https://aigrant.com/

Here is my application (selected questions only):

Provide a short summary of your product

Better code generation than Cursor

Describe your product in more detail

Run manicode in your terminal. Ask it to do any coding task. It will make changes to your files.

...and it will do a really good job. Why?

1. It has full access to read and write to your files, run terminal commands, and scrape the web

   It can: grab files it needs for context, edit multiple files at once (no copy-pasting), run the type checker, run tests, install dependencies, and search for documentation.

   These abilities are key to doing a good job and will only become more powerful as LLM's continue to level up.

2. It uses so-called "knowledge" files

   LLM's perform so much better with extra context!

   With Manicode, we've come up with this idea to check in knowledge.md files in any directory, and write down extra bits of context, like which 3 files you need to edit in order to create a new endpoint. Or which patterns are being deprecated and which should be used. Or which directories can import from other directories.

   Every codebase has lots of implicit knowledge like this that you have to impart to your engineers. Once written down, it makes Claude really fly! It's truly a night and day difference.

3. It's synchronous, and you can give feedback

   You're chatting with it. It takes ~30 seconds to get back to you and then you can tell it what you want to do next or what it did wrong.

   This keeps Manicode on track and aligned.

4. It learns

   The flow of using Manicode is:

   • Ask it to do something

   • If it fails, point out its error

   • Manicode fixes the error and automatically writes down how it can improve for next time in a knowledge file

   • You push the commit, and now Manicode has become even more capable when the next engineer runs it in the codebase.

   This is the magic loop that will make Manicode productive for experienced engineers in giant codebases.

5. We're unafraid to spend for better results

   We can use as many parallel API calls with as much context as we can to produce the best code, because we know that the alternative is human labor, which is much more expensive.

We're targeting the largest market for software engineers

• It's a tool for daily use by experts (not just junior engineers)

• It's for software maintainers (not just people starting new projects)

We're starting with a console application, because it's simple and has great distribution

• Every developer knows how to install new packages with npm or pip.

• Most developers already have the terminal accessible: as a pane in your vscode window, for example.

The timing is right

Claude Sonnet 3.5 passed some bar of coding competence, and the form factor of a fully capable agent that can change any file works now, whereas before you could only reliably edit one function at a time.

There is a moat after all

Handling every tech stack well, knowing when to run their tests and type check, integrating with git, linear, slack, and email, supporting database migrations, etc, etc, etc. You can build hundreds or thousands of special case prompt magic to improve things so that it always just magically works the first time. A startup arriving at this 6 months late wouldn't catch up.

Try it out!

> npm install -g manicode

> manicode

Intro video

Demo video

https://www.loom.com/share/2067e3ad5fdf4565905f6aeb8f13b215?sid=de0e9ad8-447a-485a-bcb3-71b8a5a43665

Addendum

I submitted this last night. The few things I forgot to include:

• The prototype is communicating with my server over websockets and so is significantly more complex than running a local script. It is already set up to work on any project immediately.

• I intend to charge $100 per month per user to get off the free plan (and some usage based fees after that if you use it a huge amount).

• Giving manicode full access to your files and terminal where it can run stuff without confirmation from the user sounds scary, but is actually not risky in reality, especially if you have version control. This quality of doing something that normal people think "goes too far" or seems unsafe is a correlated with good startup ideas, because it means fewer people are likely to have thought of it. (E.g. For Airbnb: You let random strangers sleep in your house? Or Manifold: You let anyone ask and judge the resolution of their own question?)

• Aug 12: Another contrarian thesis I forgot to write is that I think it's likely that using the best LLM on the market (e.g. Sonnet 3.5) will continue to outperform any specially trained model or fine-tuned model.
  The big LLM's train on a huge amount of code and have the largest budgets. Smaller but more specific coding models might sound fancier, but could well be a dead-end.
  Empirically, the better the LLM's get, the more they can just take natural language instructions through context that are far, far more configurable and can be iterated upon quickly. I think these custom instructions, embodied in the knowledge-file approach of Manicode, will outpace custom trained models for the next several years. If you want to make that bet, bet on Manicode!

They said they will let us know if we won by September 20th at the latest.