No management needed

No management needed: Anti-patterns in early-stage engineering teams
9 minutes by Antoine Boulanger

Antoine explains why most engineering “management problems” in early-stage startups are self-inflicted. He says that founders should avoid motivating engineers, hiring managers too early, or copying big-company practices. Instead, he suggests that success comes from hiring motivated people, staying focused on product and users, and using minimal, simple management only when team size truly requires it.

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Beyond senior: Consider the staff path
14 minutes by Joel Hawksley

The staff role involves broader scope than senior engineers, working across multiple teams or diving deep into complex problems. Staff engineers fit into four archetypes: Tech Lead, Architect, Solver, or Right Hand to executives. Success requires aligning with business needs, keeping public records of work, predicting future trends, and turning ambiguous problems into clear tasks others can handle.

Work expands. Time vanishes. Here's why.
4 minutes by Michał Poczwardowski

Michał shares his thoughts on two famous laws explaining why work takes longer than expected. Parkinson's Law says work expands to fill available time. Hofstadter's Law states tasks always take longer than estimated, even when accounting for this tendency. Michał suggests using timeboxing, clear completion criteria, and public commitments to combat these effects while building trust in yourself and teams.

Outcomes > learning opportunities
34 minutes by Shreyas Doshi

In high-stakes situations, leaders should prioritize company outcomes over individual learning. Company success is the strongest driver of career progress, since it is visible, verifiable, and creates the most learning through growth. The real challenge for leaders is not making tough decisions, but communicating them clearly and empathetically without sacrificing results.

Many are in the dark about dark launching
6 minutes by Dave Mangot

Dave found out that most companies understand feature flags but very few grasp dark launching. Dark launching involves running new systems in parallel with existing ones, processing real data but discarding the results until the new system is thoroughly tested and validated.

And the most popular article from the last issue was:

• Three ways to solve problems