AI Workflow Prompts: From Goal to Sequence
An AI workflow prompt set turns one goal into an executable sequence — objective, prompt, and expected output per step, ready to run top to bottom.
View Resource →Prompt Builders
Big tasks fail in single prompts. Describe the goal and get a sequential workflow instead — focused prompts with an objective and expected output each, where every result feeds the next step. Runs entirely in your browser.
The big task to break into steps — e.g. "Launch a new SaaS product".
An AI workflow prompt set turns one goal into an executable sequence — objective, prompt, and expected output per step, ready to run top to bottom.
View Resource →The decomposition method for AI work: clarify the outcome, split into components with dependencies, sequence by risk, execute one component per prompt.
View Resource →A sequential prompt workflow for competitor analysis: scope what the analysis must decide, evaluate every competitor on the same criteria, and end with findings a pricing or positioning call can rest on.
View Resource →A sequential prompt workflow for content strategy: audience first, then goals, competitor gaps, topic clusters, defensible angles, and a publishing plan with a review loop.
View Resource →A sequential prompt workflow for hiring: outcome-based role definition, signal-mapped screening, structured interviews, evidence-based debriefs, and a 30-day onboarding.
View Resource →A sequential prompt workflow for market research: scope the question, set evidence rules, map the landscape, hunt counter-evidence, and end with a stress-tested verdict.
View Resource →Big tasks fail in single prompts. Multi-step prompting breaks a goal into focused, sequential prompts — each output validated, then fed into the next.
View Resource →A sequential prompt workflow for product launches: problem definition through MVP scope, risk register, milestone roadmap, launch checklist, and post-launch review.
View Resource →Prompt chaining runs prompts in sequence where each output becomes the next prompt's input — the technique that turns a chat into a pipeline.
View Resource →In sequential prompting the order is the intelligence: definitions before judgments, evidence before conclusions, plans before execution.
View Resource →Instruct an AI agent that runs on its own without it wandering off — anchor it to a role, write the agent system prompt, then lay out the multi-step plan it works through.
View Playbook →Run hiring the same way for every role — build a reusable job-description template, lay out a consistent screening sequence, and extract structured data from resumes instead of eyeballing each one.
View Playbook →Describe the big goal — "Launch a new SaaS product", "Choose a CRM", "Hire a backend engineer" — pick a workflow type, a complexity, and a step count, then click Build Workflow. The builder decomposes the goal using its browser-side phase libraries: every workflow type carries its own sequence of phases (a research workflow scopes a question, maps candidates, and hunts counter-evidence; a hiring workflow defines outcomes, designs screens, and structures debriefs — they share nothing). Each step arrives ready to run: an objective, a complete prompt with your goal woven in, and the expected output that feeds the next step. Nothing leaves your browser.
Every other tool on this site produces or improves a single prompt. The Multi-Step Prompt Builder produces a sequence: it decomposes a goal into ordered, focused prompts where each output feeds the next. If your task fits in one prompt, use the other tools; if it's a project, use this one.
Three reasons: validation (you check each output before it becomes the next step's input, so one weak assumption can't poison everything), focus (the model goes deep on one job per prompt instead of spreading attention), and steering (you can course-correct at any checkpoint without losing the work behind it).
Deterministic phase libraries, one per workflow type, built from how that discipline actually sequences work. Complexity selects the phase pool — Simple keeps the core phases, Advanced adds rigor phases like counter-evidence hunting or risk mapping — and the step count selects from that pool while preserving order. The same inputs always produce the same workflow.
Yes — prompts reference the previous step's output ('Using the audience from the previous step…'), which is why running them in a single conversation works best. The expected-output line tells you exactly what each step should hand to the next.
Yes, and you should — especially constraints specific to your situation. Each step prompt is a starting point with your goal woven in. To strengthen an individual step's wording further, run it through the Prompt Rewriter.
Use General — it runs the universal decomposition: clarify the outcome, break into components, gather inputs, sequence, execute, review. It's less specialized but works for anything with a definable outcome.