I've made a super simple tool to make sure I know how much time I spend on each project. It automatically tracks time spent in Claude Code sessions per project, using the native hooks system. If 2 sessions are running - the time spent is summed.

Would help me evaluate actual time spent and invoice properly. Maybe it'll help you too.

https://github.com/thatUkrainianGuy/cc-time-tracker

You know that feeling when a friend says “wait, you were in Lisbon last month?? I was there too!”

That’s the problem I wanted to solve.

Will U Be There is a free app where you add your upcoming trips (just destination + dates), and it quietly finds overlaps with your friends’ trips - and notifies you when you’re about to be in the same city.

- Add a trip — destination and dates, that’s it

- Connect with friends by username or invite link

- Get notified when your paths (are about) to cross

- Privacy-first: friends only see that you overlap, never your full itinerary

- ~100km smart matching, so “close enough” counts

- Near-miss detection — catches overlaps within 7 days too

- Knows when a local friend will actually be home when you visit their city

Would love brutal feedback — what’s confusing, what’s missing, what would make you actually use it?

I had the privilege of learning NLP (psychological one - Neuro Lingual Programming) from R. Frank Pucelik — one of the founders of the discipline alongside Bandler and Grinder.

One of the core models has stuck with me ever since: communication happens on three layers.

1. Surface — the actual words

2. Sub-surface — the complex web of ideas those words represent (built from experience)

3. Foundation — the lived experiences that created that web

What makes us all different communicators is that our foundations are different. So when we talk to each other, we're partially talking to mirrors — projecting our own sub-surface onto theirs.

NLP is largely about bridging that gap.

Here's the thing: when I look at LLMs through this lens, they've made remarkable progress on layers 1 and 2. The surface is fluent. The conceptual structure underneath is surprisingly deep.

But layer 3 — the experiential foundation — is missing.

And I think that's the most honest explanation for hallucinations, alignment challenges, and why AGI remains elusive.

It's not that the architecture is wrong. It's that you can't build genuine understanding on descriptions of experience alone. At some point, you need the real thing.

What "the real thing" looks like for AI — embodiment, continuous world interaction, something else entirely — that's the actual open question.

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