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- Issue #570
Issue #570
Essential Reading For Engineering Leaders
Friday 29th November’s issue is presented by QA Wolf
QA Wolf gets engineering teams to 80% automated end-to-end test coverage, and it helps them ship 5x faster by reducing QA cycles from hours to minutes.
That’s because they provide unlimited, parallel test runs on their infrastructure that gets you pass/fail results in 3 minutes. Here’s how it works:
They build and automate tests for every single user flow & API in your app.
They spin up separate containers in cloud infra to run thousands of tests in parallel. Pass/fail results hit your GitHub repo, Slack, & CI pipeline in 3mins.
They maintain and update all tests as your product changes, and they verify all bug reports – so you never see the flakes.
— James Stanier
tl;dr: “I’ll pitch the takeaway up front, and it’s this: hold yourself accountable for making decisions and progressing discussions as quickly as possible, by whatever means necessary. Be restless while a decision hasn’t been made. Dead time is your enemy. Be creative about ways of shaving minutes, hours and days from a decision point.” James gives several examples of how to approach this.
Leadership Management
— Will Larson
tl;dr: In this 20 minute video presentation, Will discusses the under-defined and ambiguous role of Principal Engineers. He defines them as engineers who solve ambiguous, company-wide problems that would otherwise block engineering executives.
Leadership Management Video
— Nishant Shukla
tl;dr: Golden Datasets have long been a reliable method for measuring AI prompt performance. But as AI innovation moves fast, companies need a more agile, flexible, and cost-effective solution to stay ahead of their competition. Enter random sampling of AI prompt performance—a cutting-edge approach that adapts to real-world data and drives scalable performance for QA Wolf customers. Stay ahead of the curve—watch the webinar now.
Promoted by QA Wolf
Management Data
— Charlie Andrews
tl;dr: (1) Advice: imagine you’re giving advice to someone else in your position. What are the concrete next steps you’d recommend they take? (2) Commit: identify how long each day you feel comfortable taking your own advice. I usually find 30 minutes or an hour is good. Some activities also have a natural “increment” that you can use as your commitment, like “I will send one cold email to a potential customer every day.” (3) Exit ramp: give yourself an exit ramp by identifying a date when you’ll reevaluate your commitment.
CareerAdvice
“Just believe in yourself. Even if you don’t, pretend that you do and, at some point, you will.”
— Gergely Orosz
tl;dr: “This data is likely to be biased towards early tech adopters and non-enterprise users, as I posted on social media, and self-selecting software engineers active on those sites who are likely to be up-to-date on new tools, and willing to adopt them. There were more replies from developers at smaller companies like startups or smaller scaleups, and very few respondents from larger companies.”
DevTools
tl;dr: Built atop OIDC, EASIE works through Sign in with Google (and Microsoft) and includes just-in-time provisioning and automatic deprovisioning. EASIE requires Clerk's Enhanced Authentication add-on (+$100/month) but they've eliminated SSO connection fees, allowing you to add as many connections as you'd like. Click to learn more.
Promoted by Clerk
UsefulTool
— Angela Ambroz, Alec Brevé
tl;dr: “Sometimes, you just can’t randomize - it’s either not possible, or it’s unethical, or you sacrifice too much precision. In those cases, you can release your treatment to one group and create a composite, synthetic control made up of a weighted combination of your untreated groups.”
DataScience Product
— Sam Rose
tl;dr: Latency visualization shows critical timings for programmers. Operations are displayed as bars with heights proportional to their execution time.
Latency
— John Nunemaker
tl;dr: John discovered his Postgres database was using 87% disk space, mainly due to unprocessed downloads in a podcast hosting app. Rather than batch-deleting millions of old records, they used a table-swapping technique to create a new table with only recent data, freeing up significant space quickly and efficiently.
AI PostgreSQL
Most Popular From Last Issue
Engineering Principles – The 5 Step Process — Christian Scheb
Notable Links
Aisuite: Unified interface to multiple Generative AI providers.
Multi-Agent Orchestrator: Managing multiple AI agents.
Payload: Build a modern backend + admin UI.
Screenpipe: Your AI assistant that has all the context.
WeSQL: MySQL with compute-storage separation architecture.
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