r/PromptDesign

Hello everyone!

I’m wrapping up my CS degree and recently spent a lot of time diving into "Vibe Coding" with Claude Code.

As a result, I built an automated prompt optimizer:

"My Personal Prompt Engineer"

The tool is built on a One-Click approach to maximize speed and eliminate manual iterations.

The goal is to strip away the overthinking:
You provide your raw intent in plain language, and the tool instantly transforms it into a professional, high-performance prompt
.

✅ 3 Modes (Fast, Pro, Master)
✅ Token-efficient logic
✅ 100% Privacy-first (Browser-based)
✅ Completely free

It started as a portfolio project, but I was surprised to see similar tools charging $5–$20/month for even more basic functionality.
After testing several paid options, I’m confident that the logic I’ve implemented produces better results.

I’ve kept it free because it was a "side hustle" to master the tech, but seeing the market demand makes me wonder if this is more than just a side project.

Would love your feedback!

Hey everyone,
We’ve all been there: you’re using an AI autocomplete, and it suggests a perfectly formatted method call... for a method that doesn’t exist in your codebase. Or, the tool is so slow to "index" your repo that you've already finished the line by the time the suggestion pops up.
I’ve been looking into **RepoFuse**, a framework designed to solve the "Context-Latency Conundrum."
**The Core Tech:**
Instead of just dumping your whole repo into a prompt (which kills speed and hits token limits), it uses something called **Fused Dual Context**:
**Rationale Context:** It builds a semantic graph of your imports, classes, and methods so it knows what’s actually available.
**Analogy Context:** It finds similar patterns elsewhere in your repo to guide the logic.
**Why it’s different:**
It uses **Rank Truncated Generation (RTG)**. It basically "compresses" the repo's wisdom into a tiny, high-density prompt. In benchmarks (CrossCodeEval), it’s showing \~40% better Exact Match scores and is roughly 25% faster than standard RAG-based completion.
**Check it out here:** \[RepoFuse.com / GitHub Link\]
I’d love to get some feedback from people working in large monorepos. Does your current setup struggle with cross-file context?

Spent the weekend running an identical prompt across GPT 4o, Claude Sonnet, Gemini, and Llama. The fun discovery was not that the answers differed (that was expected). It was how much the prompt that worked best differed.

Same task: “Explain quantum entanglement to a curious 14 year old, then give 3 follow up questions they could ask.”

GPT 4o needed almost no instruction. The default tone landed beautifully.

Claude responded best when I added “warm but not childish.” Tone landed perfectly after that.

Gemini did really well when I added “use one analogy, then explain it.”

Llama improved a lot with explicit format, length, and voice guidance.

I have been doing these comparisons through Gen36 AI lately (the “AI Superbot,” every model in one chat). It makes A/B testing super easy because you do not have to copy and paste across tabs.

Bigger insight I am landing on: prompt engineering is becoming model engineering. The “same prompt” produces the best results when you tune it per model.

How are you all handling this in your workflows?

Hey everyone,
l've been a developer for a while now and I kept running into the same problem - I had dozens of repos, half-built projects, and scattered scripts sitting in GitHub doing nothing. Every time I wanted to start something new, I'd think "I feel like I've already built part of this somewhere..." but I never knew where.
So 1 built RepoFuse.
What it does:
RepoFuse connects to your GitHub, scans your existing repositories, and uses Al to surface buildable product ideas based on what you've already written.
Instead of starting from scratch, it finds the patterns, modules, and logic you've already built — and shows you what you're closer to shipping than you think.
Who it's for:
Solo devs and indie hackers sitting on a graveyard of half-finished projects
Dev teams who want to extract more value from
their existing codebase
• Non-technical founders working with developers who want to understand what's already been built
Why I built it:
Most "idea generators" give you generic SaaS ideas with no connection to your actual skills or existing work. RepoFuse is different — every idea it surfaces is grounded in code you've already written. It's not guessing. It's analyzing.
Where it's at:
RepoFuse is fully launched and live. You can con V your GitHub and get your first analysis today.

https://repofuse.com

I think prompt engineering communities are slowly getting flooded with low-value content.

A lot of posts are becoming:

"prompts that will change your life”

“10 AI prompts for insane results”

“Copy this prompt for perfect output”

But honestly, most of these prompts can themselves be generated by another AI in seconds.

You can literally ask an AI:

“Give me 10 prompts for better images”

or

“Generate 7 prompts for productivity”

and it will instantly create them.

So after a point, these posts stop being real prompt engineering and become prompt recycling.

I thought the goal of this subreddit was deeper than that.

-Prompt engineering should be more about:

- how to structure instructions

- how to control outputs

- how context changes results

- how models interpret language

- prompting techniques

- reasoning methods

- system design

- failure cases

- improving consistency

That is actual skill.

A random list of “10 prompts” is usually just surface-level content that anyone — or any AI — can mass produce endlessly.

That is just engagement/karma farming.

The real value is not the prompt itself.

The real value is understanding WHY a prompt works.

not a sponsored post. not affiliated with anyone. just genuinely surprised by what happened.

same prompt. word for word. copy pasted across all three. same temperature. same context. same everything.

completely different outputs.

ChatGPT:

clean. structured. confident. gave me exactly what i asked for in exactly the format i expected.

technically correct. emotionally flat. felt like a very good intern who understood the assignment perfectly and had no opinions about it.

Gemini:

longer. more thorough. cited things. felt like it was trying to impress me with how much it knew rather than actually helping me with what i needed.

the answer was in there somewhere. took a while to find it.

Claude:

did something i didn't ask for and didn't expect.

answered the question. then added one paragraph that started with "one thing worth considering that your question doesn't directly address—"

that paragraph was the most useful thing i got from any platform that day.

it noticed something sitting just outside the frame of what i asked. without being prompted. without me asking for it. just. offered it.

like a collaborator who actually read the brief instead of just executing it.

the difference i've realised after months of using all three:

ChatGPT executes.

Gemini elaborates.

Claude thinks alongside you.

all three are useful. they're useful for different things.

but if the problem requires actual thinking rather than execution or information — one of them is doing something the others aren't.

the uncomfortable part:

i've been defaulting to ChatGPT for everything out of habit.

habit built in 2023 when it was the only real option.

it's 2026. the options are different now. the gap between platforms is real and task-dependent and i've been ignoring it for two years because switching felt like extra friction.

the friction took four minutes.

the difference in output quality was not small.

run your most important prompt across all three this week.

not to find a winner. to understand which tool is actually right for which kind of problem you have.

the answer is different for everyone. but you can't know yours until you actually compare.

which platform surprised you when you actually tested them side by side?

Anyone knows a site or Application that I can store my prompts?

I want to use as library to permit to search anytime for some specific caracters or tags.