Hey, Luca here! Welcome to a new edition of the 💡 Monday Ideas 💡 — ideas and readings to start the week on the right foot.
🎟️ Discover 8 levels of context maturity in AI engineering
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1) 🔍 Is validation really the new bottleneck?!
So are the pundits (like myself) right? Is validation the new bottleneck? I think it depends, but for Tolaria I surely spend a lot of time on it.
Every task that gets completed by the AI is shipped in a new alpha version and moved to the “in review” section, where I review it against my production vault.
Here, a few things may happen:
It’s good — I move the task to “to release”
It’s ~90% good — I do the final tweaks from my MacBook’s Codex
Needs work, but it’s still good progress — this is the trickiest to decide. If it’s incomplete but still useful, I have a bias towards progress and I release it anyway, creating a separate task for the improvements.
Wrong or not usable — this is where the task is sent “to rework”, with a QA comment about what needs to be fixed.
I do a big batch of reviews first thing in the morning, for tasks that were done overnight, and then usually again after lunch, and before dinner, where I also try to make sure the AI has enough to do for the night.
So today validation feels like the biggest bottleneck indeed, also because I believe the right course of action most of the time is to keep specs light and let the AI figure out stuff by itself.
For most features, even when the first pass is not exactly how I wanted it, there is an argument to be made that if it’s good progress it should be released anyway, and have users chip in and give feedback. This has worked well many times, and evolved the product in the right direction faster than if I had waited for a perfect first version.
Of course nothing of this is exactly new thinking (MVPs, etc), but I think what’s changing here is the magnitude. I find that the right course of action is constantly to release a bit more control than what I am comfortable with, and this boundary keeps moving.
I wrote more about this in the full piece on how I run Tolaria as a open source project 👇
2) 🌍 Async vs sync comms at Todoist
Remote work debates often get stuck in a binary: async good, meetings bad, or the reverse.
What I liked in my conversation with Gonçalo Silva, CTO of Doist, is that their view is much more practical. Doist has been remote-first for more than a decade, long before the COVID era, and they have learned that async-first does not mean async-only.
Async is fantastic when people need focus, when the topic is well-bounded, and when a thoughtful written update is enough. Doist replaced a lot of status rituals with async threads: people write updates when it works best for them, and others consume them on their own schedule.
But some conversations are simply bad async candidates. Gonçalo’s heuristic is to look at the number of iterations you expect:
“If you’re disagreeing with somebody and you feel like you’re not quickly advancing towards convergence, that is probably a great prompt to just hop into a meeting. We settled a conversation that had been going on for multiple days in a call in 14 minutes.”
If the topic starts from a blank canvas, involves disagreement, needs multiple rounds of back-and-forth, synchronous chats are the faster tool, and should not be seen as a failure of async culture.
You can find the full interview with Gonçalo here 👇
3) 📚 Weekly Readings
Finally, here are the best articles I have read this week:
🥇 AI Demands More Engineering Discipline. Not Less
12 min • by Charity Majors
When Charity writes, we listen. The real product of a software team is shared understanding, and AI-generated code makes that easier to destroy at scale. For this reason, discipline now matters more, not less.
🥈 Revised Rules of Engineering Leadership
8 min • by Will Larson
Will’s piece is a great attempt at updating classic engineering leadership rules and ideas for the agent era. A lot of great takes about migrations, domain expertise, harnesses, and more. Including practical examples!
🥉 Humans and Agents in Software Engineering Loops
7 min • by Kief Morris
This connects nicely with the loop-engineering conversation: humans should not micromanage every generated line of code, but design and improve the loop that lets agents build, test, and learn. Great article hosted on Martin Fowler’s blog.
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See you next week!
Luca