Stop Copy-Pasting Prompts Between Models: Format-Native Prompting for Claude 4.7, GPT-5.5, and Gemini 3.1
Each frontier model parses structure differently -- XML, JSON, or markdown. Match the format, and output quality jumps measurably.
Pillar
Techniques
Chain-of-thought, few-shot, role prompting, structured output
39 articles • Page 2 of 5
GPT-5.5's Seven-Part Prompt Schema: Why OpenAI Wants You to Delete Every Prompt You've Ever Written
OpenAI's new prompting guide kills personas, step-by-step, and emotional primers -- here's the minimal structure that actually works on reasoning models
Tuning Thinking Budgets: The Prompt Technique That Replaced Chain-of-Thought in Claude 4.7 and GPT-5.4
Stop writing 'think step by step'. Start setting token budgets that match the task.
What Leaked System Prompts From GPT-5.4, Claude 4.6, and Gemini 3.1 Teach You About Writing Your Own
The biggest AI labs just showed us their playbook -- here's how to steal their system prompt patterns for your own workflows
Persona Stacking: Layer Multiple Roles in One System Prompt for Expert-Level Output
Why 'You are a senior engineer who also reviews for security' beats single-role prompts
Meta-Prompting: Write Prompts That Generate Better Prompts Than You Can
Use frontier models to improve their own instructions with measurable improvement loops
The Negative Prompt Pattern: Tell the LLM What NOT to Do and Watch Quality Jump
Why exclusion constraints are more effective than inclusion instructions for complex tasks
Few-Shot Prompting Is Dead Weight in 2026: When Zero-Shot With Constraints Outperforms Examples
The counterintuitive cases where removing examples improves output quality
Prompting for Financial Analysis: Extract Insights From Earnings Calls and SEC Filings
Structured prompts that turn 100-page filings into actionable intelligence