Reddit Lead Generation AI Agent

What This Agent Does

This intelligent automation workflow monitors the web for specific keyword mentions using F5Bot alerts and automatically qualifies potential leads using AI. When your target keywords appear in online discussions, forums, or social media, the agent captures these mentions, processes each one individually, and uses Claude AI to evaluate whether they represent genuine business opportunities worth pursuing.

Key benefits include:

• Save 10+ hours per week by eliminating manual keyword monitoring and lead research
• Never miss an opportunity with automated 24/7 monitoring of your target keywords
• Focus on quality leads only as AI pre-qualifies each mention before it reaches your inbox
• Respond faster than competitors by getting instant notifications when relevant discussions happen

Perfect use cases:

• SaaS companies monitoring product category discussions to find prospects actively seeking solutions
• Agencies tracking client industry keywords to identify potential customers asking for help
• Developers monitoring technology-specific forums where their tools could provide value
• Consultants finding businesses discussing problems they can solve

Who Is It For

This workflow is ideal for sales teams, marketers, and business development professionals who want to practice social listening at scale without drowning in irrelevant mentions. If you're currently manually checking Reddit, forums, or social media for people discussing topics related to your product or service, this automation will transform your lead generation process.

It's particularly valuable for:

• Solo entrepreneurs and small teams who need to maximize their limited time while staying on top of opportunities
• B2B companies with clearly defined buyer personas and specific pain points to monitor
• Service providers who can offer immediate value when prospects express needs publicly
• Growth hackers implementing community-driven acquisition strategies

You should be comfortable defining your ideal customer profile and the keywords that indicate buying intent, as the AI qualification depends on clear criteria you'll establish.

Required Integrations

RSS Integration

Why it's needed: F5Bot delivers keyword alerts via RSS feeds, which this workflow polls at regular intervals to capture new mentions. The RSS integration is the data source that feeds your entire lead qualification pipeline.

Setup steps:

1. Create your F5Bot account:

   • Visit https://f5bot.com
   • Enter your email address (no password required)
   • Verify your email through the confirmation link

2. Configure keyword alerts:

   • Add each keyword or phrase you want to monitor (e.g., "looking for project management software", "need help with email marketing")
   • F5Bot will monitor Reddit, Hacker News, and Lobsters for these terms
   • You'll receive an RSS feed URL for each keyword

3. Obtain your RSS feed URL:

   • Check your email for the F5Bot confirmation
   • Copy the unique RSS feed URL provided (format: https://f5bot.com/feed/[unique-id])
   • This URL updates automatically when new mentions appear

4. Configure in TaskAGI:

   • Open the "F5Bot Keyword Alerts" node in your workflow
   • Paste your RSS feed URL into the Feed URL parameter
   • Set the Poll Interval to match your Schedule Interval Trigger (recommended: 15-60 minutes)
   • Enable Deduplicate Items to prevent processing the same mention multiple times
   • Save the node configuration

Pro tip: Create separate F5Bot alerts for different keyword categories, then duplicate this workflow for each feed to maintain organized lead tracking.

Configuration Steps

Step 1: Schedule Interval Trigger Configuration

This node determines how frequently your workflow checks for new keyword mentions.

• Set Interval to 30 and Unit to minutes for balanced monitoring (checks twice per hour)
• For high-priority keywords, reduce to 15 minutes
• For broader monitoring with lower urgency, increase to 60 minutes or 2 hours
• Consider your F5Bot alert volume—higher mention frequency requires more frequent checks

Step 2: F5Bot Keyword Alerts (RSS Poll) Setup

Configure the RSS polling node to retrieve new mentions:

• Feed URL: Paste your F5Bot RSS feed URL from the integration setup
• Max Items: Set to 10 to process up to 10 new mentions per check (adjust based on your typical volume)
• Deduplicate: Enable this to track which items you've already processed
• The node outputs an array of new mentions, each containing title, link, description, and publication date

