Field Notes
I keep thinking about Unreasonable Hospitality.
The book is about hospitality, but I do not think the lesson stays inside restaurants.
A lot of the magic comes from small touches.
The thing that feels extra.
The thing that does not fit neatly on a spreadsheet.
The thing someone remembers later because it made them feel considered.
Those touches always had a problem.
They did not scale.
That is part of why they felt special. A business could not automate its way into genuine care. Somebody had to notice the moment, have the taste, make the call, and do the extra thing.
AI changes the math.
It does not create taste for you. It does not make a lazy business suddenly thoughtful. But it can help a business remember more, prepare faster, connect the dots, and make the small touch possible more often.
That is the part I think a lot of people are going to miss.
Last time, we talked about specified intelligence. The point was simple: stop reaching for the biggest model by default. Name the job, name the source, name the risk, name the review gate, then pick the brain.
This is what comes after that.
Once you have the right intelligence pointed at the right job, what are you using it to create?
Most people will use AI to make the work faster.
Good.
They will use it to write the email faster, draft the proposal faster, summarize the meeting faster, respond to the customer faster, and ship the deliverable faster.
Also good.
But faster will become normal.
The tool is the floor.
How you use it becomes the moat.
If AI makes everyone more efficient, the small things matter more.
The follow-up that arrives before the client has to ask.
The update that answers the question they were secretly worried about.
The recommendation that feels like it came from someone who was paying attention.
The handoff where the next person already knows the context.
The experience where someone feels remembered in a normal, natural way.
That is the moat.
Playbook
Here is a simple restaurant version.
A guest books a reservation.
The restaurant already has a few pieces of clean context. Prior visits. Dietary notes. A special occasion. Maybe a quick pre-arrival question they willingly answered.
AI can help turn that into a better handoff.
The server knows what to recommend. The kitchen can prepare a menu path that makes sense. The manager can decide whether there is a small touch worth making.
The point is simple.
Use clean context to make the visit feel considered.
That is hospitality as the example.
But the pattern applies everywhere.
If you run a renovation business, the finished project is only one part. The client wants to feel like the project is under control while the walls are open and dust is everywhere.
If you run a consulting business, the final recommendation is only one part. The client wants to feel like you remembered the constraint they mentioned three calls ago.
If you run a software company, the bug fix is only one part. The customer wants to feel like support understands what they already tried and what outcome they actually wanted.
If you run a community, another event on the calendar is only one part. The member wants to feel like the room remembers what they are building.
This is where AI gets interesting for operators.
Your inbox becomes context.
Your meeting notes become context.
Your project files become context.
Your support history becomes context.
Your preferences, deadlines, open loops, past decisions, and recurring concerns become context.
All of that can become a memory layer for the business.
The mistake is thinking the memory layer is only for productivity.
It is also for experience.
Because the best experience often comes from remembering the right thing at the right time.
Here is the practical version:
- Pick one moment where a customer, client, guest, member, or partner feels something.
- Name the emotion you want them to feel instead.
- Identify the small touch that could create that feeling.
- Decide what context the business is allowed to use.
- Let AI prepare the draft, reminder, suggestion, handoff, or recommendation.
- Keep human taste at the review gate.
- Remember what worked.
That is the loop.
AI does the prep work.
The human keeps the taste.
The business gets better each time.
This is where the product quality conversation gets too small.
Using AI to make the product better matters.
Using AI to deliver faster matters.
Those things get you in the game.
The distance opens when the experience around the work gets better too.
Because people remember how the work felt.
They remember whether they had to chase you.
They remember whether you caught the detail.
They remember whether the process felt chaotic or calm.
They remember whether they felt like a transaction or a person.
That is the part AI can help with when the system is designed well.
The AI is just the prep layer.
The operator still has to give the business a way to remember, prepare, and follow through.
Orientation
This connects back to The Agentic Internet, The Model Doesn't Matter, and Specified Intelligence.
The Agentic Internet gives AI the ability to move through systems.
Workflows give it a path.
Specified intelligence helps you pick the right brain for the job.
Emotion gives the work a reason to matter.
That is the piece I do not want operators to miss.
The next wave of AI adoption is going to make a lot of businesses faster.
Some will stop there.
I think the better operators will ask a different question:
How can this make the experience more personal, more thoughtful, and more memorable?
Next time: The Real Measuring Stick.
Because once AI can make us faster, smarter, and more emotionally precise, the next question is simple:
What are we buying with all of that?
For now, pick one moment in your business where someone feels uncertain, stressed, excited, ignored, or unseen.
Then ask:
What small touch would change that feeling?
Comment below and tell me where AI could help you improve the experience around the process.
I read every one.
— Brian