That split us pretty quickly in the latest Live I hosted with , , and .

Alicia thought obvious AI copy from someone she knows looks lazy. Anjeanette’s first instinct was more generous: maybe they were just busy. Cory admitted some of his earliest writing was “fully AI slop”, but said it gave him the confidence to start.

The argument really came down to standards 👇🏻

When does saving time with AI become an excuse for work you wouldn’t have accepted from yourself before?

When anyone could have written it

Anjeanette calls it the “robot voice problem”.

“If literally any other human in my position could write this post, then it’s probably not good enough.”

For Alicia, the problem is copy that says plenty without saying anything specific:

“AI says something that anyone could have said. Oftentimes it says a lot without saying anything whatsoever.”

She asks whether you’d actually talk like that to someone over lunch.

The copy can read perfectly well while leaving almost nothing recognisable about the person publishing it. Something recognisably yours should survive the process.

And you still need enough judgement to notice when the person has disappeared from the work.

Can AI teach you to write?

Alicia thinks people who are still learning to write should be particularly careful.

“If you don’t know what AI copy looks like, you don’t see it. Then it’s really hard for you to take the AI back out of it.”

Cory disagreed based on his own experience. He used to think he was a terrible writer, and AI gave him somewhere to start.

“The content I used to put out was just fully AI slop. But it gave me the confidence to get going.”

He used it to understand how other writers structured things and learn techniques he hadn’t picked up before. He doesn’t rely on it in the same way now.

Claudia is comfortable letting AI into the process earlier.

“It really comes down to the human editing.”

She’s happy for AI to help with an early draft, provided she goes back through it, changes the tone and removes what doesn’t belong.

Cory learnt as he used it. Alicia’s concern is what happens when somebody never builds enough judgement to know what needs fixing.

Starting with your own material makes it easier to keep yourself in the draft.

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Start with something that’s already yours

Cory now starts with material that already belongs to him. He records conversations, pulls transcripts into his system and uses AI to find ideas in things he has actually said.

“I don’t want my content to be written by AI. I want it to be the actual words that I say.”

Claudia often starts by dictating an idea into AI and using the conversation to think it through rather than asking it to produce something from nothing. I prefer that too because the model gets your context and natural phrasing before it starts drafting.

I’ve ended up doing much the same with my inbox. I recently connected ChatGPT after spending an unreasonable amount of time building SOPs and rules for how I deal with guest pitches, requests and follow-ups.

The first draft follows the rules I already use. I still review it, and if the action is wrong or the reply doesn’t sound like me, it doesn’t go out.

That source material matters. A transcript or voice note gives AI words and thoughts that already came from you. An SOP gives it decisions you’ve already made instead of asking it to guess how you behave.

Seven writers started sounding like one robot

At one point, Anjeanette had seven writers working across completely different industries, and their work started sounding strangely similar.

“It didn’t matter what industry it was. All of a sudden, the same stuff started coming in.”

She was fine with them using AI.

“I don’t care if you use AI, but don’t let me know that you used AI. Trick me.”

What frustrated her was that some writers had discovered they could produce in ten minutes what previously took two hours, then hand over the first thing AI gave them.

“If they had just spent the time to master the tool and get a little better at it, I would never have known.”

Their output pushed her to learn the tools herself. Eventually she started asking why she was paying people for work she could produce better on her own.

What cost them was handing over work that made the shortcut obvious.

Sometimes the right move is not to post

I asked when they’d rather skip a post than put their name to something AI created.

Anjeanette’s line is whether she can still recognise the person in the work:

“If you can’t recognise yourself in it, or your client in it, I’ll scrap it.”

Alicia had posted on LinkedIn that day for the first time in a week because she hadn’t had the headspace.

“I would never put my name to something just for the sake of posting content.”

Claudia’s test is whether something personal still made it into the work.

“I draw the line when there’s no personal touchpoint.”

That could be something she’s experienced or actually happening in the business. AI can help shape it. She still wants something there that belongs to the person behind it.

Humans don’t have a protected monopoly on creativity that AI will never touch.

A lot of what we call original work is already a remix of things we’ve seen and learnt from before.

AI can absolutely throw out an idea I hadn’t considered, even if nine of the ten suggestions are mediocre at best.

Fine. I’ll use the spark. Once the draft exists, I still want to decide whether it’s something I actually believe and whether the standard is good enough for my name.

If my name is on it, I want the judgement behind it to still be mine.

📡 Live Discussions

had it running in the background, reading a client email and attachment. had already checked in with his AI running coach about his ultramarathon training.

We’d gone live to talk about how much of our work AI should do while all four of us were already handing it jobs that would have taken our time a year or two ago.

What interested me more was how differently we treated those jobs once AI could do them without us. 👇🏻

Start with what you can check

Philip runs much of his business through Notion and now uses AI to build pages and set up automations without learning every click himself. Cory uses it for repetitive jobs throughout his day, documenting conversations, updating his CRM, preparing emails and finding people he’s forgotten to reply to.

