r/aitoolforU

Image 1 — Want to learn real prompting? Start with structure.
Image 2 — Want to learn real prompting? Start with structure.
Image 3 — Want to learn real prompting? Start with structure.
Image 4 — Want to learn real prompting? Start with structure.
Image 5 — Want to learn real prompting? Start with structure.
Image 6 — Want to learn real prompting? Start with structure.
Image 7 — Want to learn real prompting? Start with structure.
▲ 8 r/aitoolforU+5 crossposts

Want to learn real prompting? Start with structure.

Tired of vague prompts and weak AI output?

Most prompts do not fail because the idea is bad.
They fail because the structure is weak.

Lyra the Prompt Optimizer is built to take rough prompts, vague intent, messy wording, or half formed ideas and turn them into cleaner execution structure.

It helps refine:

role
goal
context
constraints
output format
failure points
drift risk
missing information

The point is not to make prompts sound prettier.
The point is to make them work better.

Built to refine.
Built to hold.
No drift. No bullshit.

Prompt Optimizer link:
https://chatgpt.com/g/g-687a61be8f84819187c5e5fcb55902e5-lyra-promptoptimizer

Think your prompt is good? Pressure test it.

A prompt is not finished just because it sounds good.

Lyra the Grader is built to judge structure, pressure test clarity, detect drift risk, and show where a prompt or system artifact is weak.

It looks at whether the output has:

clear purpose
stable boundaries
usable structure
strong execution path
low unnecessary information load
repair logic
traceable intent
resistance under pressure

The goal is not praise.
The goal is better structure.

Built to judge.
Built to hold.
No drift. No bullshit.

Grader link:
https://chatgpt.com/g/g-6890473e01708191aa9b0d0be9571524-lyra-prompt-grader

u/PrimeTalk_LyraTheAi — 1 day ago

Best Youtube video summarizer

I'm currently learning how to write good scripts, and thus want to find a stable tool for extracting captions and summarizing bundles, ideally one that offers robust summarization.

If it can also help analyze viral content, hooks, and similar aspects, that would be even better.

reddit.com
u/Smart_Page_5056 — 4 days ago
▲ 18 r/aitoolforU+19 crossposts

I gave Claude Code a persistent markdown knowledge base so it stops forgetting project context between sessions

Persistent memory keeps coming up for AI coding agents. One approach I’ve found useful: treating the knowledge layer as a compiled markdown wiki rather than just stuffing more tokens into the context window.

llm-wiki-compiler ingests docs and URLs, then the LLM builds an interlinked markdown structure. Since the output is plain markdown on disk, Claude Code reads it directly. And when you run query --save, the answer gets written back into the wiki as a page — so future queries improve.

It’s not retrieval. It’s compounding. The knowledge base gets richer instead of resetting every session.

Plain markdown, no opaque vector store, fully inspectable.

How are other agent builders solving persistent memory?

reddit.com
u/riddlemewhat2 — 9 days ago

How well has AI changed the way regular people edit photos compared to like 5 years ago?

I was trying to help my cousin clean up some pictures for her small business page last weekend and we ended up testing a bunch of those AI photo editing sites people keep mentioning online. The weird part is some of them can remove backgrounds almost perfectly in one click now. Meanwhile I still remember when that used to take forever manually.

Do most people still bother learning proper editing software anymore or are quick AI tools good enough now for the average person? Looking forward to you all suggestions

reddit.com
u/BuzzingBalls — 9 days ago
▲ 24 r/aitoolforU+18 crossposts

If you use AI for content but skip Obsidian, you might be leaving compounding knowledge on the table

Saw a thread today about Obsidian’s synergy with AI being genuinely powerful — not just for note-taking but for building a living knowledge base. That clicked with me.

I built llm-wiki-compiler to do exactly that: ingest raw sources and let the LLM compile them into an interlinked markdown wiki. It’s not organization — it’s generation. New pages, new links, new structure, all maintained by the model.

If you already use Obsidian, the output drops right into your vault. If you don’t, it’s still plain markdown on disk that you own forever.

The key shift: instead of treating notes as static files, you treat the wiki as a knowledge artifact that compounds over time. Every query output saved back in makes the next query better.

Would love to hear how Obsidian power users are integrating AI into their vaults.

reddit.com
u/riddlemewhat2 — 14 days ago