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- Issue #613
Issue #613
Essential Reading For Engineering Leaders
Tuesday 6th May’s issue is presented by Warp
Every hour lost to slow engineering workflows is an hour your business leaves revenue on the table.
56% of Fortune 500 engineering teams rely on Warp’s Agent Development Environment (ADE) to eliminate outdated workflows, accelerate delivery, and fuel growth.
— Mai-Lan Tomsen Bukovec
tl;dr: AWS VP shares a framework for Principal Engineer roles developed at Amazon. The framework defines six key roles: Sponsor (project lead), Guide (technical expert), Catalyst (idea launcher), Tie Breaker (decision maker), Catcher (project rescuer), and Participant (contributor). This helps organizations optimize senior engineers' impact and develop talent effectively.
Leadership Management
— Sean Goedecke
tl;dr: “I have delivered a lot of successful engineering projects. When I start on a project, I’m now very (perhaps unreasonably) confident that I will ship it successfully. Even so, in every single one of these projects there is a period - perhaps a day, or even a week - where it feels like everything has gone wrong and the project will be a disaster. I call this the valley of engineering despair. A huge part of becoming good at running projects is anticipating and enduring this period.” Sean discusses how he tackles this phase.”
Leadership Management
— Zach Lloyd
tl;dr: The biggest unlock from AI isn’t just speed — it’s parallelism. Great developers are starting to multithread themselves, spinning up agents to handle multiple tasks at once. But today’s tools aren’t built for this kind of parallel work. We need systems that give developers visibility, control, and oversight across all those moving parts — or we risk the chaos outpacing the gains.
Promoted by Warp
Management AI
— Ben Kuhn
tl;dr: “The problem is that the bad consequences of underconfidence and under-ambition are severe but subtle, whereas the bad consequences of overconfidence and wishful thinking are milder but more obvious. If you’re overconfident, you’ll try things that fail, and people will laugh at you. If you’re underconfident, you’ll avoid making risky bets, and miss out on the potential upside, but nobody will know for sure what you missed. That means it’s always tempting to do what the low-info heuristic tells you and be less ambitious—but ultimately, that ends up being worse for the world.”
CareerAdvice
“Never forget that only dead fish swim with the stream.”
— Marcus Noble
tl;dr: “I want everyone to have that same confidence and I want to hear all of you giving talks too! You have stories to tell, lessons to share and experience to pass on. So here is my learnings on how I approach giving a talk in front of a crowd of techies, mainly focussed on technical talks but most of this should apply to most public speaking.”
CareerAdvice
tl;dr: Learn from this preview on how Clerk's Organization feature allows you to easily set up and manage a multi-tenant application for your team.
Promoted by Clerk
Guide
— Yulei Liu
tl;dr: “Traditionally, evaluating search relevance relied on human annotations, which posed challenges in scale, latency, consistency, and cost. To solve this, we built AutoEval, a human-in-the-loop system for automated search quality evaluation that is powered by large language models (LLMs). Through leveraging LLMs and our whole-page relevance (WPR) metric, AutoEval enables scalable, accurate, and near-real-time search result assessments.”
Architecture LLM
— Doug Turnbull
tl;dr: “These vectors correspond to vector embeddings, a representation of a word, sentence, image, or, really anything. Embeddings come out of models that move similar items closer. Our model might know that "Mary had a little lamb" is very similar to "Little bo peep had a sheep" - yielding nearly identical embeddings - despite sharing no important words.”
Database
— Bram Jetten
tl;dr: “In early 2022, when we counted our ARR at PlanGo, my co-founder and I shared a moment that we couldn't believe. We just crossed the magical €1M ARR milestone, something that felt unreal for a company built on one Rails codebase and one developer (me).”
Rails
Most Popular From Last Issue
Systems Ideas That Sound Good But Almost Never Work — Steven Sinofsky
Notable Links
Anemll: Artificial neural engine ML library.
Friday Deploys: Apparel and accessories for work and leisure.
Kubetail: Real-time logging dashboard for Kubernetes.
Sparks: Typeface for creating sparklines in text.
System Prompts: Collection of leaked system prompts.
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