What If Everybody Did Everything Right?
- Lorin Hochstein tl;dr: In the wake of an incident, we are inevitably led to answer two questions: “What did we do wrong here? What didn’t we do that we should have?” Lorin argues these questions create a specific lens to scrutinize the incident. “An alternative lens for making sense of an incident is to ask the question “how did this incident happen, assuming that everybody did everything right?” Assume that everybody whose actions contributed to the incident made the best possible decision based on the information they had, and the constraints and incentives that were imposed upon them.” This incites different questions: (1) What information did people know in the moment? (2) What were the constraints that people were operating under?featured in #492
featured in #491
A Guide To Organization Modeling In Authentication
tl;dr: Organization modeling is a crucial part of building authentication and authorization into applications. However, once SSO and various user-organization relationships are thrown into the mix, the logic can become complex to manage. For developers building this in-house, there are important nuances and implementation details to consider.featured in #491
featured in #490
featured in #490
Add More Rigor To Your Reference Calls With These 25 Questions
tl;dr: 25 questions including: (1) How does this person compare to the best you’ve ever seen in the role? (2) On a scale of 1 - 100, how would you rank this person? (3) On a scale of 1-10, how do you rate XYZ on specific trait or ability? (4) Can you tell me about a project that would have failed without the candidate? (5) What haven’t I asked that, if you were me, you would want to know about this person?featured in #489
How To Measure The Impact Of Generative AI Code
- Ben Lloyd Pearson tl;dr: What’s the ROI of your GenAI code? By the end of 2024, GenAI is projected to generate 20% of all code – or 1 in every 5 lines. Learn how to use PR labels to get telemetry on GenAI code, allowing metric tracking that compares AI-generated code against unlabeled PRs. With this free automation, you can track the ROI of your GenAI investments and identify potential security and compliance risks.featured in #489
How To Hire Low Experience, High Potential People
- Tara Seshan tl;dr: “After 1000+ hours of interviewing candidates, making many mistakes in hiring and firing, and closely imitating the best possible behaviors of my “hiring savant” managers, this is what I’ve learned about separating the wheat from the chaff in order to find amazing yet unconventional people.” Tara provides a guide for finding such folks.featured in #488
A Guide For Notification Systems
- Sam Seely tl;dr: A complete guide for what to consider if you're evaluating whether to build your own notification system or use a third-party vendor.featured in #488
Accelerating Code Reviews With Nudges
- Abi Noda tl;dr: In 2020, the code review team at Meta discovered that 85% of developers were satisfied with the code review process in general. They were less satisfied with the speed with which their code was reviewed. This inspired a core hypothesis that the NudgeBot could decrease code review time in 3 ways: (1) The time a diff waits in the ‘needs review’ status. (2) The number of diffs that take over 3 days to close, this timeframe was chosen because they were only nudging diffs after 24 hours. (3) The time to first action.featured in #488