 months, here's why". Writing things down forces more measured language and prevents the performance review surprises that tank relationships.
Vibecoding a high performance system
tl;dr: AI-assisted coding can dramatically accelerate system design exploration when you have objective performance metrics to guide you - this author prototyped 8 different architectures. The key insight is that we're moving from coding-bounded to experiment-bounded development, but only if you maintain rigorous code review since AI still writes logically correct but performance-killing slop. Works best for greenfield projects where you can iterate rapidly on fundamental design decisions.
Most popular from last Sunday
What did you read recently that you would like to share?