Step 3: Process Each Match (Loop) Configuration

This loop node processes each RSS item individually:

• Input Array: Map to the output from the RSS node: {{$node["F5Bot Keyword Alerts"].data}}
• Loop Mode: Set to "Process Each Item" to handle mentions one at a time
• The loop creates a $loop.item variable containing the current mention's details
• Each iteration passes through the AI qualification before moving to the next mention

Step 4: AI Lead Qualifier Agent Setup

This is where the intelligence happens. Configure Claude to evaluate each mention:

Model Configuration:

• Model: claude-haiku-4-5 (fast and cost-effective for qualification tasks)
• Temperature: 0.3 (lower temperature for consistent, focused evaluation)
• Max Tokens: 500 (sufficient for qualification analysis)

System Prompt (customize for your business):

You are a lead qualification specialist. Evaluate whether social media mentions represent genuine business opportunities.

Analyze each mention for:
- Clear expression of need or pain point
- Indication of buying intent or timeline
- Appropriate company size/profile
- Relevance to [YOUR PRODUCT/SERVICE]

Respond with JSON:
{
  "qualified": true/false,
  "score": 1-10,
  "reason": "brief explanation",
  "urgency": "high/medium/low"
}

User Prompt (maps mention data to AI):

Evaluate this mention:

Title: {{$loop.item.title}}
Content: {{$loop.item.description}}
Source: {{$loop.item.link}}
Date: {{$loop.item.pubDate}}

Is this a qualified lead for our business?

Output Parsing: Enable "Parse JSON Response" so the AI's structured output can be used in the next step

Step 5: If Condition Configuration

This decision node filters qualified leads from noise:

• Condition Type: "Expression"
• Expression: {{$node["AI Lead Qualifier Agent"].json.qualified === true}}
• Alternative check: {{$node["AI Lead Qualifier Agent"].json.score >= 7}} (for score-based filtering)
• Qualified leads follow the True Path, unqualified mentions follow the False Path

Step 6: Action Nodes (True/False Paths)

True Path (qualified leads): Add your desired action nodes here:

• Send notification via Slack/email with mention details and AI analysis
• Create CRM record with lead information
• Add to outreach sequence
• Post to team dashboard

False Path (No Operation): Currently does nothing with unqualified mentions, but you could:

• Log to a separate sheet for pattern analysis
• Archive for future review
• Track rejection reasons for keyword refinement

Testing Your Agent

Initial Test Run

1. Manual trigger test:

   • Click the "Test Workflow" button in the TaskAGI editor
   • This executes immediately regardless of schedule
   • Watch each node execute in sequence

2. Verify RSS polling:

   • Check that the F5Bot node returns recent mentions
   • Confirm the data structure includes title, description, link, and date
   • If empty, verify your RSS feed URL and that F5Bot has captured mentions

3. Validate loop processing:

   • Expand the "Process Each Match" node execution
   • Confirm it creates separate iterations for each mention
   • Verify $loop.item contains the expected data structure

4. Review AI qualification:

   • Examine the AI agent's JSON responses for each mention
   • Check that qualification logic aligns with your criteria
   • Adjust the system prompt if scoring seems too lenient or strict

5. Confirm conditional routing:

   • Verify qualified leads flow to the True Path
   • Check that unqualified mentions route to False Path
   • Review the qualification threshold accuracy

Success Indicators

✅ RSS node retrieves 1+ new items (if mentions exist)
✅ Loop node shows multiple iterations matching item count
✅ AI agent returns valid JSON with all required fields
✅ If condition correctly routes based on qualification status
✅ No error messages appear in any node execution logs

Ongoing Monitoring

After deployment, check your workflow execution history weekly:

• Review qualification accuracy (are good leads being filtered out?)
• Monitor false positive rate (are poor leads getting through?)
• Adjust AI prompt based on patterns in misclassified mentions

Troubleshooting

"RSS feed returns no items"

