Coming from Gumloop?
Gumloop is useful when business work needs an agent to choose tools and use shared context, and it also offers custom triggers. Whenever fits the part of that work you can already write down: you describe the job in plain language, and AI writes TypeScript once that later runs execute. AI building is free within weekly usage limits; the file is yours. Review summaries and sample results; reading code is optional. Fixed logic is deterministic with the same inputs and dependencies, while changing external data and optional AI can change results and costs.
What you get on Whenever
Written once, then run as code
AI writes the procedure once, and the published TypeScript decides what happens next on every run. A model is called only where you add an AI step.
The same steps on every run
For the part of the work you can already write down, the published code runs it the same way every time. This applies to fixed non-AI logic with the same inputs and dependencies; optional AI and changing external state can change outcomes. You can review the summary and results without reading code.
TypeScript you can download
What you keep is a readable TypeScript file: read it, edit it, diff it, take it with you. AI building and editing are free within weekly usage limits; published runs are metered separately.
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.
Keep judgment. Write down the procedure.
An agent session and a workflow execution are not interchangeable units. Separate the reasoning you need from the steps you already know.
Gumloop
Agent-usage credits
Models, tools, active compute and orchestration
The documented agent-chat meter combines several costs. BYOK and enterprise deployment affect the bill.
Gumloop agent-chat credits combine model, tool, compute and orchestration usage. Eligible BYOK model calls on usage-based Pro-or-higher plans use zero model credits, while older policies may discount instead; provider charges and platform tool or compute charges remain, and orchestration rates differ. AI-generated polling triggers are saved code, billed each poll even if the agent does not start. Budget trigger and agent usage together.
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
Gumloop
Gumloop agent execution can choose tools with a model. Its documented AI-generated polling triggers are saved code that runs on a schedule; an agent starts when the trigger condition is met. Fixed trigger code and model-directed agent work are different modes.
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
Gumloop
Documented agent-chat billing combines model usage, successful tool calls, active compute time and orchestration. Credit consumption depends on what the agent does, not just how often a trigger fires.
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
Gumloop
Agents, tools, business knowledge, approvals and evaluations suit work that needs context and judgment. Recurring, one-time, app-event and webhook triggers can initiate that work.
Whenever
Describe the rules you already know; AI writes the procedure. Review the summary and sample results, not necessarily the code. Keep an explicit model step for judgment. Agent platforms may also offer fixed workflows or scripts; compare the mode you actually use.
Export and portability
Gumloop
The agent-version API exports immutable configuration and changes. It omits skill file contents and is a read-only endpoint, not a restore/deploy API. Enterprise own-VPC execution is also documented.
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
Gumloop
Gumloop documents immutable agent-version configuration snapshots and performance evaluations. This is not a promise that every self-edited instruction has version history; the authoring documentation distinguishes those edits.
Whenever
Read the fixed procedure and execution log, then test the failing input. If a model step is present, inspect its input and output separately from the surrounding code.
Where the AI cost lands
Gumloop
Model use is one part of agent-chat credits. BYOK pays provider tokens separately, while tool, compute and orchestration costs can remain. Own-VPC enterprise customers have different compute treatment.
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 Gumloop
Gumloop
Keep it for genuinely open-ended work, rich connectors, shared knowledge, human approvals, evaluations and agent-management controls. Those capabilities may be central to the job, not overhead to eliminate.
Whenever
Consider Whenever for the stable sub-procedure: fetch these records, apply these rules, update these destinations. A typed workflow is not a substitute for every knowledge-driven agent or enterprise deployment requirement.
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 repeatable Gumloop job.
Bring one job with clear inputs and outputs. Keep the agent for the work that still needs an agent.
Capture the configuration and context
Record the trigger prompt, tools, approvals and expected outputs. Use the version export as reference, and collect needed skill content separately; that endpoint does not export skill files.
Make the decision boundaries explicit
Separate fixed API operations from steps that need judgment, then describe both and let Whenever’s AI write them. Review the workflow summary and sample results; inspect TypeScript if useful and any deliberate model call. Reconnect services rather than assuming agent credentials transfer.
Compare representative outcomes
Use safe examples, including ambiguous input and approval cases. Keep work requiring Gumloop-specific controls there; switch only the bounded procedure after disabling its original trigger.