Books for people who are or aspire to manage/lead team(s) of software engineers
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Updated
Jan 27, 2024
Books for people who are or aspire to manage/lead team(s) of software engineers
A list of resources about Software Engineering Management
A curated list of tools, templates, books, newsletters, podcasts, and resources for engineering managers and tech leaders.
Learning resources for engineering managers.
Awesome resources about engineering leadership for those who are (or soon to be) leading software enginners
A complete system for writing LinkedIn posts that sound human, not AI. Built for Claude Projects. Includes anti-AI detection, voice calibration, 2026 algorithm strategy, and weekly workflow.
Decision memos, incident playbooks, SLO templates, and architecture reviews for engineering leaders.
A collection of resources to help guide engineers transition into management & help current Engineering Leaders succeed
Solution Architect & Engineering Leader | Building scalable systems, mentoring teams, and designing products that last.
A repository with resources on the challenges you might encounter as an engineering manager.
A practical, copy‑pastable OS for EMs/Tech Leads. Clear principles, team ops, delivery, platform, metrics, culture, crisis, scaling, and reusable templates for remote‑first SaaS.
A place to keep my reflections on software engineering leadership
Matt Blackford's technical blog on cloud infrastructure, DevOps and engineering leadership
Vicente Opaso's personal website, revamped!
A collection of resources for engineering managers in the tech industry.
Repo hosting the raw BMD manifesto. Subject to change without notice
Professional portfolio and technical manifesto of Joshua Karr. Focused on Distributed Systems, AWS Cloud Architecture, and Backend Engineering Excellence.
SHAM (System Health & Architecture Monitor) is a framework for observing how software systems change over time by tracking risk introduced, system stability, recovery behavior, and surrounding context. It helps make structural health and invisible work visible as systems evolve under real-world constraints.
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