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- Issue #660
Issue #660
Essential Reading For Engineering Leaders
Tuesday 21st October issue is presented by Unblocked
Your engineers are already vibe coding.
Unblocked turns your scattered team knowledge into the context Cursor and Claude need to generate ship-ready code.
— Lizzie Matusov
tl;dr: “Code reviews are foundational to modern software development - but how do experienced developers actually read, understand, and evaluate changes? What mental models do they use, and how can we better support those strategies across teams and tools? This week we ask: How do experienced engineers comprehend code during review, and what can leaders do to support more effective, scalable review practices?”
Leadership Management
— Jean Hsu
tl;dr: “If you’re leading a team, the most effective way to get output is not to mandate effort or hours. It’s to help people find work that feels easy for them - not necessarily work they already know how to do, but work that feels obvious for them to get done by whatever means possible.”
Leadership Management
— Dennis Pilarinos
tl;dr: AI coding agents can’t solve real engineering problems with prompts alone - it needs institutional knowledge. Context engineering puts together the right mix of your code, docs, tickets, and conversations so AI generates code that works in your system.
Promoted by Unblocked
Tools AI
— Anil Dash
tl;dr: “Technologies like LLMs have utility, but the absurd way they've been over-hyped, the fact they're being forced on everyone, and the insistence on ignoring the many valid critiques about them make it very difficult to focus on legitimate uses where they might add value.”
AI ThoughtPiece
“Good design adds value faster than it adds cost.”
— Denis Stetskov
tl;dr: “We're living through the greatest software quality crisis in computing history. A Calculator leaks 32GB of RAM. AI assistants delete production databases. Companies spend $364 billion to avoid fixing fundamental problems.”
ThoughtPiece
— Antonija Bilic
AI is transforming software engineering, but enterprise software will not be vibe coded. Kent Beck, Bryan Finster, Rahib Amin, and Punit Lad explain why the future belongs to disciplined, context-aware development, where specs, multiplayer workflows, and organizational trust turn AI from an experiment into a force multiplier.
Promoted by Aviator Runbooks
AI BestPractices
— Arham Jain
tl;dr: “Is your code a tangled mess of business logic and side effects? Mixing database calls, network requests, and other external interactions directly with your core logic can lead to code that’s difficult to test, reuse, and understand. Instead, consider writing a functional core that’s called from an imperative shell.”
Tests
— Joy Arulraj
tl;dr: “This paper proposes a preliminary taxonomy of system design principles distilled from several domains in computer systems. The goal is a shared, concise vocabulary that helps students, researchers, and practitioners reason about structure and trade-offs, compare designs across domains, and communicate choices more clearly.”
SystemDesign
— Jordan Cutler
tl;dr: “In this article, I’ll share every item in my setup with you in case it interests you, especially with shopping season coming up. With each item I share, I’ll tell you a little bit about it.”
Productivity
Most Popular From Last Issue
How To Use AI To Help With Software Engineering Tasks - Gregor Ojstersek, Steven Levey
Notable Links
Claude-Cookbooks: Notebooks & recipes showcasing ways of using Claude.
Dayflow: Generate a timeline of your day, automatically.
Duck-UI: Web-based interface for interacting with DuckDB.
PaddleOCR: Turn any PDF or image doc into structured data.
Steel: OS browser API for AI agents & apps.
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