
Turn photos into stained-glass panels
Reimagine flowers and still lifes as translucent glass pieces with dark seams and gentle backlight.
Open recipe
Browse prompts for writing, research, learning, and image creation. Add your context, inspect the full prompt, and use it with your preferred AI assistant.

Reimagine flowers and still lifes as translucent glass pieces with dark seams and gentle backlight.
Open recipe
Turn a flower or tabletop photo into a tactile oil painting with broken color, visible strokes and soft background edges.
Open recipe
Recast flowers or objects as pearlescent metal sculptures with soft studio reflections and a quiet pale setting.
Open recipe
Reduce a familiar subject to luminous cyan contours with generous dark space and a restrained halo.
Open recipe
Rebuild a landscape from matte paper shapes, shallow overlap shadows and tactile cut edges.
Open recipe
Keep a coastal view recognizable while repainting it with luminous gouache-like shapes and layered depth.
Open recipe
Render a familiar pet or object in graphite, preserving its pose with directional pencil marks and clean paper highlights.
Open recipeCreate content
Expand one evidence-backed topic into distinct audience questions and a coherent publishing sequence
Open recipe
Translate a flower or still-life photo into luminous blue-and-white tones inspired by photographic cyanotypes.
Open recipe
Turn a favorite place into a compact 3D-style landscape model with sculpted terrain, glassy water and soft studio light.
Open recipe
Rebuild a landscape as fine architectural mesh lines, quiet dark planes and a small luminous focal accent.
Open recipePersonal productivity
Choose realistic outcomes and sequence weekly experiments within actual capacity
Open recipeMany paths, one reliable recipe
Browse by type, task, audience, tool, or collection. Inspect the examples and guidance for each recipe.
Start with what you want the AI to produce
Find a recipe for the outcome you need now
Start from the result you need to produce
Find prompts for recurring professional work
Build skills, teach, and prepare for career moves
Plan everyday decisions and personal projects
Curated starting points for common roles and goals
Explore visual styles and practical recipe workflows
Adapt portable recipes and see recorded test status
FAQ
Learn how to choose a recipe, add useful context, and review the result.
An AI prompt recipe is a reusable set of instructions for a specific task, such as drafting a message, analyzing a document, or planning a meeting. AILesson recipes combine a prompt template with context fields, a worked example, and checks you can use to review the AI response.
Open a recipe that matches your task, fill in the context fields, and inspect the assembled prompt. Copy it into your preferred AI assistant, then use the recipe's checks to review the response. Unfilled fields remain as placeholders, so replace or remove them before sending the prompt.
The recipes use plain-language instructions designed to be portable across AI assistants. Check each recipe's test record for the tools actually tested. Results can vary by model and version, and tasks involving files or other inputs require an assistant that supports those inputs.
Search by the task or outcome you need, or browse by prompt type, task, audience, AI tool, or workflow. Compare the expected result and worked example with your goal before choosing a recipe. Add your own source material, constraints, and output requirements rather than copying the example unchanged.
No. Prompt assembly happens in your browser; the recipe builder does not send your field inputs to an AILesson server or an AI model. If you paste the finished prompt into another service, that service handles the information under its own policies. Only include information you are allowed to share with it.
No. A worked example and a test record show how a recipe was used, not a guarantee of future results. Check facts, source references, calculations, and whether the response follows your constraints. Use the recipe's review checklist and verify time-sensitive claims before relying on the output.