I wasted months guessing at prompts before I figured out what actually works. These six techniques changed everything.
🕐 Updated June 2026 · 6 sectionsI've been prompting AI models daily for two years — ChatGPT, Claude, Gemini, the works. Most of the "advanced techniques" floating around Twitter are fluff. But these six? They consistently deliver. Each comes with a real example you can steal and tweak for your own work.
Bad: "Write about AI"
Good: "Explain how transformers work in AI, at beginner level, with a real-world analogy, in 300 words"
Vague prompts get vague answers. When I started including format, audience, and a word count, my results went from mediocre to exactly what I needed in one shot.
Prompt: "You are a senior Python developer reviewing my code for security vulnerabilities. Here is the code: [code]"
Tell the AI who it is and it suddenly gets 10 IQ points in that domain. I use this trick constantly for coding reviews and content editing.
Prompt: "Solve this problem step by step. Show your reasoning at each step before giving the final answer."
Making the AI "show its homework" cuts errors dramatically. I use this for anything involving math, logic puzzles, or multi-step reasoning.
Prompt: "Convert sentences to pirate speak. Input: Hello friend → Output: Ahoy matey! Input: How are you → Output: How be ye sailin?"
Two or three examples beat a paragraph of instructions every time. This is my go-to when I need consistent output formatting across dozens of prompts.
Prompt: "List 5 tips in bullet points. Each under 15 words. Include a relevance score out of 10 for each."
Give the AI guardrails and it stays on track. Word limits, output formats, specific fields — constraints prevent rambling and keep responses scoped to what you actually need.
Prompt sequence: "Write a blog intro about AI" → "Make it more conversational" → "Add a surprising stat in the first sentence" → "Cut it to 3 sentences"
The first response is rarely the best. Treat the AI like a junior colleague — give feedback, refine, and iterate. Three rounds of revision consistently produces output 2-3x better than the first draft.
Be specific. Include format, length, tone, audience. A 30-second detailed prompt saves 5 minutes of editing poor output.
0-0.3 for factual/technical. 0.5-0.7 for creative. 0.8-1.0 for brainstorming and ideation.
Yes — even more so. Better models reward better prompts. The gap between good and bad prompts has grown.
Yes. Build a prompt library. Many pros maintain templates. ChatGPT Custom GPTs can save prompt workflows.
Practice daily. Try same prompt on different models. Join r/ChatGPT and r/PromptEngineering. Read model docs.