Cadenly is your AI product team — whether you've never written a spec or you write them for a living. Describe what you want and the agent plans and runs the right workflows: business case, PRD, competitive and pricing analysis, a build-ready spec, QA, the build package, even the kickoff and a findings deck — asking only the calls that are yours to make. Or drive any of the twenty workflows yourself. Each one's output feeds the next.
Bring an idea, a PRD, or your board. 7 days free, then $20/mo · cancel anytime.
Twenty AI-assisted workflows spanning the whole arc — strategy, definition, build, and delivery — each staged so you stay in control and the AI does the mechanical work, or hand the whole thing to the agent. Size the market and pricing, build the business case, design AI into the product, recover the spec from what you shipped, turn a PRD into a build-ready spec, plan the QA and the build package, prep the kickoff, and present the findings — idea to shipped, in one place.
A startup advisor in software — not a chatbot that agrees with you. It diagnoses your real bottleneck before prescribing, challenges the numbers you take for granted, and pushes back when the plan is wrong. It remembers your goals and holds you to a check-in cadence, so advice compounds instead of resetting. Built to counter exactly how generic AI misleads founders: default positivity, false confidence, and advice that ignores your actual constraints.
A standing, interactive plan for founders — revisable market, model and GTM sections, a runway calculator, pricing-scenario compare, an investor CRM, milestones, and an AI coach that flags what needs attention.
Compare your product against rivals side-by-side — researched positioning, pricing and features, and the strategic read on where you win.
Research the market, model the economics, design tiers, and land on a pricing strategy that holds up — not a guess, a defensible plan with the reasoning behind each number.
The decision argument a PM produces to get something funded — problem, options (including do-nothing), a recommendation, cost/benefit & ROI, risks, and the ask. Built from the work already done for the product.
Turn the whole run into an answer-first slide deck tailored to your audience — leadership, investors, or your team — leading with the verdict, not a tour.
Take a product from problem to spec — brainstorm the problem, users and vision, then shape features, flow and requirements ready to build.
Turn a PRD or flowchart into delivery-ready specs — gap analysis, epics, story sizing, test cases, and Jira-ready packages.
Designing AI into your product — a decision framework that first asks whether AI even fits, then shapes capability, interaction, context, behavior, evaluation and cost into a spec.
Too many AI-generated requirements? Filter the firehose against researched business goals — sorted into Core, Competitive, Customer and Visionary buckets you own and phase — into a focused, phased scope. Not a bare MVP: the smallest complete build that ships quality, ready to hand to Prioritization or the Roadmap.
Built it with AI? Reverse-engineer the spec from what actually shipped — a feature map, actor flow, gap analysis, requirements with stories and acceptance criteria, test cases, and a PRD.
Review your product screen by screen against UX best practice and platform conventions — from real personas — and get prioritized, rationale-backed fixes for navigation, layout, and messaging that you accept, dismiss, or hand straight to your coding agent.
Score a backlog with RICE — pull candidates from your other projects, let AI estimate, rank by leverage, hand off to the roadmap.
A visual board — place prioritized items across Now / Next / Later phases and move them as plans change.
Plan how the product gets proven — test strategy, cases, data, performance and security — so quality is designed in, not bolted on at the end.
Everything engineering needs to start — a constitution, a phased build plan, and handoff docs written for developers or AI coding agents.
Walk into the build-kickoff meeting ready — agenda, per-role focus, the decisions to drive, and the pushback to expect. You run it; this preps you.
Design an automation as an n8n workflow — trigger, nodes, data mapping, credentials, and error handling — ready to build.
Your daily program-management loop — board status, risks, standup, meetings, and a management-ready weekly status.
Turn real feedback — reviews, tickets, NPS — into themes, ranked pain points, and a prioritized action list.
Structured product and engineering docs — problem, users, requirements, ready to hand off.
Epics and stories formatted for a clean import — no copy-paste into the board.
A prioritized list with reach, impact, confidence and effort — ranked by leverage, not volume.
Swimlane journeys and Now / Next / Later boards you can export and drop into a doc.
A management-ready summary and a recency-aware risk register pulled from your board and meeting notes.
A capability, interaction, context, behavior, evaluation and cost spec — the AI decisions made before engineering starts.
A constitution, dependency-ordered build plan, software design doc and per-epic specs — a file tree you unzip into a repo and point a coding agent at.
Whether you're validating an idea, breaking down a vague doc, or running standup in ten minutes, there's a workflow for it.
No PM background needed. Describe what you want and the agent takes it from idea to PRD to a build-ready spec — and a package your developers, or an AI coding agent, can actually build.
Recover the spec from what you already shipped, add real test cases, and package it for a clean handoff — so what you vibe-coded becomes something you can harden and trust.
Shape the PRD, prioritize with RICE, and hand engineering a build-ready spec that's already structured, sized, and thorough — the way someone who's written a thousand would.
Sequence the roadmap, prep the build kickoff, and run the week — risks, standups, and a management-ready status — from one place.
An honest advisor, a living plan with runway and scenarios, competitive and pricing reads, and a business case — so you build the right thing, not the wrong one.
When AI generates more requirements than anyone can build, filter the firehose against business goals into a focused, phased scope — then turn it into flows, requirements, and test cases that hold up to review.
Start your free trial and pick a workflow — bring an idea to validate, a PRD to spec, or your board to run the week.