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- Issue #718
Issue #718
Essential Reading For Engineering Leaders
Friday 22nd May’s issue is presented by Gauntlet
Join Byron Mackay as he breaks down why system design is becoming one of the most important skills for software engineers in an AI-first job market.
In this session, you’ll learn how to:
Understand why system design is becoming a critical skill for software engineers in an AI-first market
Think more deeply about the technical decisions that impact security, performance, and long-term maintainability
Recognize key system design topics to study, including databases, data flow, authorization, and schema design
Learn more about Night School including access to past sessions: https://gauntletai.com/night-school
— Mike Fisher
tl;dr: “The retention curve that goes down is actually a more powerful narrative tool than the one that goes up, because it creates urgency, names an enemy, and invites the team into the fight. Honest reckoning builds more trust than optimistic reporting.” Mike shares The Story Frame - a framework for how leaders should present metrics to their team.
Leadership Management Communication
— Justin Reock
tl;dr: A panel of senior engineering and research leaders who debated the following: (1) Will AI mean fewer engineers? (2) Is AI accelerating technical debt? (3) Will most code be AI-generated within five years? (4) Is the future of engineering about managing agents? (5) Do leaders need to mandate AI adoption? (6) Is code review now the bottleneck? Is risk the only thing holding back adoption? (7) Are AI adoption problems really culture problems?
Management AI DevEx
tl;dr: Join Byron Mackay as he breaks down why system design is becoming one of the most important skills for software engineers in an AI-first job market. In this session, you’ll learn how to: (1) Understand why system design is becoming a critical skill for software engineers in an AI-first market. (2) Think more deeply about the technical decisions that impact security, performance, and long-term maintainability. (3) Recognize key system design topics to study, including databases, data flow, authorization, and schema design.
Promoted by Gauntlet
AI Event
— Michael Lopp
tl;dr: Michael describes the moment his chief of staff told him he was the problem - barely treading water as a senior leader. The fix: admit you're failing, ruthlessly prioritize with a trusted other, delegate even when you think people aren't ready, and say no to everything else.
Leadership Management
“Every job looks easy when you’re not the one doing it.”
— Richard Marmorstein
tl;dr: Richard argues we're not in software's "centaur era" yet - the point where human-AI teams outperform either alone. AI coding agents still can't reliably make independent progress on long projects, which is why software engineers are valuable. Even when they can, human jobs don't disappear until AI teams working alone beat human-AI teams, which took decades in chess.
CareerGrowth AI
— Santosh Kumar Radha
tl;dr: If your team has chained Claude Code to write, then to review, you already know the pattern. Harness orchestration is the architectural discipline behind it, a first look at how Claude Code, Codex, and Gemini compose as primitives. Read the breakdown — written for engineering leaders evaluating the agent layer.
Promoted by AgentField.ai
Architecture AI
— Birgitta Böckeler
tl;dr: “Internal quality problems affect AI agents in similar ways that they affect human developers. An agent working in a tangled codebase might look in the wrong place for an existing implementation, create inconsistencies because it has not noticed a duplicate, or be forced to load more context than a task should require. In this article, I describe my experimentation with various sensors that help us and AI reflect on the maintainability of a codebase, and what I learned from that.”
CodeReview AI
— Cheng Huang
tl;dr: “This post shares my most valuable learnings on: ensuring correctness with code contracts, applying lightweight spec-driven development, and pursuing aggressive performance optimization - plus my wish list for the future of AI-assisted coding.”
Rust CaseStudy AI
— Alex Kladov
tl;dr: Alex walks through his advanced git blame workflows in service of understanding code history and the "why" behind code changes. He describes this as a 4D approach to reading code.
DeepDive Git
Null Pointer
Productivity Gains
Most Popular From Last Issue
How I Use LLMs As A Staff Engineer In 2026 - Sean Goedecke
Notable Links
OpenSpec: Lightweight framework for spec-driven development.
Portless: Replace port numbers with named local URLs.
Semble: Code search for agents.
TokenSpeed: LLM inference engine for agentic workloads.
Zerolang: Programming language for agents.
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