/Management

Innovations In Evaluating AI Agent Performance

- Michael Lopp tl;dr: Just like athletes need more than one drill to win a competition, AI agents require consistent training based on real-world performance metrics to excel in their role. At QA Wolf, we’ve developed weighted “gym scenarios” to simulate real-world challenges and track their progress over time. How does our AI use these metrics to improve our accuracy continuously? 

featured in #614

What You Give Airtime To Will Expand

- Wes Kao tl;dr: “First, the thing you give airtime to tends to grow in importance in people’s minds. This is why you should avoid incepting negative ideas. Ideas are fuzzy until you put them into words, either spoken or written. The longer you give it airtime, and the more you repeat it, the more real and concrete it becomes.”

featured in #614

Hold What You’ve Got

- Mike Fisher tl;dr: “As you get close to launching something, closing a deal, wrapping up a quarter, etc. there is often a lot of noise in the signals. It's very tempting to follow that noise but more than likely that will lead you in circles.”

featured in #614

Principal Engineer Roles Framework

- Mai-Lan Tomsen Bukovec tl;dr: AWS VP shares a framework for Principal Engineer roles developed at Amazon. The framework defines six key roles: Sponsor (project lead), Guide (technical expert), Catalyst (idea launcher), Tie Breaker (decision maker), Catcher (project rescuer), and Participant (contributor). This helps organizations optimize senior engineers' impact and develop talent effectively.

featured in #614

Principal Engineer Roles Framework

- Mai-Lan Tomsen Bukovec tl;dr: AWS VP shares a framework for Principal Engineer roles developed at Amazon. The framework defines six key roles: Sponsor (project lead), Guide (technical expert), Catalyst (idea launcher), Tie Breaker (decision maker), Catcher (project rescuer), and Participant (contributor). This helps organizations optimize senior engineers' impact and develop talent effectively.

featured in #613

The Valley Of Engineering Despair

- Sean Goedecke tl;dr: “I have delivered a lot of successful engineering projects. When I start on a project, I’m now very (perhaps unreasonably) confident that I will ship it successfully. Even so, in every single one of these projects there is a period - perhaps a day, or even a week - where it feels like everything has gone wrong and the project will be a disaster. I call this the valley of engineering despair. A huge part of becoming good at running projects is anticipating and enduring this period.” Sean discusses how he tackles this phase. 

featured in #613

5 Misconceptions About AI Agents

- Zach Lloyd tl;dr: The biggest unlock from AI isn’t just speed — it’s parallelism. Great developers are starting to multithread themselves, spinning up agents to handle multiple tasks at once. But today’s tools aren’t built for this kind of parallel work. We need systems that give developers visibility, control, and oversight across all those moving parts — or we risk the chaos outpacing the gains.

featured in #613

A Weekly Mind Meld

- James Stanier tl;dr: “Since starting my new CTO role, I've been sharing a weekly update with my team. It's how I continually open up my thoughts to the team with a long-term goal to reduce any mental alignment gap between us. I like to think that the more I share, the more they can understand what I believe is important and why, and the more that my style of working and thinking can propagate through the team.” James shares how he executes this mind meld. 

featured in #612

Innovations In Evaluating AI Agent Performance

- Michael Lopp tl;dr: Just like athletes need more than one drill to win a competition, AI agents require consistent training based on real-world performance metrics to excel in their role. At QA Wolf, we’ve developed weighted “gym scenarios” to simulate real-world challenges and track their progress over time. How does our AI use these metrics to improve our accuracy continuously? 

featured in #612

Mastering The Human Side Of Engineering: Lessons From Apple, Palantir And Slack

tl;dr: “Lopp begins by offering tactical advice on creating durable, effective engineering orgs and discusses the pivotal relationship between product and engineering. He then charges leaders to ask themselves if they possess some of the people-centered skills he’s seen of successful leaders over his career.”

featured in #612