- Pointer
- Posts
- Issue #761
Issue #761
The Briefing For Engineering Leaders
Tuesday 20th October issue is presented by Larridin
AI changed how software ships. Most engineering metrics didn't keep up. Larridin built the AI-native standard for engineering performance, measuring velocity, code quality, and production reliability.
Engineering Output weighted by complexity and quality
AI Output Share and AI Slop Index
Code Durability and change failure rate
— Bjorn Roche
tl;dr: Bjorn offers the following: (1) Being more hands-on. (2) Onboarding is faster. (3) Less caution about dependencies and adopting new tech. (4) Bus factor is less of a concern.
Leadership AI
— Gergely Orosz
tl;dr: “Ramp and Stripe built platforms for non-engineers to build internal websites and tools with, and both are taking off in those workplaces. I expect more companies to do the same.”
IndustryTrends PlatformEngineering AI
tl;dr: AI changed how software ships. Most engineering metrics didn't keep up. Larridin built the AI-native standard for engineering performance, measuring velocity, code quality, and production reliability. (1) Engineering Output weighted by complexity and quality. (2) AI Output Share and AI Slop Index. (3) Code Durability and change failure rate.
Promoted by Larridin
Management Metrics AI
— Andi Roberts
tl;dr: “When someone believes they are performing well and you see evidence otherwise, you are often facing a perception gap rather than defensiveness. Start by understanding the gap, then surface your evidence with precision before inviting them to make sense of it alongside you. This reframes the conversation from “you are wrong about yourself” to “here is what I am seeing, what do you make of it?””
Management Feedback
“It is the mark of an educated mind to be able to entertain a thought without accepting it.”
— Boris Cherny
tl;dr: "I shared this note with my team earlier this week, and am posting it here as well. I hope it is interesting or helpful for others working on building product in the age of AI."
Leadership DecisionMaking AI
tl;dr: Does your team share agent workflows, approval rules, and guardrails, or is everyone improvising? Seven questions place your organization on an 8-stage AI-engineering maturity scale created by Fabien Potencier, creator of Symfony. In about three minutes you get your stage, a score on eight areas, and the one change that moves you forward fastest. Find out where your team really stands.
Promoted by Upsun
Management Metrics AI
— Will Larson
tl;dr: “As we’ve walked this path, we–like everyone else progressing down it–have run into the problem of pull request review. The p50 pull request review took about 33 minutes to complete 2 years ago, but now takes us about 77 minutes. The slope here correlates tightly with the number of pull requests getting merged. Tightly enough that addressing it became one of my priorities for the week... I think our current approach is an interesting one, which we call the small-change.”
CaseStudy CodeReview
— Alex Fedoseev
tl;dr: “Nothing has influenced the way I design software more than algebraic data types. It sounds overly academic—the kind of term that makes people roll their eyes or scares them away altogether. But honestly, it only sounds scary. The idea itself is quite simple, and learning it showed me a fundamentally better way to build software.”
DeepDive CodeQuality Architecture
— Lambros Petrou, David Laban
tl;dr: “The question becomes: how do you scale the control plane for millions of databases without making every query slower by sending it through centralized bottlenecks?”
Scale Database
Most Popular From Last Issue
The Brain Sandwich - Matheus Lima
Notable Links
AI Job Search: Job application framework built on Claude.
Filee: Free OS file converter.
Harness2: Framework for recursive agent harnessing.
Jasna: Video restoration tool.
Orca: The place for working with a fleet of agents.
How did you like this issue of Pointer?1 = Didn't enjoy it all // 5 = Really enjoyed it |