tl;dr in tech by Joe Karlsson - Issue #12
tl;dr: Knowing how your org works can be:
1) Knowing what technical skill you need to invest effort into that will actually be rewarded.
3) How to effectively pitch projects or improvements and see these through to completion.
4) How to navigate ambiguity and more.
tl;dr: As Daniel transitioned into a new role of managing managers, he sought wisdom from several, experienced executives, asking them 4 questions:
1) What worked for you and helped you succeed?
2) Have you experienced failure? What would you have done differently?
3) Were there any resources you found helpful as you grew into the role.
4) What piece of advice would you give your past self before entering the role?
tl;dr: “The types of problems organizations have are heavily influenced by their incentive structure.” Marianne describes the types of problems you’ll find in various org structures i.e. in engineering led orgs, orgs where engineering reports to product, or security, or in flat orgs. She concludes “the best organizations at managing technical debt tend to be the ones that have a thoughtful process in place to adjudicate competing incentives.”
tl;dr: Independent, cross-functional meetings at Squarespace e.g. Infrastructure Council, Backend Council and Data Council create a “sense of togetherness across an ever-growing engineering organization.” Dan started the Engineering Manager Forum and shares his blueprint for how it’s run.
tl;dr: Three pieces of information should be conveyed by an error message:
1) Context: What led to the error? What was the code trying to do when it failed?
2) The error itself: What exactly failed?
3) Mitigation: What needs to be done in order to overcome the error?
3) Flaky tests erode trust and breed learned helplessness.
tl;dr: “The median data to engineers ratio for the US companies I looked at is 1:7 compared to 1:4 for European companies. And the design to engineers ratio is 1:9 for both groups. This post gives some answers to why this is but also leaves some questions unanswered.”
tl;dr: Earth’s rotation, relative to the fixed stars, has sped up and is predicted to continue to do so. Although there are no immediate implications, if it continues over a sustained period of time, we might find ourselves having to consider a negative leap second, as explained here.
tl;dr: A mental model for how a neural network works by building one from scratch. “The hardest part is acquiring the conceptual understanding of a system to come up with an equation for its performance.”