30-60 Days In A New Leadership Role: Run Experiments For Change

- Lara Hogan tl;dr: "We’re intentionally limiting this process to two experiments because tons of change at once will be scary and confusing for folks. We’re also going to limit the experiment timeline to 2-3 weeks; the goal is to be able to gather data at the end of your first 60 days in your new leadership role." After crafting experiments, develop your communication plan, implement your experiments and prepare to share the results.

featured in #385

How We Found Our Ideal Customer Profile

- James Hawkins tl;dr: "Creating an Ideal Customer Profile is one of the most important things we've ever done." James shows how this is reflected in the companies revenue. It enabled the company to make important decisions - they were better placed to describe what the company does, what the site looks and feels like, pricing model, and more. James also describes how the company approached creating this profile.

featured in #385

A Framework For Prioritizing Tech Debt

- Max Countryman tl;dr: "Now with a complete list of your tech debt as it stands go through each and answer the following questions: (1) If we choose to do nothing, will this issue become worse, remain the same, or improve? (2) If it'll become worse, how quickly will it degrade? (3) If it remains the same, how much disruption is it causing today? (4) If it'll improve, at what point will it improve to the degree it's no longer an obstruction?"

featured in #384

We Invested 10% To Pay Back Tech Debt; Here's What Happened

- Alex Ewerlöf tl;dr: Alex discusses how "Tech Debt Friday" started at his org, what was learned and how it's executed: (1) We spend 10% of our time to deal with tech debt. (2) The first rule is not to create debt in the first place. (3) The PR that creates tech debt should come paired with the issue to deal with it. And more. 

featured in #383

Resilience And Waste In Software Teams

- Jessica Kerr tl;dr: Jessica explains resiliency in the context of the Southwest Airlines software failure. "When software is brittle, it falls over in production, and that falls to people to fix. While software can be robust to anticipated conditions, only people handle unexpected events. When software can’t even handle stuff that happens all the time, then people suffer the strain."

featured in #383

Meetings For An Effective Eng Organization

- Will Larson tl;dr: "I’d like to recommend 6 core meetings that I recommend every organization start with, and that I’ve found can go a surprisingly long way. These six are split across three operational meetings, two developmental meetings and finally a monthly engineering Q&A to learn what the organization is really thinking about." Will discusses each in depth. 

featured in #382

Why Your Team Should Be Using Just-in-Time Access

- Adam Buggia tl;dr: Least privilege in the cloud is hard, but progress can be made by taking a risk-based approach. Consider an attacker who obtained one of your developer’s credentials; what access would they have? By adding a temporal dimension to developer access policies, the attack surface can be significantly reduced for many security-breach scenarios. That’s where just-in-time access comes in.

featured in #382

Evaluating Managers: 5 Heuristics To Measure Managerial Impact

- AbdulFattah Popoola tl;dr: Measuring a manager’s impact is hard since outcomes take time. This post provides early evaluation metrics as well as tips for course correction. Each of the following heuristics are explained in detail: execution, people management, team development, strategic vision & organizational influence.

featured in #381

Our Cloud Spend In 2022

- Fernando Álvarez tl;dr: "Getting this massive spend down to just $3.2 million has taken a ton of work. The ops team runs a vigilant cost-inspection program, with monthly reporting and tracking, and we’ve entered into long-term agreements on Reserved Instances and committed usage, as part of a Private Pricing Agreement. This is a highly-optimized budget.""This post will cover why I went through the effort of creating a Python SQL engine and how a simple query goes from a string to actually transforming data." Toby covers tokenizing, parsing, optimizing, planning and executing.

featured in #381

What Is A Product Engineer (And Why They're Awesome)

- Ian Vanagas tl;dr: "In this post, we define the role of a product engineer, break down the characteristics of the role, go over their skills, and finally figure out why they matter. We base this information on industry research, and job posts from top startups hiring product engineers, which we quote throughout."

featured in #380