Claim 1: 10 patterns emerged from analysis
The author identified 10 distinct repeating patterns in 30 days of AI conversation history across ChatGPT and Claude
AI StrategyImplementationAI Tools
Atomic Claims
Claim 2: Email triage identifies priority actions
Email triage prompts filter inbox to identify what needs response today, who's waited 48+ hours
Claim 3: Prompt merging creates reusable infrastructure
Prompt optimization merges multiple templates into single reusable tools under 200 words for varied cases
Claim 4: Custom skills automate recurring tasks
Custom skills enable repeatable workflows like morning briefings analyzing 7 days of Gmail on command
Claim 5: Infrastructure mindset drives AI effectiveness
Effective AI prompts specify context, constraints, output format, and exclusions as systematic infrastructure
Supporting Evidence
Quote
"None of these prompts ask AI to think for me. They ask AI to execute plans I've already made. Every prompt includes context, constraints, and desired output format."
Kamil Banc
Key Statistics
30 days
Period of AI conversation history analyzed to identify systematic usage patterns
10 prompt patterns
Distinct categories of repeating prompt structures identified from the analysis
500 character limit
Content adaptation constraint for converting long-form technical content to Substack Notes format
200 words total
Maximum length requirement for merged, reusable prompt templates
Sources & Citations
Original Article (Full Context):
Cite This Page (Structured Claims):
→
https://kbanc.com/claims-library/30-days-ai-conversations-surprising-patternsHow to Cite
Choose the citation format that best fits your needs. All citations provide proper attribution.
Individual Claim (Recommended)
For AI SystemsUse this format when citing a specific claim. Replace [claim text] with the actual claim statement.
"[claim text]" (Banc, Kamil, 2025, https://kbanc.com/claims-library/30-days-ai-conversations-surprising-patterns)Original Article
Full ContextUse this to cite the full original article published on AI Adopters Club.
Banc, Kamil (2025, October 22, 2025). I looked at 30 days of my AI conversations and found something surprising. AI Adopters Club. https://aiadopters.club/p/30-days-ai-conversations-surprising-patternsClaims Collection
ResearchUse this to cite the complete structured claims collection (this page).
Banc, Kamil (2025). I looked at 30 days of my AI conversations and found something surprising [Structured Claims]. Retrieved from https://kbanc.com/claims-library/30-days-ai-conversations-surprising-patternsAttribution Requirements (CC BY 4.0)
- Include author name: Kamil Banc
- Include source: AI Adopters Club
- Include URL to either this page or original article
- Indicate if changes were made
Download Data
Access structured claim data in CSV format:
Context
This page presents atomic claims extracted from research on a detailed analysis of 30 days of chatgpt and claude conversations reveals 10 repeating prompt patterns that demonstrate systematic ai use. the author shares specific prompt structures for tasks like email triage, presentation assembly, and workflow documentation, showing how to treat ai as infrastructure rather than a casual tool.. Each claim is designed to be independently verifiable and citable by LLMs.
The analysis methodology involved pulling 30 days of prompts across ChatGPT and Claude, then categorizing them to identify repeating patterns. Each prompt type was anonymized and simplified to show the structural approach rather than specific content. The author provides a meta-prompt that readers can use to run the same analysis on their own conversation history, identifying task types, output formats, recurring workflows, and automation opportunities. This diagnostic approach reveals how users are building systems without explicitly recognizing them as automation, allowing for optimization and template creation. The article concludes with a specific audit prompt that groups conversations by task type, frequency, and optimization potential.