# I lost my best AI prompt after 40 tweaks. So I built a tiny git for prompts.

> Source: <https://dev.to/lululuhu/i-lost-my-best-ai-prompt-after-40-tweaks-so-i-built-a-tiny-git-for-prompts-1d5j>
> Published: 2026-08-11 09:16:54+00:00

You're iterating on a prompt for an LLM. You tweak one word, the output gets better. You tweak another, it gets worse. You paste it into ChatGPT, it kind of works. You change "concisely" to "in 3 bullets", and suddenly the summaries are perfect.

Then tomorrow comes. And you have **no idea which version was the good one.**

Your folder looks like this:

```
prompts/
├── summarize.txt
├── summarize_old.txt
├── summarize_v2.txt
├── summarize_v2_final.txt
├── summarize_v2_final_FINAL.txt
├── summarize_REALLY_final.txt
└── summarize_use_this_one.txt
```

And the worst part? The "good" one might be any of them. 😭

You can't diff them. You can't tell what changed between `v2_final`

and `v2_final_FINAL`

. You can't roll back to the version that actually worked.

Good question. I asked myself the same thing.

You can. And technically, PromptVault borrows git's entire model — content-addressed objects, trees, commits. But in practice, prompts live next to code. They're mixed into repos, notebooks, chat exports, and random `.txt`

files on your desktop.

Prompts deserve their own version control that:

`.txt/.md/.prompt/.j2/.yaml`

files specifically`.pv/`

folder that doesn't collide with your code repo's `.git/`

So I built it. 🛠️

PromptVault is `git`

, but purpose-built for prompts. It's written in Rust, ships as a single ~2MB static binary, and runs entirely on your machine. No account, no cloud, no telemetry.

``` bash
$ pv init
Initialized empty prompt vault in ./.pv

$ pv add prompts/summarize.md
added: prompts/summarize.md

$ pv commit -m "refine: summarize now reports tone + title"
[main 791151d] refine: summarize now reports tone + title
 1 prompt
```

Now iterate. See exactly what changed:

``` bash
$ pv diff prompts/summarize.md
diff -- prompts/summarize.md
 You are a precise summarizer.

-Summarize the text below in 3 concise bullets, then propose a title.
+Summarize the text below in 3 concise bullets, propose a title, and note the tone.

 {{text}}
```

Walk back through every iteration:

``` bash
$ pv log
commit 791151d…
parent 4100199…
Date:   Mon Aug 10 10:04:33 2026 +0000

    refine: summarize now reports tone + title

commit 4100199…
Date:   Mon Aug 10 10:04:33 2026 +0000

    feat: initial prompt set
```

Restore any past version by hash, tag, or branch:

``` bash
$ pv show 4100199   # prefix works too 🔍
$ pv revert v1.0    # restore working tree to a tagged version ⏪
```

This is the killer feature for prompt engineering. You want to test two variants of the same prompt? Branch it.

``` bash
$ pv branch experiment
$ pv checkout experiment
# ... tweak the prompt, commit it ...
$ pv checkout main       # working tree restores to main's version
$ pv checkout experiment # ...and back to experiment's version
```

Switch branches and the working tree restores instantly. No copying files, no renaming, no "wait, which folder was the experiment in?" 🎯

When you're done, compare them against a dataset:

``` bash
$ pv ab main:summarize.md experiment:summarize.md -d cases.jsonl --show
A/B:  A=main:summarize.md  B=experiment:summarize.md  (3 cases)

[1/3] DIFF  differs
--- A vs B ---
-A You are a precise summarizer.
+B You are a concise summarizer.

  hello world
--- end ---

Summary: 0 identical, 3 differing (of 3)
```

Pure local. No model calls. No API keys. 🔒

One thing that annoyed me about existing prompt tooling: **everything wants to call a model.** Every eval run costs money. Every test sends data to OpenAI.

