# Research

#### Responsibilities

* Find yield-maximizing investments/strategies in the Solana ecosystem.
* Produce content for the alpha chat.

#### What we are looking for

* NFT mint Tracking.
* People who don't need to be told what to do, who can perform self-directed research and turn it into critical and original analysis.
* People who prefer to be given a project to look into and summarize relevant information in an easily digestible form.
* Fundamental analysis, technical analysis, finding alpha early – really anything that helps people make money, keep their money, and find communities they gel with.
* Ability to express ideas clearly.

#### Long-term goals

* Find ways to show those in class B and lower (including those who aren't Grape members) what they are missing out on.
* Increase the number of people who join Grape for the research.
* Implement a way for people to request researchers to perform research on specific projects.

*A pre-requisite for the acquisition of any skill role is being a Great Ape.*

***Application Steps***

**Step 1: Share your Talent**

Start by sharing your talent and particular research focus in a short paragraph here, in [<mark style="color:purple;">**#share-your-talent**</mark>](https://discord.gg/Kj6CJKh6H2) on [<mark style="color:purple;">**Discord**</mark>](https://discord.gg/grapedao), and express your interest in joining the Researcher team.

**Step 2: Share your Alpha**

Start sharing your Solana Alpha content over at [<mark style="color:purple;">**#grape-chat**</mark>](https://discord.gg/amTprhcNn9) on [<mark style="color:purple;">**Discord**</mark>](https://discord.gg/grapedao) to get noticed.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.grapes.network/grape-network/grape-subdaos/subdao-units/research.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.