Let’s turn “50 Advanced Prompting Techniques for Gen AI” into a 50-day guided journey — one new technique per day, with a short explanation, a real example, and a mini exercise to practice.
Day 1: Role-based prompting – Give the AI an identity (“You are a Nobel-winning physicist…”). Exercise: Ask it to explain quantum tunneling as a comedian vs. a scientist.
Day 2: Instructional layering – Break down tasks into numbered steps. Exercise: Ask for a 3-step summary of any news article, then expand step 2 in detail.
Day 3: Output formatting – Use markers, tables, or JSON for clean structure. Exercise: Get the AI to output a product comparison in JSON format.
Day 4: Progressive refinement – Start broad, then refine with constraints. Exercise: First ask for 10 startup ideas, then refine to only those under $500 capital.
Day 5: Creativity with boundaries – Give specific do’s and don’ts. Exercise: Generate a poem with only one-syllable words.
Day 6: Embedding context – Put relevant info directly in the prompt. Exercise: Provide 3 bullet facts about yourself and ask AI to draft a cover letter.
Day 7: Long-form anchoring – Use a story or background to shape output. Exercise: Give a fictional world description, then ask AI to create laws for it.
Day 8: Prompt recaps – Summarize past exchanges inside the prompt. Exercise: After 2 responses, ask AI to recap its own answers before continuing.
Day 9: Context reduction – Shrink large inputs without losing meaning. Exercise: Ask AI to summarize a 1000-word essay into exactly 3 sentences.
Day 10: Simulated memory – Build continuity by re-feeding AI’s own outputs. Exercise: Ask AI to remember a fictional character’s backstory and continue it daily.
Day 11: Divergent vs convergent – Generate many ideas, then narrow down. Exercise: 20 app ideas → shortlist the 3 most profitable.
Day 12: Randomization seeding – Add “pick a random animal” to fuel novelty. Exercise: Write a business pitch that includes a giraffe.
Day 13: Hypotheticals – Frame prompts as “What if…?” Exercise: What if electricity was never discovered? Describe today’s world.
Day 14: Multi-perspective – Ask for multiple viewpoints on one issue. Exercise: Debate AI ethics as an engineer, a poet, and a lawyer.
Day 15: Inversion – Flip assumptions. Exercise: Instead of “how to succeed at work,” ask “how to fail at work.”
Day 16: Multi-role simulation – AI plays multiple characters. Exercise: Simulate a panel of experts discussing climate change.
Day 17: Alter-ego prompting – Create a rebellious counter-voice. Exercise: AI as “Devil’s Advocate” against your own argument.
Day 18: Cross-discipline synthesis – Merge fields. Exercise: Explain blockchain as if it were a cooking recipe.
Day 19: Style-mirroring – Mimic a style (academic, Shakespeare, TikTok). Exercise: Summarize Newton’s laws in rap lyrics.
Day 20: Role conflict – Assign two contradictory roles. Exercise: Ask AI to argue both for and against remote work simultaneously.
Day 21: Step reasoning – Request explicit reasoning. Exercise: Ask AI to solve a math riddle step by step.
Day 22: Hidden reasoning – Ask for final answer only (test conciseness). Exercise: “Do the reasoning silently, just give me the answer.”
Day 23: Multi-pass refinement – Re-run outputs with extra polishing. Exercise: First draft → improve clarity → shorten.
Day 24: Reverse-engineering – Deconstruct an output back to logic. Exercise: Give AI a conclusion and ask it to infer reasoning.
Day 25: Branching reasoning – Generate multiple solution paths. Exercise: Ask for 3 possible solutions to world hunger, each with pros/cons.
Day 26: Curriculum-style prompts – Build lessons. Exercise: Ask AI to create a 5-day crash course on Python.
Day 27: Progressive challenge – Increase difficulty step by step. Exercise: Math questions that get harder each time.
Day 28: Tutor-student simulation – Ask AI to quiz you and give feedback.
Day 29: Socratic questioning – AI only asks guiding questions.
Day 30: Self-testing loops – Ask AI to test its own answer for errors.
Day 31: Word count limits – Exact number of words. Exercise: Write a 7-word life lesson.
Day 32: Tone control – Friendly vs formal. Exercise: Same email in 3 tones.
Day 33: Register shifting – Street slang vs corporate jargon.
Day 34: Time-era localization – As if written in 1800s.
Day 35: Resource-limited – Explain using only emojis.
Day 36: Image-to-text – Ask AI to caption an image (if tools allow).
Day 37: Text-to-visual – Write prompts for an image generator.
Day 38: Style blending – Combine “sci-fi” + “noir detective” storytelling.
Day 39: Diagram description – Ask AI to describe a flowchart in text.
Day 40: Multi-modal layering – Mix instructions across text + visuals.
Day 41: Prompt chaining – Sequence outputs.
Day 42: API-ready formatting – JSON/CSV outputs for code.
Day 43: Validation loops – AI checks its own work.
Day 44: Error correction – Force AI to find mistakes in past outputs.
Day 45: Delegation – AI assigns itself sub-tasks.
Day 46: Prompt debugging – Ask “Why did you answer like this?”
Day 47: Compression – Shrink prompts without losing power.
Day 48: Scaling – Handle large docs with chunked prompts.
Day 49: Self-prompting – Ask AI to create its own prompts.
Day 50: Meta-meta prompting – Ask AI to invent a new prompting technique.
At the end of 50 days, the learner will have a personalized playbook of 50 prompting strategies, tested with real outputs and tailored to their own domain (business, creative writing, research, etc.).