u/Interesting-Post4178

I have been using openclaw / claude whatever pretty much daily and the thing that keeps bugging me is meetings.

like every meeting I take, half the actual value disappears the second the call ends. Someone agrees to something, a client drops important context, and a week later when I open the agent to help draft the follow-up it has no idea any of that ever happened.

basically should meetings be part of an agent's long-term memory? agents feel smart inside one chat and then forget everything that matters about how my work actually operates. meetings are where most of that real context gets created, then it dies in a transcript or a notion doc somewhere.

anyone else feel this? or does the idea of an agent sitting in on your calls and quietly keeping notes and remember people over time feel too creepy to actually want?

This may be a weird one, but I’ve been thinking about AI reliability through the lens of fortune-telling.

Not because I’m trying to prove astrology is real. More because some traditional systems are surprisingly structured, and general-purpose AI tools are not always great at respecting structure.

A while ago, I had dinner with a mentor of mine. He’s one of the most analytical people I know, very much not a “just trust the universe” type. Somehow the conversation drifted into a traditional Chinese astrology-like system called Zi Wei Dou Shu.

The easiest Western explanation: imagine astrology, but someone replaced a lot of the feelings with a spreadsheet.

You take a birth date and birth time, run them through fixed calculation steps, and generate a structured chart. That chart is then interpreted across personality, work style, relationships, and life timing (example below).

What surprised me was how rule-based it actually is. Whether or not you believe in it, the chart itself is not supposed to be “just vibes.” There’s one question of whether the chart is calculated correctly, and a separate question of what the chart means.

So I tried running the same case through ChatGPT, Claude, and Gemini.

The same birth information produced different underlying charts across different models. Sometimes the same model shifted slightly depending on how I phrased the prompt.

Not just different interpretations. Different base charts, which means the polished explanation on top was sometimes just confident-sounding text built on the wrong foundation.

That bothered me more than I expected. So I stopped treating it like a fortune-telling problem and started treating it like a reliability problem.

I separated the chart calculation from the interpretation layer. The calculation part should be fixed, rule-based, and not something the AI gets to freestyle. The LLM is useful after that: explaining the chart in plain English, making it understandable, and connecting the dots.

The output felt different. Less generic, more specific, probably because the AI was explaining from a fixed structure instead of making things up from scratch.

I tested it on myself and a handful of friends. I was expecting polite reactions. What I got was people stopping mid-read to ask how it knew certain things, work patterns, how they handle relationships, a tendency they'd never mentioned out loud. Not everyone, but enough that it wasn't coincidence. The ones who were most skeptical going in were also the most unsettled coming out. That's when I stopped thinking of this as a fun experiment.

But there’s still a harder layer: edge cases.

Some rules aren’t perfectly resolved through documentation alone. For example, how birth location affects the chart, or where exactly the cutover falls between one day and the next. These are the kinds of things you can’t fully prompt your way out of. You need historical cases, test sets, and calibration.

That’s the part I’m curious about for AI builders:

For domains where the core rules are deterministic, but edge cases are ambiguous and only resolvable through historical data, what’s the best architecture?

• Rule engine + LLM explanation?
• RAG over expert documentation?
• Fine-tuning on historical cases?
• Something else?

I’m still experimenting with this and would love thoughts, especially from people who are skeptical. The fortune-telling part is weird, I get it, but the reliability problem feels pretty real.

example output:

https://preview.redd.it/qh9fbyeqn41h1.png?width=1364&format=png&auto=webp&s=552233468c1bb54e84253bbb43c434f3cbc777a9

I’m still pretty new to Reddit, so maybe I’m missing something here.

I joined a subreddit and made a post asking how people take meeting notes - what tools they use, how they keep track of action items, how they make notes useful after the meeting, etc.

That was it. I wasn’t trying to sell anything or promote anything. I genuinely just wanted to hear how other people do it.

But my post got removed and I got banned.

I get that every subreddit has rules, and mods probably deal with a lot of spam. But as a new user, it honestly felt confused. It’s hard to know what's appropriate for a community when you barely get a chance to participate.

Has this happened to anyone else? Anything I can do improve?

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