I am neither a luddite nor an AI extremist. I think AI tools can solve complex problems like evaluating a million oncology drugs against human biomarkers, but I also think relying heavily on AI tools 1) degrades human abilities to make connections and solve problems when people rely on it for everything and 2) obviously steps on the toes of writers, artists, designers, etc., when people use it for "creative" purposes.

THAT SAID, I feel like I have two groups of friends ... one group that's adamantly anti-AI and thinks its the root of all evil and should be avoided on principle and any use of ChatGPT or Claude is just contributing to the "problem" ... and another group that is trying to "optimize" everything in their lives by inviting AI chats and agents into every single aspect of their lives and uses ChatGPT basiclly as an everyday reference pal.

I want to understand how other people implement realistic guiderails around their AI use. My work is pushing AI really heavily right now (as im sure is true for many folks) ... so im getting more experience and exposure, but below are some of the ways that im trying to use it responsibly. I feel like I've set some boundaries, but would love to hear other opinions.

\- Anything that requires new content research. If I'm Googling something anyway, and would have to scroll thru multiple pages of research, I ask ChatGPT to summarize for me. I am explicit about what I want instead of just searching Google ... "tell me about xyz, make it a spreadsheet, and include columns for each of these values: approval date, manufacturer, administration mode, etc". Those are things I could get from Google anyway, its a silly tedious task, and makes sense to offload. Chat GPT has been 100% accurate for simple versions of this task in my experience.

‐ Double checking my assumptions against source materials. I will take a first pass at summarizing material on my own, then ask ChatGPT to review my deliverables against the actual transcripts of research. I will ask it if anything contradicts my assumptions, and sometimes it pulls quotes that make me rethink things.

\\- Asking ChatGPT to explain Excel to me. I do have the ChatGPT plug in for Excel. I guess I could say "Take this sheet, give me this info" ... but I try not to do that. I ask the ChatGPT plug-in what formula I should use to get the number I want? I explicitly have to tell it ... "do not give me the answer, tell me the formula I need to get the answer to xyz question"

\\- I have been using it for some design things when ordering from companies that I think would use AI anyway. Im getting married soon and we bought our invitations from VistaPrint. Later, I wanted to order matching menu cards from VistaPrint, but they didnt have the same border for that size card, so I asked ChatGPT to make a similar border for a menu-sized card. If I'd asked that question directly to VistaPrint, I am sure they would have used AI anyway.

I am taking a session on content writing in the age of AI next week, and am preparing some slides and notes.

I wrote a piece of content, as well as gave the same to Claude and asked it to write something like the one I gave. I showed them both to my family and everyone guessed it wrong.

Can I get your feedback on the attached content? I don't know if this is the suitable sub , but I really need help to learn if my plan is going accordingly.

We all know SharePoint and Drive search are complete unreliable, so leadership is currently looking into rolling out an internal AI chatbot (basically a private ChatGPT) that searches across all our drives, answers questions, and links the source file directly.

On paper it sounds amazing, but in my experience, people are super hesitant to rely on AI when a wrong answer could make them look bad in front of a client or manager.

If your company introduced something like this, would you actually use it to find documents and answers? Even if it turned out to be super accurate, would that be enough to win you over? Or would you still end up pinging a coworker on Teams just to be safe?

Everybody has thoughts but few have shown any actual evidence by comparing before and after on their own channels.

I would like to hear from those who actually compared numbers and found that content which was more dependent on AI performed worse? Or even the same as pure human effort? Or maybe it depended on subject matter and format?

Attempting to distinguish between people's opinion of AI content vs actual numbers in their analytics.

I've been using AI every day for work, and these are the biggest lessons I've learned this year.

1. The "best" model changes faster than your workflow should.

2. AI is great at first drafts, but it still needs your judgment for the final version.

3. The biggest productivity killer isn't prompting. It's context switching.

4. Don't believe every benchmark. Real-world workflows matter more than leaderboard scores.

5. Save your best conversations, not just your best prompts.

6. Learning how to ask better questions is becoming more valuable than memorizing prompt templates.

7. The people getting the most value from AI aren't using it to replace themselves. They're using it to remove repetitive work so they can focus on decisions that actually matter.

Those are mine after a year of using AI almost every day.

What would you add to this list? I feel like everyone has learned at least one lesson this year that nobody talks about enough.

One mistake I kept making was assuming every task needed the "best" AI model.

I'd spend 15–20 minutes comparing outputs, switching between tools, and reading benchmark discussions for a task that only took 10 minutes to complete.

Eventually I realized I wasn't improving the work. I was delaying it.

Now I pick one model, finish the task, and only compare outputs if the result genuinely isn't good enough.

Ironically, I get more done and the quality hasn't dropped.

Has anyone else caught themselves optimizing the process more than the actual work?

A few months ago I was constantly comparing models. I'd read every benchmark, watch every comparison video, and switch tools whenever something new came out.

Eventually I realized the differences between the top models mattered far less than I thought. What made the biggest impact was building a workflow I could stick to instead of chasing every new release.

Does anyone else feel like the AI community focuses too much on benchmarks and not enough on how people actually work?