Cory is comfortable handing over jobs where he can quickly tell whether they’ve been done properly. Summaries and moving information around are easy to check. Once something needs his judgement, he gets involved.

Joel goes further. When he publishes on Substack, AI can turn the original piece into a LinkedIn post and carousel, then publish them without him seeing them first.

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Trust has to be earned

Joel spent months testing the process and adjusting the rules before he was comfortable letting it run alone. He knows the original material well enough to judge the LinkedIn version because he wrote it and spent months testing the process.

On another post, he was short on time and let AI write the introduction. He published it, read it again five minutes later and took the whole post down. The SEO and keywords were fine, but it didn’t sound like him.

That first workflow works because Joel knows the source material well enough to catch when the adaptation goes wrong. Handing over something you don’t understand yourself is much riskier.

Your name is still attached

Philip tried letting AI reply to his Substack messages early on and stopped within a week. Nobody complained. He didn’t like people believing they were having a conversation with him when they weren’t.

Joel draws a line around email and comments. AI reads the background and prepares a Gmail draft. He still checks it before anything goes out.

A bad post or piece of advice can damage trust you spent years building. If an email gets something wrong, the model doesn’t deal with the customer afterwards or explain bad advice to a client. You’re the one dealing with the fallout.

AI changes who you can hire

Hiring another virtual assistant made Philip look at AI from the other side: what could somebody else now handle with AI helping them?

Previously, they’d struggled to give a VA a wider range of jobs because the business had too many moving parts to pick up quickly. With good documentation and the AI tools they’ve built, a new VA can take on more much sooner without knowing every corner of the business first.

It made me ask something else: what happens when AI helps you do something before you’ve learnt enough to judge the result?

The polished answer can still be wrong

If you don’t understand good writing, you’ll struggle to spot a weak draft. The same problem appears when AI communicates with customers or makes decisions for you. A mistake in judgement can now sit underneath perfectly reasonable wording.

Cory disagreed with part of that. Some of his early LinkedIn writing with AI was awful, he said. The important part was that he started writing. He paid more attention to other writers and asked better questions as his own writing improved.

AI can help you try something before you’re particularly good at it, and that can become part of how you learn. The problem comes if you never develop enough judgement to stop accepting whatever it gives you.

That becomes more important as AI starts doing more without you. I’m already giving it jobs I wouldn’t have handed over a year ago, and that list is growing.

Before I stop checking another one, I want to know I’d still catch the bad answer.

📡 More Live Extras

We got into ChatGPT vs Claude, role-based AI setups, why weak output is often a setup problem, and what changes when you stop treating a tool like it should do every job.

A lighter one than the usual Millennial Masters podcast, but plenty in here if you’re trying to make AI more useful inside real work.👇🏻

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Helping founders make better business decisions.

By Daniel Ionescu

What came up in the live

1️⃣ Stop using one chat for everything

A lot of weak AI use starts with people treating one chat like it should hold every task, tone, and context at once. Once the work gets more varied, that setup starts slipping fast. ⏱️ 08:19

2️⃣ One AI tool shouldn’t be doing five different jobs

Research, writing, editing, analysis, strategy, and admin all need different standards. A lot of disappointment starts when one tool gets asked to do too many of them badly. ⏱️ 11:33

🔗 Stop using AI assistants, build a 5-role AI team instead

3️⃣ If the output is weak, look at the setup first

Examples, tone, banned words, context, previous materials, and clear standards all matter more than you think. A lot of what gets blamed on the model is really bad setup upstream. ⏱️ 12:19

4️⃣ Voice dictation is still badly underused

If you’re still typing compressed prompts, you’re often starving the model of tone, detail, and intent. Speaking your thoughts out properly gives it much better raw material to work with, and it’s much faster than typing. ⏱️ 16:46

🔗 7 ways Joel uses voice dictation to 3x his output

5️⃣ A better setup beats a clever prompt

Once the conversation moved into orchestrators, sub-agents, and repeatable workflows, the bigger point was that useful AI is less about clever prompts and more about building a better system around the work. ⏱️ 19:04

🔗 How to use Claude Cowork task scheduler

6️⃣ ChatGPT vs Claude matters less than you think

The useful question is not which one “wins” in the abstract, but which one fits the job, the workflow, and the level of context you need. Tool choice matters, but setup and role clarity matter more. ⏱️ 25:00

7️⃣ You still need to decide what stays human

Delegation matters, but so does judgement. AI can take work off your plate without taking the parts of the job that still need your taste, voice, and final call. ⏱️ 52:24

🔗 Cross-domain thinking as an AI skill

8️⃣ Good AI use looks more like management

Once AI becomes part of the workflow, the founder job starts looking less like “using a tool” and more like setting roles, standards, and feedback loops properly. ⏱️ 53:44

📡 More Live Extras