Tea scam i guess

Matched with a girl on a dating app recently.

We chatted for a bit, she shared her number, and we moved to a call.

Next day she tells me she's bored. We talk for a while and somewhere in the conversation she says she hasn't had tea and feels like ordering something from Zomato.

I was like, "Yeah, order something."

She says she's not able to.

Then: "Why don't you order it for me? And you can pay the delivery guy too."

😂

Mind you, we haven't even met yet.

It wasn't about the money. A tea/snack order isn't exactly going to bankrupt me.

But something about a person I've never met asking me to order and pay for their food barely a day after matching just didn't sit right with me.

So I didn't argue, question her, or try to figure out what the angle was.

Just politely got off the call.

Blocked the number.

Went back to the dating app and reported the profile.

Maybe I'm getting old, but is this normal on dating apps now? 😂

Would you guys have done the same, or am I reading too much into it?

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u/Top_Star_9520 — 9 days ago
▲ 2 r/ClaudeCoder+1 crossposts

Built a lightweight macOS menu bar system monitor because I got tired of opening Activity Monitor constantly.

Built a lightweight macOS menu bar system monitor because I got tired of opening Activity Monitor constantly.

Current features:

  • CPU usage
  • RAM usage
  • Network activity
  • Disk stats
  • Native macOS-style menu bar UI
  • Lightweight + fast refresh

But the interesting/problematic part is something else I’m trying to solve:

I’m experimenting with integrating live AI account/API monitoring directly into the menu bar.

The goal is:

  • monitor multiple AI providers/accounts
  • show live rate limits
  • remaining quota/tokens
  • request usage
  • account health/errors
  • model availability
  • maybe even cost burn rates later

Right now my approach is pretty messy:

  • polling APIs periodically
  • provider-specific adapters
  • local caching
  • fallback retries
  • some manual parsing because every provider exposes limits differently

The biggest issue:
There’s no standardized way to monitor AI account limits/usage across providers in real time.

Some APIs expose headers.
Some expose dashboards only.
Some expose delayed billing APIs.
Some expose nothing useful at all.

What I’m lacking:

  • a clean architecture for multi-provider rate-limit monitoring
  • efficient refresh strategies without wasting API calls
  • better approaches for live quota tracking
  • ideas around normalization across providers
  • maybe websocket/event-driven approaches instead of polling

Would genuinely love input from people building with OpenAI/Anthropic/Gemini/Groq/etc.

How are you currently tracking:

  • rate limits?
  • token usage?
  • spend?
  • degraded model availability?
  • multiple accounts/projects?

Also:
What stats would YOU actually want visible in a menu bar AI monitor?

u/Top_Star_9520 — 5 months ago