Anthropic engineers just leaked their internal AI workflow.
Turns out, 99% of people are using LLMs completely wrong.
Here are 5 techniques that separate amateurs from experts:
1/ THE "MEMORY INJECTION" TECHNIQUE
Most people start fresh every time. Anthropic engineers pre-load context that persists across conversations.
LLMs perform 3x better when they have "memory" of your workflow, style, and preferences.
Example prompt to test:
"You're my coding assistant. Remember these preferences: I use Python 3.11, prefer type hints, favor functional programming, and always include error handling. Acknowledge these preferences and use them in all future responses."
2/ REVERSE PROMPTING
Instead of telling the AI what to do, make it tell YOU what it needs.
Forces the model to think critically about requirements before executing. Reduces hallucinations by 40%.
Example prompt:
"I need to analyze customer churn data. Before you help, ask me 5 clarifying questions about my dataset, business context, and desired outcomes. Don't start until you have all the information."
Claude Pro just became the best $20/month I spend.
I use it for workflow automation, trend analysis, and document processing.
Here are 12 Claude prompts that replaced my $200/month research subscriptions:
Prompt 1: "Analyze these 5 competitor websites [paste URLs]. Extract their value props, pricing psychology, objection handling, and CTA strategies. Show me what's working and what gaps I can exploit."
This single prompt replaced my marketing consultant. Projects context means it remembers everything. Used this to 3x our conversion rate.
Prompt 2: "Read this 80-page market research PDF. Give me: (1) counterintuitive insights others will miss, (2) 3 immediate opportunities, (3) risks everyone's ignoring. Format as a strategic brief."
Turns dense reports into actionable intelligence in 90 seconds. The Artifacts feature makes it presentation-ready instantly.