> ## Documentation Index
> Fetch the complete documentation index at: https://docs.remyx.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Set up your discovery feed
> Turn your project's extracted history into a daily discovery digest of papers and repos ranked against your team's actual work.
*Setup phase ยท \~3 minutes*
A generic AI discovery feed surfaces what's hot. A discovery feed grounded in your project surfaces what's relevant to the directions your team has actually shipped, ranked against real history.
In this tutorial, you'll wire up that feed using the experiment history from the previous tutorial so the recommendations Remyx delivers are scoped to your work.
**Prerequisites.** You've completed [Create your project](/tutorials/get-started/create-your-project). The project has finished cold-start extraction.
## What a discovery feed gives you
A **research interest** is a saved configuration that tells Remyx what kinds of papers, repos, models, and datasets you want to hear about. The system runs daily and surfaces the top results that match, ranked against the experiments your project has already shipped.
In practice, this means:
* A paper about a new depth estimator gets ranked higher if your project has been swapping depth estimators.
* A retrieval rerank technique gets ranked higher if your project's history shows retrieval-quality experiments.
* Off-direction work (an unrelated benchmark, a refactor framework) gets pushed down or filtered out.
Setting this up takes one minute.
## Create the interest from your project
If you checked **Create a research interest from this project** during the wizard in the previous tutorial, an interest already exists for this project. Skip to the curation step below.
Otherwise:
1. Open **Feed** in the sidebar and click **+ New Interest** in the page header.
2. Pick the **From project** tab (it's the default).
3. Select the project you created in the previous tutorial.
4. Save.
The interest pre-fills with every experiment in the project. A "Preparing recommendations..." overlay runs while Remyx assembles the context, then a refresh kicks off automatically and the first set of recommendations populates as soon as the build completes.
## Curate the experiment list
The pre-filled list is a checklist. The experiments you keep checked are the signal Remyx uses to rank papers. The experiments you uncheck become noise to ignore.
Keep:
* Model swaps and architecture changes
* Evaluation method changes (new benchmarks, new metrics)
* Routing or policy changes
* Prompt-engineering experiments
* Data-pipeline-stage upgrades
Uncheck:
* Pure refactors (file moves, type-hint cleanups)
* Dependency bumps
* Security patches
* Infrastructure-only changes (CI, build, packaging)
These don't reflect direction-setting decisions, so leaving them in the context dilutes the signal.
The experiments you keep don't just filter topics โ they train the ranking. Remyx feeds the curated history into the recommendation ranker and fits a preference model over it, so the feed leans toward the methodological directions you've actually shipped. See [How recommendations are ranked](/platform/discover/feed#how-recommendations-are-ranked).
Save the curated list. The refresh re-fires.
## Set the daily count
In the interest's settings, choose how many recommendations you want delivered each day. You can update this value as needed.
## Optional: let the feed open PRs for you
If this interest is backed by a GitHub repo, you can go a step further than a digest and have Remyx open a **reviewable draft PR** for the most implementable recommendation on a schedule โ the cold-start reading and scaffolding done for you, with you still reviewing and merging. This is covered in [Automated discovery PRs](/platform/discover/outrider).
Turn the feed into scheduled draft PRs you review (Outrider)
## Recap
You now have:
* A research interest that knows your project's direction
* A daily count for how much research Remyx surfaces
* A feedback loop where curating the experiment list sharpens future recommendations
Once the first batch of recommendations lands, [Scope an experiment from a recommendation](/tutorials/get-started/scope-an-experiment) shows how to turn one of them into a structured experiment.
## Next
Lock in the eval template and decision policy that future variants will be judged against.
Turn recommendations into scheduled draft PRs you review
Full series arc
Save the curated list. The refresh re-fires.
## Set the daily count
In the interest's settings, choose how many recommendations you want delivered each day. You can update this value as needed.
## Optional: let the feed open PRs for you
If this interest is backed by a GitHub repo, you can go a step further than a digest and have Remyx open a **reviewable draft PR** for the most implementable recommendation on a schedule โ the cold-start reading and scaffolding done for you, with you still reviewing and merging. This is covered in [Automated discovery PRs](/platform/discover/outrider).