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u/FlatNarrator

▲ 37 r/dividends

Seeing this projection makes me so happy

5 years ago, I would never have thought I’d be looking at a chart where my portfolio generates six figures in cumulative dividend income over the next few years. I would’ve thought that was crazy.

https://preview.redd.it/8avnjjj7fc2h1.jpg?width=1158&format=pjpg&auto=webp&s=8f3915c0d9895e8d3333bd709062a1839295351c

Took me a while but I finally realized when you first start out, the progress feels painfully slow. You get a few bucks here and there, and it's hard to see the big picture. But consistency and letting the math do its thing changes everything

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u/FlatNarrator — 1 day ago
▲ 3 r/GolfGear

Has anyone here actually used a smartwatch with any golf training gear?

I’ve been messing around with Phigolf2 Flex lately and didn’t even realize until recently that it works through a smartwatch app too. I’m normally someone who hates extra setup or logging into stuff, but this was honestly simple. I downloaded the Phigolf app on my watch, paired it with my phone, and it basically just worked.

What surprised me is how convenient it is not having to constantly pull my phone out. I can just glance at the watch while playing the Phigolf game and keep going. It feels more like a quick casual practice session than sitting down and playing a “golf simulator.”

I’m using it mostly for tempo and keeping my swing consistent when I can’t get to the range.

Curious if anyone else here has tried phigolf or other similar gear.

reddit.com
u/FlatNarrator — 5 days ago
▲ 2 r/sideprojects

I built a tool that converts websites into iOS + Android apps (without rebuilding)

A lot of founders I know have a working website or SaaS, but mobile apps stay on the “later” list because rebuilding everything in Flutter/React Native feels like starting over.

So I built WebViewGold, a tool that helps you turn an existing website into a publishable iOS + Android app using a webview approach.

What it supports:

  • app store ready builds (iOS + Android)
  • splash screen + icons
  • push notifications support
  • file uploads/downloads
  • external link handling (open in browser vs inside app)
  • basic navigation controls

The biggest lesson from building this is that the quality of the final app depends heavily on how good your mobile website UX already is.

Would love feedback from anyone who has shipped webview apps long-term. What issues did you hit after launch?

reddit.com
u/FlatNarrator — 6 days ago
▲ 0 r/dividends

Anyone else realize their dividend income is wildly uneven throughout the year?

I always thought my dividend portfolio was “doing well” until I mapped the income month-by-month.
Turns out my cash flow was way more uneven than I expected.
Example from my latest breakdown:
March: $1,390
June: $1,423
September: $1,501
December: $4,017
But then some months were as low as:
January: $71
April: $61
November: $72
That completely changed how I think about building a dividend portfolio.
So I started focusing more on payout schedules and which holdings actually help smooth out weak months. Monthly payers like O and JEPI made a much bigger difference than I expected.
Now I’m trying to build more consistent monthly cash flow instead of only chasing annual yield.
Curious how everyone else approaches this:
Do you optimize for higher total annual income, or smoother monthly dividend consistency?

https://preview.redd.it/5tsmy3a06q0h1.jpg?width=1216&format=pjpg&auto=webp&s=2e405e2f0542bdd418f7a5dc94bbb7c6070ee327

reddit.com
u/FlatNarrator — 10 days ago
▲ 2 r/AskRobotics

How much of robotics failure is actually a data problem rather than a model problem?

I’ve been noticing a pattern in robotics discussions lately where most optimization effort goes toward models, hardware, or control systems, but less attention gets paid to the quality of the training data itself.

Especially for systems using vision or multimodal inputs, small issues in labeling or dataset consistency seem to create massive downstream problems:

  • object annotations that vary between annotators
  • edge-case environments that never appear in training
  • inconsistent sensor synchronization
  • data collected in conditions that don’t match deployment environments

What’s interesting is that a lot of these failures don’t show up immediately in testing, but later in real-world operation.

I recently read about teams like Unidata focusing heavily on the data preparation side for AI systems (collection, labeling, structuring for training), and it made me wonder whether robotics workflows underestimate how much reliability depends on dataset quality long before the model stage.

For people here working on robotics/vision systems:

  • Where do your biggest data bottlenecks usually happen?
  • Do you build datasets internally or outsource parts of labeling/annotation?
  • Have you seen cases where improving data quality mattered more than changing the model itself?

Curious how others approach this in production environments.

u/FlatNarrator — 14 days ago
▲ 86 r/dividends

I’ve spent the last couple of years chasing the next big thing and well... the screenshot speaks for itself. I’m currently sitting on over $4,700 in harvestable losses from positions like MSTR, RIVN and ACB.

My plan is to sell everything here and dump it into SCHD. Basically want to stop gambling and start building a reliable income

u/FlatNarrator — 15 days ago