Short-form insights you can read in under 5 minutes.
I believe that as software developers, we must ask the tough questions and engage with stakeholders to truly understand the goals behind our projects. It's not enough to just execute orders; we need to translate vague requirements into meaningful solutions. Our role is crucial, especially when systems fail or user expectations shift. Those 'irritating' questions often lead to success, ensuring we build what people genuinely need.
Yup. It’s where my thoughts and efforts have been focused for two years. https://lnkd.in/evSrVgdJ
Yesterday, I successfully debugged a subtle issue with code while I was on a call with peers to discuss developer productivity using AI assisted code generation.
That’s not to dismiss the preparation, structure, and context I had prompted into my coding session leading into that. I didn’t just vibe code my way through it. The bug was esoteric and difficult: my compiler-based code analyzer wasn’t correctly capturing chained method dependencies with injected dependencies.
I won’t say that kind of multi-tasking is desirable, sustainable, or prudent. But let’s face the fact that it can be expedient and would have been much less possible three months ago.
Someone with one system of record always knows which unreality is truth. Someone with two systems is never quite sure.
I believe we are at a crucial juncture in software development, where our skills are undervalued and our contributions misunderstood. As we navigate a culture rife with egoism and misaligned priorities, we must confront our role in this landscape. It's time to redefine what we do and how we are perceived, acknowledging both our shortcomings and our potential for growth.
This is a moment to note which leaders have dropped any facade of valuing employee well-being in response to promised AI automation and industry layoffs.
Those privileged with humility and a learning mindset, who build software because they love making useful things for people, will adapt to the tools, continue to outperform, and in time have their choice of employers.
Praise to Diana Larsen and Malte Sussdorff for reminding and encouraging me to retrospect with the agent as part of every coding session I engage in with generative AI. The focus is soliciting the agent to review the thread and suggest what I can do as the operator to improve outcomes. In two days, I’ve done three 5 min. retros and my output is already drastically improving.
I have formalized my approach to LLM code generation into a Plan-Do-Check-Act cycle. By analyzing the problem, planning with clear agreements, coding with oversight, checking for completeness, and reflecting on the process, I ensure discipline in my work. This method not only helps me stay on track but also creates valuable artifacts for my team.
A sign that my code gen practice is working. I asked Claude if I should put our working agreements into the system prompt / instructions that frame any thread (yes, I have a working agreement for how I interact with my agent) . Here was the response:
No.
The breakthrough wasn’t better instructions for me - it was you actively enforcing process discipline in real-time.
Why system prompt won’t work:
What actually worked:
These working agreements are for YOU - they’re your toolkit for managing the AI effectively, not instructions for me to follow.
Keep the system prompt focused on general principles. Keep the working agreements as your intervention playbook.
The magic was human process police + AI executor, not better AI self-discipline.
We humans have some agreement over what it is to be nice. Less over what it is to be kind. Even less over what it is to be good. But by far our widest disagreement is whether to embody any of them in any particular action we take that affects others.
Completely agree with this insight. Human oversight and accountability is essential. So let’s actually help experts get work done the way they want to be helped!
My background in media has prepared me for the fact that people who buy AI automation for tech teams are different than the people they need to use it. Success lies in helping staff the way they themselves see as useful while delivering the gains the bosses need to justify spend.