Good Decisions
Hey!
Welcome back to another week of musings.
We spent the weekend taking care of our senior dog. Hopefully, you had a great weekend and managed to be rested for the week ahead!
Was this forwarded to you? You can subscribe here!
Things I enjoyed in the past week
After work: If AI takes all our jobs, what’s next for humanity? It's an interesting article about how many people are betting on AI to take our jobs and how Gen-Z views the current work landscape.
How to measure AI developer productivity in 2025 | Nicole Forsgren. In an AI-related note, this is closer to software engineering and how productivity with AI looks in practice.
My job has become dealing with tech debt on the daily. At the beginning, I would tend to think, "Who chose this?" Sometimes I was the culprit, other times people were no longer at the company, etc.
I know that it's easy to critique decisions in hindsight, since I wasn't there and knew what they knew, the pressure to deliver, etc. At this point, I'm not that interested in critiquing, but in spelunking what made those choices, even with my own decisions, I've been trying to document more the context and reasons for taking a specific decision.
In general, it's hard to know if you're making good or bad decisions in the moment; sometimes, it might not even matter if your team is in analysis paralysis. Like, if right now, you wonder how or who chose the current technology stack? The CTO might have built whatever they already knew at the time, Java, Python, in AWS. How is that going for your team or company? Another reason why it's hard to learn about how good a decision was is that it might just become "the way" of how a company operates, and people forget that someone chose that way.
Those types of implicit decisions might boil down to what a person or team knew at the time. Like, why did we choose PostgreSQL over anything else? People were choosing productivity if they already knew how to use PostgreSQL and keep it up and running without too much hands-on.
Other times, people take a lot of time when some of the stakeholders might want to have a "data-driven" approach. In these situations, I've seen people inadvertently overwhelming others with too much data or using only data that serves their purpose. Even with data, a lot of the time, decisions are based on instinct.
And this brings me to one of my recent observations: people with enough context seem to know what to do.
I think in practice, and using my earlier points, these people are decisive and are not afraid to be accountable, even if the choice is bad. Most of the time, it won't, and many times in a company, if you're asking a question, you already know the answer. "Should we shut down this non-growing project?", "Should we stop this project that is not making progress?", etc. Even if the choice is bad, being accountable and taking action to fix the situation before it gets to a disaster will earn the trust of your leadership.
So, how do we build enough context? In my case, I've been going through and having conversations with peers across all the teams under my organization, participating in product discussions, discovery, customer feedback, and working closely with teams on the ground.
Your turn!
Have you ever thought about how and who makes decisions at your organization or company? Have you ever had to decide to stop a tie-breaker? Let me know your thoughts by replying to this email!
Happy coding!
website | twitter | github | linkedin | mastodon | among others