🧭 THIS WEEK AT AI SECOND ACT
Howdy, much less news/announcements this week in AI land which is good. The year is winding down! I do like Thanksgiving in the US, once you hit that, you’re pretty much done, kind of / nearly. Been busy on my end with a strange work trip to Germany, home to Australia for a bit and now back to snow! Finally, some snow in Chicago.
<Australia hammered England in the (cricket) Ashes 1st test match and 2nd starts tonight - let’s hope for a repeat!> (slight aside)
Read below for understanding use cases, we’ve gone through a lot of AI topics, and we’ll definitely repeat/reinforce some intro topics.
One topic that is key is use cases, understanding actually how AI can help in real life.
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👉 You can also just hit "Reply" and let me know what you want more (or less) of, or use the poll to give feedback.
My goal is to make this as valuable and practical as possible as we navigate the new AI era. 🚀
🧰 AI NEWS + LEARNING
Here are a few things I found recently:
Helping schools navigate AI - Definitely super difficult for education in the AI era, both students and teachers. At least, a massive change era that is.
HBR Article - why AI initiatives fail - must read!
Editorial on AI & Healthcare - Guardian - I like the Guardian generally although seems quite anti AI these days.
And as usual, I’ve been busy building/hacking, I renamed the site and added more details of stuff I’m working on. Definitely rough/work in progress, WIP but moving fwd.
🗺️ FEATURED INSIGHT
How to Find AI Use Cases
Most teams overcomplicate AI. Finding actual use cases that provide value in real life is tricky, however.
Find a pain that happens every week. Fix the part that slows everyone down.
Here’s the 15-minute method I use with teams.
1. Look at your calendar
Your calendar tells you where the real work is:
Weekly reports
Status reviews
Approvals
Backlog grooming
Customer updates
Ask: Which of these meetings exist because someone had to prepare information manually?
That’s your first AI use case.
2. Look at the work people repeat
Every team has the same 3 patterns:
Something takes too long
Something needs rewriting or cleanup
Something needs summarizing or sorting
Examples AI can fix fast:
Drafting weekly summaries
Cleaning up requirements/user stories
Preparing customer responses
Turning messy notes into clean documentation
Synthesizing 10 sources into one brief
If it’s repeated and annoying, it’s an AI candidate.
3. Ask your team one question
Skip brainstorming sessions.
Just ask:
“What takes you 30–90 minutes every week that AI could shrink to 5?”
People always mention:
Documentation
Tickets
Emails
Reports
Research
Meeting prep
Knowledge transfer
Pick the one everyone nods at.
4. Map the workflow
Draw the steps on a sticky note:
Trigger → Work → Output → Who uses it
Then ask:
“Which step is slow, manual, or repetitive?”
That’s where AI goes.
Not the whole process — just the painful step.
5. Validate with a simple test
Use this one-sentence filter:
“If AI did this step, would the team save time every week?”
If yes → you found a use case.
If no → move on.
1-Hour Exercise for This Week
Check your calendar for any recurring meeting.
Identify the prep work that happens before that meeting.
Ask your team what part of that prep is slow or manual.
Test it with: “If AI did this step, would we save time every week?”
Create one use case, not ten.
Ship it. Measure it. Build momentum.
Weekly AI strategies for operating executives
— Brett
👉 Hit “Reply” and share your experience — I read every one!
Picture by Andrey Matveev on Unsplash.