/Management

Setting Policy For Strategy

- Will Larson tl;dr: Will explores setting policy as a critical step in engineering strategy, following exploration, diagnosis, and refinement. It defines policy as turning diagnosis into actionable decisions, covering coding practices, hiring mandates, and architectural choices. The chapter outlines structured steps for policy creation, types of policies, and criteria for effective policies. It also discusses handling uncertainty, recognizing constraints, and addressing missing strategies. 

featured in #598

The 5 Most Difficult Employees (And How To Actually Handle Them)

- Claire Lew tl;dr: Claire shares the five most challenging employee archetypes she’s encountered, and the specific strategies that can help you lead them successfully: (1) The Entitled Veteran. (2) The Passive Resister. (3) The Brilliant Aggressor. (4) The Perpetual Victim. (5) The Performance Rollercoaster. 

featured in #598

Delegating Complex Tasks

tl;dr: Most leaders can delegate simple things - e.g. teams, metrics - pretty well. Most leaders struggle with delegating complex skills or responsibilities. Herein we’ll discuss two proven methods for delegating complex tasks that you can use right away - exponential training and suboptimal standardization.

featured in #597

The 5 Most Difficult Employees (And How To Actually Handle Them)

- Claire Lew tl;dr: Claire shares the five most challenging employee archetypes she’s encountered, and the specific strategies that can help you lead them successfully: (1) The Entitled Veteran. (2) The Passive Resister. (3) The Brilliant Aggressor. (4) The Perpetual Victim. (5) The Performance Rollercoaster. 

featured in #597

AI Dev Tools Are Focused On The Wrong Problem

- Dennis Pilarinos tl;dr: The biggest challenge in software development isn’t writing code. It’s finding the context to know what code to write.

featured in #597

The Omniscience Expectation And The Mardenfeld

- Kellan Elliot-McCrea tl;dr: “For many leaders the hardest job they have is getting comfortable with not knowing. It is natural to feel like you have to understand everything about the area that you lead. My boss expects me to be able to answer an arbitrary question on the spot, in order to accomplish that I need to be an expert on an increasingly large number of topics. I accomplish this by asking for more and more detailed information from my team, perpetuating this omniscience expectation. There are two obvious problems with the omniscience expectation (and one non-obvious problem).”

featured in #596

Rethinking LLM Inference: Why Developer AI Needs A Different Approach

- Markus Rabe Carl Case tl;dr: “This post breaks down the challenges of inference for coding, explaining Augment’s approach to optimizing LLM inference, and how building our inference stack delivers superior quality and speed to our customers.”

featured in #596

Should Managers Still Code?

- James Stanier tl;dr: “The short answer is that it depends exactly on what you mean by coding. I think that there is a big difference between being in the code and writing code. All managers should be in the code, but not all managers should be writing code.” James elaborates.

featured in #595

The Trouble With “Good Enough"

- Wes Kao tl;dr: “If you say “good enough” and there are 50 operators listening, it can be expected that there will be 50 different ideas of what “good enough” means. This is a problem (and opportunity) for you.”

featured in #595

AI Dev Tools Are Focused On The Wrong Problem

- Dennis Pilarinos tl;dr: The biggest challenge in software development isn’t writing code. It’s finding the context to know what code to write.

featured in #595