AI Prompt Guides
Master how to communicate effectively with modern AI systems using battle-tested prompt architectures and copyable templates.
Dedicated AI Platform Guides
Tailored prompt structures that leverage the unique architecture, context windows, and tools of each model.
ChatGPT
Prompt Guide & ArchitectureMaster conversational reasoning, Custom Instructions, and the OpenAI structured prompting pattern.
Claude
Prompt Guide & ArchitectureHarness Claude's massive context window, XML tag structuring, and Artifact rendering precision.
Cursor
Prompt Guide & ArchitectureMaximize codebase indexing, @Files context referencing, and targeted diff generation.
DeepSeek-R1 & V3
Prompt Guide & ArchitectureMaximize open-weights reasoning power, chain-of-thought deliberation, and mathematical precision.
Flux.1 & Black Forest Labs
Prompt Guide & ArchitectureMaster 12B-parameter rectified flow transformers, photorealistic prompt engineering, and typography generation.
Gemini
Prompt Guide & ArchitectureLeverage 2M+ token multimodal reasoning, Google Workspace grounding, and native YouTube/Search integration.
GitHub Copilot
Prompt Guide & ArchitectureMaster contextual repo-wide prompting, inline completions, slash commands, and Copilot Edits.
Microsoft 365 Copilot
Prompt Guide & ArchitectureDrive enterprise automation across Excel data modeling, Word executive syntheses, and Teams meeting summaries.
Midjourney
Prompt Guide & ArchitectureMaster aesthetic prompt parameters, lighting tokens, composition tags, and stylize flags.
Mistral AI & Le Chat
Prompt Guide & ArchitectureLeverage European frontier open weights, Codestral code generation, and concise multilingual precision.
Perplexity
Prompt Guide & ArchitectureUnlock precision research, real-time web grounding, academic source filtering, and cited answers.
v0 by Vercel
Prompt Guide & ArchitectureGenerate clean React Server Components, Tailwind CSS styling, and shadcn/ui component interfaces.
The 7 Core Components of High-Performance Prompts
Rather than relying on vague "secret magic words," state-of-the-art models perform best when instructions follow an explicit, structured cognitive scaffold:
1. Role & Persona
Define who the AI is acting as (e.g. 'Principal Cloud Architect', 'Senior Investigative Journalist'). Sets tone and technical depth.
2. Context & Environment
Provide codebase specs, stack versions, user constraints, and background business circumstances.
3. Clear Objective
State the single concrete goal without ambiguity. Avoid open-ended, unfocused tasks.
4. Negative Constraints
Explicitly declare boundaries ('Do not use external dependencies', 'Keep response under 300 words').
5. Output Format
Specify exact structure: Markdown table, strict JSON schema, or numbered implementation steps.
6. Few-Shot Examples
Supply 1-2 concrete pairs of sample inputs and desired outputs when exact style matching is required.
7. Follow-Up Iteration
Refine responses sequentially rather than restarting: 'Critique your code against performance edge cases, then patch it.'
Proven Prompt Templates
Ready-to-copy, battle-tested prompt templates across practical engineering and business use cases.