r/SinceAI

I realized something interesting after watching two people use ChatGPT.

I mentioned ChatGPT to my mom and asked her to ask anything. She just asked a question, got an answer, and stopped there.

Later, my friend's son (still in school) tried it. He did the opposite. He kept asking follow-up questions.

"Can you explain why?"

"What if we do it this way?"

"Is there a better way?"

"Can you compare these two?"

Within a few minutes, the conversation had gone far beyond his original question.

It made me realize that the biggest difference isn't who knows more about AI.

It's who stays curious.

The people getting the most value from AI aren't always developers or AI experts.

They're the people who don't settle for the first answer. They question it, refine it, ask for alternatives, and use AI to explore ideas instead of just getting answers.

Maybe that's one of the most valuable AI skills we can develop.

Not writing better prompts. Learning to ask better questions.

Have you noticed this too?

A year ago, people were showing off agents that could autonomously run entire workflows. Now I keep hearing experienced teams say the opposite: the biggest productivity gain came from removing autonomy from parts of the system.

A lot of agent failures are not model failures. They are boundary failures. Giving an LLM access to Slack, email, code execution, browser control, and production data sounds powerful until you realize every extra tool multiplies uncertainty. The hard part is no longer getting the model to act. It is deciding where humans need to stay in the loop.

The teams I know getting the most value from AI are often using surprisingly constrained setups. Small context windows. Limited tool access. Forced review steps. Narrow domains. Less like "AGI employee" and more like "extremely fast intern with a very specific checklist."

It makes me wonder if the near-term winners in AI won't be the companies with the most autonomous systems, but the ones with the best judgment about where automation should stop.

Have you become more aggressive or more cautious about autonomy after using AI systems in real workflows?

A new study analyzed 25 million comments from Reddit and Hacker News.

The strange result wasn’t that people are good at detecting AI.

It was the opposite.

The writing patterns that actually distinguish AI text from human text did not predict which human-written comments people accused of being AI.

We’re not detecting bots. We’re punishing a vibe.

Write clearly? Bot.
Use an em dash? ChatGPT.
Structure an argument? AI slop.
Write badly on purpose? Finally, a real human.

The Turing test used to ask whether a machine could convince us it was human.

Now humans have to convince the internet they aren’t machines.

So let’s test Reddit.

Post a 2–3 sentence opinion about AI below. It can be written entirely by you or entirely by an AI. Don’t reveal which.

Everyone else replies:

HUMAN or AI — and why.

After at least three guesses, reveal the answer.

No AI detectors. No checking profiles. Judge only the text.

I think this thread will prove that most of us have absolutely no idea.

Someone just used Claude Fable 5 to build a 45,000-line Minecraft-like game in roughly a week.

Not one prompt but almost, still a pretty clear signal.

If custom software becomes dramatically cheaper to build, where does durable value move?

Hardware + software? Proprietary data? Distribution? Or industries like construction, energy and manufacturing where software has to meet the physical world?

Where would you build today?

Models are becoming better, cheaper, and increasingly interchangeable.

But most AI systems still cannot actually do anything.

They can recommend a purchase, but not place the order.
Detect a production problem, but not stop the machine.
Suggest a treatment, but not access the patient workflow.
Find financial risk, but not move the money.

The scarce asset may not be intelligence anymore.

It may be permission:

• access to proprietary data
• authority to change real systems
• trust inside regulated industries
• distribution to actual users

A chatbot can suggest. A company with permission can act.

If intelligence becomes a commodity, who owns the permission layer in your industry?

Let’s make this a weekly builder thread.

Whether you’re working on AI apps, agents, LLM tools, ML projects, robotics, research, startups, or automations — drop what you’re building below.

3 simple questions:

1. What are you building?
Share your project, idea, prototype, or experiment.

2. What are you learning?
Could be a model, framework, paper, tool, or skill.

3. What’s blocking you right now?
Maybe someone here can help.

The goal is to make r/SinceAI a place where builders can share progress, get feedback, meet serious people, and learn faster together.

If you’re lurking, this is a great first thread to comment on.