ArticlePerplexity CometIdea Generation

I Used Perplexity Comet to Find Investment Ideas

By Felipe SinisterraJuly 30, 20256 min read
I Used Perplexity Comet to Find Investment Ideas

You’re used to AI that can answer your questions. But what about AI that can actually do work for you?

Over the past month, the major labs have kicked off a not-so-quiet arms race around agentic capabilities. One standout area: agentic browsers. Imagine a browser that autonomously scrolls, clicks, reads, and acts, handling all the boring stuff you’d rather delegate.

Perplexity recently released Comet, their new AI-enabled browser. After using it for a few weeks, it’s clear this isn’t just another gimmick. Comet feels like a tireless intern who doesn’t just give you answers; it actually does a lot of the legwork. See it in action.


Why Agentic Browsers Matter to Investors

Comet transforms your browser into an always-on, AI-powered research analyst. And this is just day one; it’s the worst version of Comet you’ll ever use. Here’s a glimpse of what’s possible right now:

  • Rapid summarization: Articles, podcasts, videos-just point and summarize. (e.g., “Summarize this Acquired podcast in 10 actionable bullets.”)
  • Interacting with SEC filings: Open up a 10-K, 10-Q, or earnings call transcript and directly query Comet’s Assistant to extract key points. (e.g., “Extract and summarize Figma’s unit economics from their S-1 in a table.”)
  • Real-time information parsing: Autonomously pull guidance from multiple central banks’ websites simultaneously. (e.g., “Summarize the current monetary policy stance from the central banks of US, Canada, Europe, and India.”)
  • Sentiment mining & idea generation: Harvest and analyze social sentiment from Reddit, Twitter, and other platforms, ranking ideas by their signal strength.
  • Native task execution: Automate structured web tasks (e.g., “Download NVIDIA’s latest investor presentation from their investor relations website.”)
  • Email management: Sort, summarize, and triage your inbox backlog.

Bottom line: dramatically faster research workflows. Better analysis. Smarter trades. Higher returns.


Example: Extracting High-Signal Trade Ideas from Reddit

Remember GameStop in early 2021? Reddit’s r/WallStreetBets turned retail investors into a powerful market-moving force. Just ask Melvin Capital. While institutional investors typically have access to higher-quality sources, it’s become undeniable that retail moves markets. Even Elon was adding to the hype.

Enter Comet. Here’s how you scrape r/stocks, surface the past week’s most actionable ideas, and rank tickers by signal-all in 90 seconds or less. Comet generates a structured table directly in its assistant panel. Watch as Comet takes control of your screen and clicks on the appropriate fields. It blew me away the first few times.


Using Comet in Action

Step 1: Navigate to r/stocks

Step 2: Open up the Comet Assistant

Note that first you need to download the Perplexity Comet browser. Then click on Assistant at the top right.

Step 3: Copy-paste the prompt below

(Missed last week’s newsletter explaining the prompt structure? Check the ROOCS framework.)

ROLE
You are a former hedge-fund analyst turned elite retail trader specializing in sourcing actionable, high-signal trade ideas from Reddit and other crowd-driven channels.
OBJECTIVE
Analyze r/stocks posts from the past 7 days, identify mentioned tickers, score each post by Upvotes × Author Karma, and produce the top five trade setups.
OUTPUT
Generate a structured Markdown table:
- Rank
- Ticker
- Company
- Sector
- Confidence Score (0–100; based on upvotes, karma, evidence strength, catalyst clarity)
- Sentiment (Bullish/Bearish/Unclear)
- Catalyst (type + known/expected date window)
- Thesis: 2–3 sentences explaining what’s the trade, why now, and relevant filing/news
- Evidence Links: 1+ credible external source + original Reddit post URL
Include a concise 50–100 word introduction summarizing key themes and overall signal reliability this week.
CONTEXT
- Audience: institutional PMs and sophisticated retail investors hunting early alpha.
- Tone: Direct, zero hype.
- Filters: Minimum 25 upvotes, author karma >500, ticker price >$2.
- Data sources: Use only Reddit page HTML and JSON.
STEPS
1. Collect top posts and top-level comments from r/WallStreetBets over the past week.
2. Extract tickers and company names; validate against US listings. Separate multi-ticker posts into distinct trade ideas.
3. Apply filters for minimum upvotes, author karma threshold, and price floor.
4. Identify explicit catalysts: earnings reports, guidance updates, M&A, product launches, insider or congressional trades, significant contracts, buybacks/dividends, short-squeeze mentions.
5. Collect supporting evidence links from posts/comments; classify links as filings, reputable news outlets, or blogs/opinions.
6. Calculate sentiment and confidence scores (0–100) based on engagement, author credibility, evidence strength, and catalyst clarity.
7. Cluster duplicate tickers across threads; retain only the highest-confidence instance.
8. Generate final Markdown table and brief intro; await user review.

Step 4: Watch Comet autonomously scroll, parse posts, and rank ideas

This is Comet autonomously navigating. I am not touching the mouse, I promise.


What’s Next: Chaining AI Tools Together

Now that you’ve harvested a list of high-potential ideas, what’s next?

Two ways to take this deeper with agentic tools like Comet:

  1. Full research workflows: Instruct Comet to pull deeper diligence: SEC filings, investor decks, credible news articles to refine and stress-test trade ideas further. For example, you may instruct it to first find ideas, and then create investment memos for each idea
  2. Multi-tool integrations: Comet’s UI is great for controlling browser tasks but limited in visual output. Have Comet send data to Google Sheets, or use more sophisticated tools (Claude, ChatGPT) to build detailed dashboards or visualizations for clearer analysis. For example, after running the provided prompt, you can try asking Comet Assistant to open up a new Claude window and code up a dashboard to better visualize the data Comet collected

The key is thinking of AI as steps in a chain, using each tool for what it’s best at.


Bottom Line

Chatbots answered questions. Agentic browsers actually execute actions, transforming tedious scrolling, clicking, and data collection into streamlined, automated workflows.

Right now, tools like Comet are exceptional interns; they still require clear instructions and oversight. But they’re evolving fast. The major AI labs (including OpenAI) are all sprinting in this direction, so expect capabilities to leap forward in the months ahead.

More experiments are coming soon. Stay tuned. Until then, happy idea hunting.

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