Current:
New: This reel provides concrete steps for using the Reddit MCP (as mentioned in DQh0ttFkgKF) to build a 'customer language file' specifically for 'human-sounding copy' and integrates these findings directly into AI prompting techniques and audit processes, moving beyond just 'pain point extraction' to 'language activation' for copy generation.
Current:
New: While DWEi9NvkTQo focuses on modular sales skills and general AI message humanization, this reel provides specific techniques ('latent space activation prompting', 'read aloud' gate, replacing 'hype words' with 'conversational language') and a structured framework for achieving humanization in marketing copy using real customer verbatim, offering actionable steps beyond the general concept.
Current:
New: DWjfckpD3YB covers general Claude skills and PDF reports. This reel introduces specific advanced prompting techniques for Claude ('latent space activation prompting') focused on tone and empathy, explicitly linking scraped customer language files (RAG) to refine Claude's output for human-sounding marketing copy, something not detailed in the general Claude skills plan.
Replace AI hype-speak with authentic customer language on TFWW website and AIAS SMS prompts to increase conversion rates.
Rewrite services and offer pages using Technique 2 customer language file (gather 50+ real quotes from SMB owners about website pain points) and Technique 4 conversational tone rules. Remove all 'clickfunnel' urgency language.
Update Claude system prompts in /services/anthropic.js to include latent space activation framing for target verticals (contractors, roofers, etc.). Add customer language files as RAG context for appointment setting conversations.
Apply 'sound like a text from someone who cares' rule to DDB LinkedIn/Telegram content vs current 'business guru' tone. Use the customer research file from Technique 2 to speak LMI community language.
Our take: We've been using Claude for AIAS since day one specifically because it avoids that 'LinkedIn AI' voice in SMS conversations. The customer language file technique is exactly how we built our qualification scripts - scraping r/smallbusiness for the real frustration behind 'I need more leads.'
Technique 2 is the real unlock - that customer language file becomes a moat. Nothing converts like mirroring their exact 2am Google search terms back to them.
What it is: Copywriting methodology to bypass 'AI voice' and LinkedIn-bro tone by using specific prompting techniques (latent space activation), customer research aggregation (reddit MCP, perplexity), Claude selection, and conversational language rules
How it helps us: Directly applicable to TFWW website copy (currently sounds corporate), AIAS SMS sequences (needs to sound human), and DDB content. We already use Claude as primary LLM in AIAS, validating Technique 3. The customer language file approach solves our 'speaking to small business owners' problem by mining r/smallbusiness and local service forums for exact pain vocabulary.
Limitations: Creator dismisses 'expert copywriter' prompts but we sometimes need conversion-optimized landing page frameworks (not just conversational). Some 'funnel speak' still converts in high-intent paid traffic contexts where urgency drivers work.
Who should see this: Dylan for DDB/TFWW copy review; AIAS dev team for SMS script generation prompts
| Step | Prompt | Completion | Cost |
|---|---|---|---|
| analysis | 11,814 | 2,967 | $0.0118 |
| similarity | 1,608 | 600 | $0.0006 |
| plan | 8,132 | 6,134 | $0.0172 |
| Total | $0.0296 | ||