Coming from Make?
Make offers visual scenarios and AI-assisted building; it is not limited to arranging everything by hand. Whenever turns your description into a procedure you supervise through summaries and sample outputs. The same published code runs each time; optional AI steps can vary and have runtime costs. Free AI building has weekly usage limits; the file is yours.
What you get on Whenever
Written from your description
Describe the job and review the generated procedure and sample outputs. Make’s Maia also creates, modifies and debugs scenarios from prompts, including module settings; natural-language changes are not exclusive to Whenever.
One run, however many operations
The meter counts the workflow execution within its call budget, rather than individual operations. To budget the month, include runtime AI spend, any need for a larger plan and external API charges. A different unit alone does not establish a lower dollar bill.
Logic you read top to bottom
Whenever produces a readable TypeScript workflow. Make also documents JSON blueprint sharing and import into other scenarios or compatible tools. Compare the artifact and connection dependencies, not an assumption that Make cannot export. AI building on Whenever has weekly usage limits.
A concrete decision
Illustrative scenarios, not customer results or recorded runs.
Greg: no “done” without the invoice receipt
Illustrative decision, not a recorded customer run: Greg wants each paid order checked against Stripe, then an invoice created, its ID saved, and only then a confirmation sent. He specifies that an invoice failure must stop the confirmation, and an already-handled order must not be charged or invoiced again. He checks the summary, sample records, provider receipts and run history—not source code. Test a missing payment, a failed invoice and a duplicate event before publishing. Whenever fits when those prescribed steps matter more than an agent deciding them again; a fixed workflow elsewhere can fit too. No screenshot here claims these actions were actually delivered.
Jaunius: make the edge cases explicit
Illustrative decision, not a benchmark: Jaunius needs all pages of 5,000 contacts, a saved last-seen ID, updates only for changed records and a clear record of which writes failed. He brings the old workflow and sample inputs, reconnects accounts, and tests pagination, an API failure and a repeated event before switching triggers. Choose a single procedure if it makes this logic easier to maintain; the other tools can also support complex logic. An optional model that classifies a note can vary and adds runtime AI usage. Compare the monthly subscription and actual usage, not the number of steps alone.
Credits per operation, or one run per workflow.
Make offers visual scenarios and AI-assisted authoring; Whenever offers an AI-written procedure. Make credits and Whenever executions count different work, so compare actual workloads and plan terms.
Make
Operation-based credits
Scenario usage, AI-agent chat and Maia usage
Ordinary non-AI operations normally use one credit; AI and advanced features can have variable rates, and Maia consumes credits from the same pool.
Do not divide a credit allowance by the number of scenarios. Modules, processed bundles and feature-specific rates affect consumption. A short Make scenario can be economical; estimate a representative workload before deciding which meter fits.
A run is one execution of one workflow, start to finish. AI building and editing are free within weekly usage limits; runs are metered separately.
A closer look
What changes when you describe the job in plain language and code runs it: to build, to run, and to keep.
Repeatable execution logic
Make
Scenarios run the modules you configure; a router splits the flow into routes, and filters add conditions to each route. AI apps and Make AI Agents are modules you add where you want them.
Whenever
AI writes it, then published code runs the same execution logic. With identical inputs and dependencies, non-AI logic is deterministic. Changing API data, time, randomness or an optional model step can change results; this is not an exactly-once delivery guarantee.
Runs per dollar
Make
Make bills in credits. Most non-AI operations consume one credit, while some features depend on tokens, processing time, pages or file size. The work performed inside the scenario matters.
Whenever
Pro includes 10,000 runs per month; see the pricing page for current US dollar prices. AI building and editing are free within weekly usage limits. Published runs are metered separately: the meter counts the whole run, not individual steps. External services and optional model calls can have their own charges.
What you can express
Make
Make builds scenarios from modules, mapped values, routers and filters on the scenario canvas, and Maia can build and edit scenarios from a prompt. Natural-language authoring alone is not the distinction.
Whenever
Describe the job in plain language: match payments to orders, fetch every page of contacts, or alert only on unseen reviews. AI writes the procedure; you supervise its rules and results, and reading code is optional. API access still needs suitable permissions and a service reachable from the hosted runtime.
Export and portability
Make
Make documents JSON blueprints containing modules, settings and mapped values, sharing them with other users, and importing into scenarios or compatible tools. Connections must be recreated; check the destination’s compatibility rather than assuming a universal runtime export.
Whenever
The TypeScript is yours: read it, edit it, export it, take it with you. Moving it to another runtime can require adapting managed connections, triggers and runtime-specific integrations.
Debugging a failed run
Make
The visual scenario remains the unit you inspect and maintain. Trace the modules and mapped values, and consider how bundles fan out when reproducing a problem.
Whenever
Review the execution log, summary and sample outputs; inspect TypeScript if useful. Make also documents history, replay and output bundles, so debugging availability is not the distinction.
Where the AI cost lands
Make
Not every scenario needs AI. Built-in AI can have variable credit rates; when you supply custom model credentials, provider token charges are separate.
Whenever
AI writes the workflow once, with free building subject to weekly AI usage limits. A published procedure runs its steps without a model choosing them. Any model call you explicitly include still runs and has its own cost.
When to keep Make
Make
Keep Make when your team likes working on the scenario canvas, already has reliable scenarios, and depends on the apps it connects. Moving a simple working scenario may buy very little.
Whenever
Consider Whenever for logic that is easier to understand as a program, or when you prefer a whole-run allowance. Make’s enterprise on-premise agent connects private systems; replacing that network access needs its own plan.
Sources and scope
Official sources captured on the date shown below. These describe published features and billing rules, not independent performance tests. Check the linked documentation for current modes, plans and limits. No competitor dollar price is asserted.
Checked
Start with a workflow brief
Pick a starting point, connect your accounts and review what Whenever builds before publishing.
Build this workflowAnnounce closed-won deals in SlackCelebrates each won deal in Slack with the numbers and a short recap of how it was won.
Build this workflowPublish Instagram posts from a calendarPublishes due rows from your Instagram calendar on the cadence you choose and writes each post link back.
Build this workflowLog survey responses and alert on low scoresAdds each survey response to Google Sheets within minutes and emails the owner when the score falls below your threshold.
Build this workflowTrack keyword rankings in a sheet each weekChecks the search position of every keyword on your list, appends the history to a sheet and reports the moves.
Build this workflowRoute large expense claims to a managerLogs every expense submission in a sheet and alerts a manager in Slack when the amount is over the approval limit.Build this workflowStart with one Make scenario.
Bring one scenario and describe what it does. Whenever writes it as a file you can read top to bottom; the rest of your scenarios can stay in Make.
Bring the blueprint and examples
Export the JSON blueprint. Capture sample bundles, mapped fields, router filters, error behavior and scheduling requirements. Keep credentials out of shared examples.
Review the translated procedure
Use the scenario as a specification, not a one-click import. Review its business rules and sample results, then reconnect services; inspect TypeScript only if useful.
Compare outputs before switching
Use safe test records to compare each destination’s result, including empty bundles and failed API calls. Turn off the Make schedule before publishing the replacement trigger.