debian-mirror-gitlab/.gitlab/issue_templates/AI Project Proposal.md

<!-- AI Project Proposal title format: 🤖 [AI Proposal] {`Need/outcome` } + {`Beneficiary`} + {`Job/Small Job`}

The title should be something that is easily understood that quickly communicates the intent of the project allowing team members to easily understand and recognize the expected work that will be done.

A proposal title should combine the beneficiary of the feature/UI, the job it will allow them to accomplish, and their expected outcome when the work is delivered. Well-defined statements are concise without sacrificing the substance of the proposal so that anyone can understand it at a glance. (e.g.🤖 {Reduce the effort} + {for security teams} + {when prioritizing business-critical risks in their assets}) -->

# [Experiment](https://docs.gitlab.com/ee/policy/alpha-beta-support.html#experiment)

##  Problem to be solved

### User problem
_What user problem will this solve?_

### Solution hypothesis
_Why do you believe this AI solution is a good way to solve this problem?_

### Assumption
_What assumptions are you making about this problem and the solution?_

### Personas
_What [personas](https://about.gitlab.com/handbook/product/personas/#list-of-user-personas) have this problem, who is the intended user?_

## Proposal
<!-- Use this section to explain the proposed changes, including details around usage and business drivers. -->

### Success
_How will you measure whether this experiment is a success?_

# [General Availability](https://docs.gitlab.com/ee/policy/alpha-beta-support.html#generally-available-ga)

## Main Job story
_What job to be done will this solve?_
<!-- What is the [Main Job story](https://about.gitlab.com/handbook/product/ux/jobs-to-be-done/#how-to-write-a-jtbd) that this proposal was derived from? (e.g. When I am on triage rotation, I want to address all the business-critical risks in my assets, So I can minimize the likelihood of my organization being compromised by a security breach.) -->

### Proposal updates/additions
<!-- Use this section to explain any changes or updates to the original proposal, including details around usage, business drivers, and reasonings that drove the updates/additions. -->

### Problem validation
_What validation exists that customers have this problem?_

### Business objective
_What business objective will be achieved with this proposal?_
<!-- Objectives (from a business point of view) that will be achieved upon completion. (For instance, Increase engagement by making the experience efficient while reducing the chances of users overlooking high-priority items. -->

### Confidence
_Has this proposal been derived from research?_
<!-- How well do we understand the user's problem and their need? Refer to https://about.gitlab.com/handbook/product/ux/product-design/ux-roadmaps/#confidence to assess confidence -->

| Confidence        | Research                       |
| ----------------- | ------------------------------ |
| [High/Medium/Low] | [research/insight issue](Link) |

### Requirements
_What tasks or actions should the user be capable of performing with this feature?_
<!-- Requirements can be taken from existing features or design issues used to build this proposal. Any related issues should be linked with this issue in the Feature/solution issues section below. They are more granular validated needs, goals, and additional details that the proposal encompasses. -->

> ⚠️ Related feature and research issues should be linked in the related issues section (Delete this line when this is done)

#### The user needs to be able to:
- ...
- ...
- ...

## Checklist

### Experiment

<details>
<summary> Issue information </summary>

- [ ] Add information to the issue body about:
  - [ ] The user problem being solved
  - [ ] Your assumptions
  - [ ] Who it's for, list of personas impacted
  - [ ] Your proposal
- [ ] Add relevant designs to the Design Management area of the issue if available
- [ ] Ensure this issue has the ~wg-ai-integration label to ensure visibility to various teams working on this

</details>

### General Availability

<details>
<summary>Issue information</summary>

- [ ] Add information to the issue body about:
  - [ ] Your proposal
  - [ ]  The Job Statement it's expected to satisfy
  - [ ] Details about the user problem and provide any research or problem validation
    - [ ] List the personas impacted by the proposal.
- [ ] Add all relevant solution validation issues to the Linked items section that shows this proposal will solve the customer problem, or details explaining why it's not possible to provide that validation.
- [ ] Add relevant designs to the Design Management area of the issue.
- [ ] You have adhered to our [Definition of Done](https://docs.gitlab.com/ee/development/contributing/merge_request_workflow.html#definition-of-done) standards
- [ ] Ensure this issue has the ~wg-ai-integration label to ensure visibility to various teams working on this

</details>

<details>
<summary>Technical needs</summary>

- [ ] [Operational Requirements Review - Checklist - #note_1337519985](https://gitlab.com/gitlab-org/gitlab/-/issues/403859#note_1337519985)

1. **Work estimate and skills needs to build an ML viable feature:** To build any ML feature depending on the work, there are many personas that contribute including, Data Scientist, NLP engineer, ML Engineer, MLOps Engineer, ML Infra engineers, and Fullstack engineer to integrate the ML Services with Gitlab. Post-prototype we would assess the skills needed to build a production-grade ML feature for the prototype
2. **Data Limitation:** We would like to upfront validate if we have viable data for the feature including whether we can use the DataOps pipeline of ModelOps or create a custom one. We would want to understand the training data, test data, and feedback data to dial up the accuracy and the limitations of the data.
3. **Model Limitation:** We would want to understand if we can use an open-source pre-trained model, tune and customize it or start a  model from scratch as well. Further, we would asses based on the ModelOps model evaluation framework which would be the right model to use based on the use case.
4. **Cost, Scalability, Reliability:** We would want to estimate the cost of hosting, serving, inference of the model, and the full end-to-end infrastructure including monitoring and observability.
5. **Legal and Ethical Framework:** We would want to align with legal and ethical framework like any other ModelOps features to cover across the nine principles of responsible ML and any legal support needed.

</details>

<details>
<summary>Dependency needs</summary>

- [ ] [Operational Requirements Review - Checklist - #note_1337519985](https://gitlab.com/gitlab-org/gitlab/-/issues/403859#note_1337519985)

</details>

<details>
<summary>Legal needs</summary>

- [ ] TBD

</details>

## Additional resources
- If you'd like help with technical validation, or would like to discuss UX considerations for AI mention the AI Assisted group using `@gitlab-org/modelops/applied-ml`.
- Read about our [AI Integration strategy](https://internal-handbook.gitlab.io/handbook/product/ai-strategy/ai-integration-effort/)
- Slack channels
    - `#wg_ai_integration` - Slack channel for the working group and the high level alignment on getting AI ready for Production (Development, Product, UX, Legal, etc.) But from the other channels fell free to reach out and post progress here
    - `#ai_integration_dev_lobby` - Channel for all implementation related topics and discussions of actual AI features (e.g. explain the code)
    - `#ai_enablement_team` - Channel for the AI Enablement Team which is building the base for all features (experimentation API, Abstraction Layer, Embeddings, etc.)


/label ~wg-ai-integration
/cc @tmccaslin @hbenson @wayne @pedroms @jmandell
/confidential

[Make change to this template](https://gitlab.com/gitlab-org/gitlab/-/blob/master/.gitlab/issue_templates/AI%20Project%20Proposal.md)