Causes:

• F5Bot hasn't detected any new mentions since last check
• RSS feed URL is incorrect or expired
• Deduplication is filtering all items as "already seen"

Solutions:

• Verify the RSS URL in your browser—it should display XML content
• Temporarily disable deduplication to see all items
• Check F5Bot email alerts to confirm mentions are being detected
• Reduce the polling interval if mentions are being captured between checks

"AI agent returns invalid JSON"

Causes:

• Response includes explanatory text outside JSON structure
• Model temperature too high causing creative formatting
• Token limit too low, cutting off response

Solutions:

• Add to system prompt: "Respond ONLY with valid JSON, no additional text"
• Reduce temperature to 0.1-0.3 for more consistent formatting
• Increase max tokens to 500-1000
• Enable "Extract JSON" option in node settings if available

"All mentions marked as unqualified"

Causes:

• AI qualification criteria too strict
• System prompt doesn't align with actual mention content
• Keywords capturing irrelevant discussions

Solutions:

• Review 5-10 actual mentions to understand content patterns
• Adjust system prompt to match the language and context of real mentions
• Refine F5Bot keywords to be more specific (e.g., "need CRM software" vs. just "CRM")
• Lower qualification threshold temporarily to see borderline cases

"Loop processing times out"

Causes:

• Too many items being processed in single execution
• AI agent taking too long per item
• Workflow timeout limits exceeded

Solutions:

• Reduce "Max Items" in RSS node to 5-10
• Increase polling frequency so fewer items accumulate
• Switch to faster AI model (Haiku is already optimized)
• Implement batch processing with smaller loops

"Duplicate leads being created"

Causes:

• RSS deduplication not enabled
• Same mention appearing in multiple F5Bot feeds
• Workflow running multiple times simultaneously

Solutions:

• Enable "Deduplicate Items" in RSS node settings
• Add unique identifier tracking (use mention URL as key)
• Implement additional deduplication in your action nodes
• Ensure schedule trigger doesn't overlap (execution time < interval time)

Next Steps

After Successful Setup

1. Deploy to production: Activate the schedule trigger and let it run for 48 hours
2. Monitor initial results: Review the first 20-30 qualified leads to validate accuracy
3. Refine qualification criteria: Adjust the AI prompt based on real-world performance
4. Add action nodes: Connect your CRM, notification tools, or outreach platforms to the True Path

Optimization Suggestions

Improve qualification accuracy:

• Add more context to the AI prompt about your ideal customer profile
• Include examples of qualified vs. unqualified mentions in the system prompt
• Implement multi-tier scoring (hot/warm/cold) instead of binary qualified/unqualified
• Track conversion rates from qualified leads to actual customers and refine criteria

Scale your monitoring:

• Create separate workflows for different keyword categories or buyer personas
• Implement priority routing based on urgency scores
• Add sentiment analysis to identify frustrated prospects (higher intent)
• Set up A/B testing with different qualification prompts

Enhance response workflow:

• Build automated response templates based on mention context
• Create team assignment rules based on lead characteristics
• Implement follow-up sequences for qualified leads who don't respond
• Add lead enrichment (company data lookup) before qualification

Advanced Usage Tips

Smart notification filtering: Instead of sending all qualified leads to one channel, route by score:

• Score 9-10: Immediate Slack notification to sales team
• Score 7-8: Daily digest email
• Score 5-6: Weekly review list

Competitive intelligence: Duplicate this workflow to monitor competitor mentions, then analyze patterns in customer complaints or feature requests.

Keyword optimization loop: Export unqualified mentions monthly and analyze common themes to discover new keyword opportunities or refine existing ones.

Response time tracking: Add timestamp nodes to measure time from mention to qualification to response, optimizing your competitive advantage in community-driven sales.

You're now equipped to run an intelligent, automated lead qualification system that works around the clock. Start with conservative qualification criteria and gradually refine as you learn what converts best for your business!