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In our previous blog (AI-Powered Market Research: Mining Reddit for Unsolved Problems ), we explored why Reddit is one of the most honest and valuable sources of market research available today. Unlike surveys or polished industry reports, Reddit captures unfiltered human frustration, real-world struggles, and unmet needs shared openly by users across industries and geographies. It is where people speak candidly about what is broken, missing, or inefficient in their daily work and lives.
Now we will move from observation to execution. In this blog, we introduce an AI-powered Problem Discovery Agent. system designed to extract real business opportunities directly from Reddit discussions. Instead of guessing what founders should build, this agent identifies recurring, unsolved problems hidden inside thousands of human-written comments.
Let’s See What We’re Actually Building
We will build this agent using minimal infrastructure: no scraping frameworks, no cloud APIs, and no complex pipelines. The entire system runs on Python, Reddit JSON, and a local LLM, making it lightweight, transparent, and easy to experiment with. The focus is not on technical complexity, but on intelligent signal extraction from real conversations.
At its core, the agent performs four simple but powerful tasks: it accepts any Reddit thread URL, converts it into structured JSON, extracts all human-written comments, and uses an LLM to surface recurring, unsolved business problems. This is not traditional sentiment analysis we are not measuring emotions. We are discovering opportunities. By turning raw internet conversations into actionable startup ideas, this agent helps founders build based on real demand, not assumptions.
Setup And Implementation Process
You only need three things to get started:
Python (3.10+) : Download python & install it.
Verify with:python --versionOllama : It is a lightweight tool that lets you run large language models locally on your own machine with simple terminal commands.
llama3 : It is an open-source Meta large language model available through Ollama, optimized for general-purpose reasoning, instruction following, and local AI development workflows.
ollama pull llama3Python Dependency
pip install requestsThat’s it no API keys, no accounts, no complexity.
Agent Implementation
Below is the initial working version of the Reddit Market Miner Agent. You can use the following code directly in your IDE to run, test, or extend it further.
import requests
import subprocess
import sys
def run_reddit_agent():
# 1. Dynamic Input: This allows you to paste any link in the terminal
print("--- 🤖 Reddit Market Miner Agent 0.1 ---")
url = input("🔗 Paste the Reddit Thread URL: ").strip()
if not url:
print("❌ Error: No URL provided.")
return
# 2. Formatting the URL correctly
if not url.endswith('.json'):
url = url.rstrip('/') + ".json"
# 3. Realistic User-Agent to bypass blocks
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36'
}
print(f"🚀 Connecting to Reddit...")
try:
response = requests.get(url, headers=headers)
if response.status_code != 200:
print(f"❌ Failed to get data. Status Code: {response.status_code}")
return
data = response.json()
# 4. Extracting comments (The Flattening Layer)
comments = []
def get_text(obj):
if isinstance(obj, dict):
if 'body' in obj: comments.append(obj['body'])
for k, v in obj.items(): get_text(v)
elif isinstance(obj, list):
for i in obj: get_text(i)
# Reddit threads store comments in the second element [1]
get_text(data[1])
if not comments:
print("⚠️ No comments found. Ensure it's a public post.")
return
print(f"🔎 Mining {len(comments)} comments for unsolved problems...")
# 5. Advanced Prompting: Identifying 'Unsolved' Problems
# We tell the AI to look for "Hacks" and "Workarounds"
prompt = f"""
Act as a Venture Capital Analyst. Analyze the following user comments to find UNSOLVED problems.
Look specifically for:
1. Complaints about existing tools being too complex or expensive.
2. Users describing 'hacks' or using manual spreadsheets to solve a problem.
3. Frustrations that multiple people agree with.
List 10 specific business problems that appear to be unsolved or poorly addressed:
---
DATA:
""" + "\n---\n".join(comments[:40])
# 6. Feeding to local Ollama
process = subprocess.run(
['ollama', 'run', 'llama3', prompt],
capture_output=True, text=True, encoding='utf-8'
)
print("\n✅ AI MARKET ANALYSIS REPORT:\n")
print(process.stdout)
except Exception as e:
print(f"❌ Error: {e}")
if __name__ == "__main__":
run_reddit_agent()Example
A Reddit thread URL is provided as the primary input to the agent for processing.
Paste the Reddit Thread URL: https://www.reddit.com/r/interestingasfuck/comments/1nw2100/an_ai_company_just_spent_1_million_on_print/Output:
As a Venture Capital Analyst, I've identified 10 specific business problems that appear to be unsolved or poorly addressed:
High cost of advertising: Users are complaining about the high costs associated with large-scale campaigns, which can be prohibitive for many businesses.
Lack of transparency in ad pricing: The comments highlight a lack of understanding and misinformation around the true cost of advertising, leading to inflated expectations.
Over-reliance on manual spreadsheets: Users are still using manual spreadsheets to track data, indicating a need for more efficient and automated solutions.
These unsolved problems present opportunities for entrepreneurs and startups to develop innovative solutions that address the needs of businesses and consumers alike.
Note : This represents only a brief summary of the generated output. When you execute the script, the system will produce a complete and detailed AI-driven analysis based on the full set of extracted Reddit comments.
Advancing The Agent Beyond v0.1
This version is just v0.1, and its real power emerges through incremental improvements. The first step is scaling: looping through multiple Reddit threads and aggregating comments across posts to capture a broader and more reliable set of signals.
Next comes intelligence layering clustering similar complaints, ranking them by frequency, and adding pain scoring by detecting emotional urgency. Finally, raw problems are transformed into startup-ready ideas by mapping each issue to an ideal customer profile and willingness to pay. Each upgrade compounds insight and moves closer to MVP-ready opportunities.
key Takeaway
This agent fundamentally changes how founders approach building products. Instead of asking, “What should I build?” the better question becomes, “What are people already begging to be fixed?” Reddit provides brutally honest signals from real users, AI listens at scale, and founders gain clear direction without relying on assumptions or guesswork.
This is not a growth hack or a passing trend. It’s a new default for market research. Founders who adopt this approach in 2026 won’t chase problems they’ll systematically extract them from real conversations.
By turning unfiltered Reddit conversations into structured business insights, the Reddit Market Miner Agent enables founders to discover real, unsolved problems backed by authentic user demand. This shifts product building from guesswork to evidence-driven opportunity discovery, creating a smarter default for modern market research.
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