How to Track 'What Did Yulissa Say' Threads on Reddit

When a phrase like 'what did Yulissa say' starts bouncing around Reddit, it’s a leading indicator: of sentiment, jokes, misunderstandings, and emerging trends your team can’t ignore. Let’s walk through how to monitor and leverage it manually, with no‑code tools, and then with an AI computer agent (like Simular) so you can stop living in browser tabs and start acting on insights.

=== 1. Traditional/manual ways ===

1. Use Reddit’s built‑in search

• Go to https://www.reddit.com/search
• In the search bar, type: what did yulissa say
• Use filters:
  • Sort by: New (to catch fresh mentions)
  • Time: Past 24 hours or Past week
  • Toggle 'Posts' vs 'Communities and users' depending on what you need.
• Open promising threads in new tabs, read comments, and note key context in a doc or spreadsheet.
• For help with Reddit search basics, see Reddit Help Center: https://support.reddithelp.com/hc/en-us

1. Use Google site search

• In Google, search: "what did yulissa say" site:reddit.com
• Click Tools → set time range (e.g., Past week).
• Open the most relevant results and cross‑check context.
• This is especially useful when Reddit’s own search misses older or oddly formatted posts.

1. Manually follow key subreddits

• Identify subreddits where the phrase is likely to appear (e.g., fan communities, drama subs, industry subs related to your niche).
• Click Join on each subreddit.
• For each, set default sorting to New to track early mentions.
• Check daily, scanning titles and top comments for 'what did Yulissa say'.

1. Use Saved searches via bookmarks

• Run the Reddit search once with your preferred filters.
• Copy the URL and save it as a browser bookmark called 'Yulissa mentions – daily'.
• Each morning, click that bookmark, skim the new results, and update your notes.

1. Log insights in a simple sheet

• Create a spreadsheet with columns like: Date, Subreddit, Link, Exact quote, Sentiment (pos/neg/neutral), Notes, Potential action.
• Every time you see a new spin on 'what did Yulissa say', record it.
• Over time, this becomes a dataset you can mine for messaging, objections, or story angles.

Pros of manual:

• High context and nuance; you see the culture firsthand.
• Zero tooling overhead.

Cons of manual:

• Time‑consuming and easy to forget.
• You’ll inevitably miss mentions that happen while you’re off.

=== 2. No‑code methods with automation tools ===

Now, let’s reduce the daily grind without writing code. The key is to use officially supported integrations so you respect Reddit’s rules.

1. Zapier or Make (Integromat) with Reddit

• Tools: Zapier (https://zapier.com/apps/reddit/integrations) or Make (https://www.make.com/en/integrations/reddit) which both offer Reddit connectors built on the API.
• High‑level setup:

1. Create an account on your chosen tool.
2. Add Reddit as a connected app (you’ll be redirected to Reddit to authorize – this uses OAuth, not scraping).
3. Choose a trigger such as 'New post matching search' (wording may vary by platform).
4. Configure the search term as: what did yulissa say.
5. Add filters: only from specific subreddits, or only posts with minimum score.
6. Add an action:
   • Send a Slack message to a #social‑listening channel.
   • Append a row in Google Sheets.
   • Send an email summary to your team.

• Result: whenever someone posts with 'what did Yulissa say' in the title or body, you receive an automatic alert.

1. RSS + automation

• Some subreddits and searches can still be followed via RSS‑like feeds.
• For example, many tools let you monitor a subreddit’s new posts.
• Use a service like IFTTT or an RSS‑to‑Slack tool:

1. Add the subreddit feed you care about.
2. Configure keyword filters for 'Yulissa' or the full phrase.
3. Pipe matches into email, Slack, or a database.

• This is lighter‑weight than a full Zapier scenario but less granular.

1. Dashboarding your mentions

• Take the data your no‑code automation is pushing into Google Sheets or Airtable.
• Add columns for sentiment and priority.
• Build simple charts or views grouped by subreddit or week.
• Now your team can see 'what did Yulissa say' trending over time without touching Reddit daily.

Pros of no‑code:

• Always‑on monitoring with minimal engineering.
• Easy to update filters as the meme or quote mutates.

Cons of no‑code:

• Limited to what the integrations expose via the official Reddit API.
• Still requires you to open links and interpret context.

=== 3. Scaling with AI agents (Simular‑style) ===

This is where an AI computer agent, such as Simular Pro running on your desktop, changes the game. Instead of just collecting links, the agent behaves like a power user.

Method A: Research assistant agent
Pros:

• High context; reads full threads and comments.
• Outputs summaries your team can act on immediately.

How it can work:

• You define a workflow in Simular Pro:

1. Open your browser and go to https://www.reddit.com/search.
2. Enter 'what did yulissa say' and apply filters (time = past 24 hours, sort = new).
3. For each of the top N results:
   • Open the thread.
   • Scroll through comments, expanding best ones.
   • Copy the relevant quotes and surrounding context.
4. Paste findings into a Google Doc or Sheet.
5. Generate a summary section: 'What people mean when they say this', 'Sentiment today', 'Risks and opportunities for our brand'.
6. Post the summary to Slack or email via your usual tools.

• Because Simular combines LLM reasoning with symbolic control, every click, scroll, and copy‑paste is reliable and visible. You see exactly what the agent did.

Method B: Narrative‑to‑action agent
Pros:

• Bridges Reddit chatter with campaigns and sales.

How it can work:

• Nightly, your agent:

1. Runs the same Reddit search and collects top posts.
2. Classifies each mention: meme, complaint, testimonial, confusion.
3. For each class, drafts:
   • A social media response play (what you’d post on X, TikTok, etc.).
   • A one‑paragraph 'voice of customer' insight for your sales or CS teams.
4. Saves drafts to a Notion or Google Doc folder for human review.

• You wake up to near‑publish‑ready material derived from 'what did Yulissa say' without spending an hour reading threads.

Method C: Multi‑step enrichment agent
Pros:

• Connects Reddit signals to your CRM or prospecting.

How it can work:

• The agent:

1. Monitors subreddits your ICP hangs out in.
2. When 'what did Yulissa say' appears in a high‑value context, captures usernames (without violating privacy or platform rules).
3. Enriches those profiles via your existing tools (e.g., web search) to understand segments and pain points.
4. Writes segment‑specific messaging ideas for your team.

Cons of AI‑agent scale:

• You must design workflows that respect Reddit’s terms and 'prove your humanity' measures.
• Agents need initial setup and guardrails.

The net outcome: manual and no‑code flows help you listen. An AI computer agent turns that listening into continuously updated narratives and ready‑to‑use assets, so the next time someone asks 'what did Yulissa say on Reddit?', you have data, story, and response queued up.