PromptVault takes a different stance: **it never calls a model.** It only renders templates and checks assertions.

``` bash
$ pv eval summarize.md --dataset cases.jsonl --show
Eval: summarize.md  (3 cases)

[1/3] PASS  contains "3 concise bullets"
--- rendered prompt ---
You are a precise summarizer.
...
--- end ---

Summary: 2/2 passed (100%)
```

You write a JSON Lines dataset, each line fills the prompt's `{{variables}}`

, and PromptVault renders + asserts. ✅

If you want to actually run the prompt through a model, pipe the rendered output to whatever runner you trust (curl, the OpenAI CLI, ollama, your own script).

This separates two concerns that existing tools conflate:

PromptVault does (1). You choose how to do (2).

For a "tiny git for prompts", it ended up with more than I planned:

`pv diff --stat`

for a one-line summary per file.`pv branch experiment`

, `pv merge experiment`

(fast-forward or three-way, with conflict markers)`pv tag v1.0`

, `pv revert v1.0`

`.pvignore`

`pv diff v1 v2`

compares any two commits/tags/branches`pv show HEAD:summarize.md`

reads any file at any ref`pv tui`

launches an interactive commit browser`pv push`

/ `pv pull`

syncs the vault to any git host as a backing store`--features run`

)`pv run`

against OpenAI/Anthropic/Ollama. `pv ab main:x experiment:x -d dataset.jsonl`

renders two versions against the same dataset and diffs themPromptVault is a tiny git. On `pv init`

it creates:

```
.pv/
├── HEAD              → "ref: refs/heads/main"
├── index.json        → staging area (path → blob hash)
├── objects/          → content-addressed store (SHA-256)
│   └── ab/cdef…      → "<type>\0<data>"  (blob / tree / commit)
└── refs/heads/main   → latest commit hash
```

Every prompt version is a **blob** addressed by the SHA-256 of `blob\0<content>`

. A **tree** maps paths to blobs. A **commit** points to a tree + parent + message. Identical content is stored once. Nothing ever leaves your machine unless you explicitly `pv push`

. 📦

It uses **Myers diff** for line-level changes (same algorithm as git), and the glob matcher for `.pvignore`

is a dynamic-programming implementation to avoid the exponential backtracking that naive recursive matchers hit on patterns like `*a*a*a*`

. 🧠

Three options:

```
# 1. Prebuilt binary (no Rust toolchain needed) 📥
#    Download from https://github.com/lululuhu/PromptVault/releases
#    Available for: Linux/macOS/Windows, x86_64 and aarch64

# 2. cargo 🦀
cargo install promptvault

# 3. From source 🔧
git clone https://github.com/lululuhu/PromptVault
cd PromptVault
cargo build --release
# binary: target/release/pv  (put it on your PATH)
```

Then, in any folder where you keep prompts:

```
pv init
```

That's it. You're versioning prompts. 🎉

A quick word on this, because I think it matters.

PromptVault is **local-first**. Everything lives in `.pv/`

on your machine. No account, no cloud, no telemetry, no analytics, no "phone home". The only network calls are the ones *you* explicitly make:

`pv push`

/ `pv pull`

to sync to a git remote you configured`pv run`

(opt-in feature) to send a rendered prompt to a model APIThe `pv run`

command reads API keys **only** from environment variables. Nothing is logged. Nothing is stored beyond the rendered prompt itself. 🔐

**Important caveat:** if your prompts contain secrets, PII, or confidential information, committing them to a vault stores that data on disk in plaintext (content-addressed, but unencrypted). Pushing to a remote sends it to that git host. Same rule as git — don't commit secrets you wouldn't commit to git. ⚠️

This is v0.2.0. The roadmap ahead:

`pv mergetool`

is planned)`{{var}}`

substitution)If you have opinions, the issue tracker is open. 🚪

If you've ever lost a good prompt to "v2_final_FINAL.txt" syndrome, give it a spin:

`cargo install promptvault`

⭐ Star it if it's useful.

🐛 Open issues if it's not.

I'm building this in the open and good ideas ship fast.

*PromptVault is MIT-licensed, written in Rust 🦀, and runs on Linux/macOS/Windows. The author has no affiliation with any AI lab.*
