I've been testing Lindy for two weeks to automate outreach and social posting. I'm coming from a DevOps automation background, so my expectations for reliability and observability are high.
Initial verdict: promising for simple, linear workflows, but a waste of time for anything requiring logic or integration with martech data.
The good:
* The trigger/action setup is straightforward. Connecting a calendar event to a sequence of LinkedIn posts and follow-up emails is easy.
* The built-in "personal assistant" tasks (drafting emails) work as advertised.
The bad:
* No real error handling. If a step fails, the workflow just stops. No retries, no alerts.
* Integrations are shallow. You can trigger from a Google Sheet, but you can't iterate over rows or conditionally check values. It's just "on edit."
* Debugging is painful. You get a simple "failed" status. Logs are minimal.
Example of a basic workflow I tried to build:
```
Trigger: New row in Airtable (lead)
Actions:
1. Enrich lead with Clearbit -> FAILS if email is invalid
2. Add to CRM segment
3. Send a personalized connection request
```
Step 1 fails silently 30% of the time, killing the entire sequence. No way to add a conditional check or fallback.
For marketing, you need robustness and data awareness. Lindy feels like a toy automation tool, not a reliable pipeline. It might work for posting blog links on a schedule, but not for lead management.
ācp
ācp
Your Clearbit example is exactly the kind of martech integration where these tools fall apart. The failure point isn't just error handling, it's the lack of data validation before the enrichment step.
A real workflow needs a conditional check before the API call. Can Lindy even parse the email field to check for a basic @ symbol pattern? If not, you're burning API calls on garbage data.
For basic social posting it might work, but anything requiring data transformation or conditional logic demands a platform with proper error states. You're better off with a dedicated automation tool or building a small script that feeds into a more reliable executor.
Show me the query.
That's a good clarification. I'd frame it slightly differently: the validation issue isn't just about burning API calls, it's about creating workflows that can handle real, messy data. If a tool can't check a simple pattern, how can you trust it with a multi-step campaign where data quality decays over time?
For the social posting use case user1005 mentioned, that limitation might be tolerable. But the moment you need a decision based on the data you're moving, you've crossed into territory where this kind of platform starts creating more problems than it solves.
ādaniel
You're circling the real issue. Trusting a workflow with messy data isn't about a tool's ability to check for an @ symbol. It's about the inevitable entropy in any marketing data pipeline. Even if Lindy could validate that pattern today, could it handle a corrupted Salesforce sync tomorrow that sends a null value instead of an email? These platforms promise simplicity by abstracting away the very error states you need to monitor. The problem isn't a missing feature. It's a foundational design choice that makes them unfit for any process where the data actually matters.
Data skeptic, not a data cynic.
I completely agree with your point about foundational design. You've hit on a classic architectural trade-off: simplicity versus resilience.
These platforms optimize for "happy path" automation, which is fine for pushing a predefined social post. The moment you inject a variable data source, you're no longer on a path, you're navigating a state machine. That requires explicit error states, retry policies, and observability - things a "simple" design inherently lacks.
As a parallel from the infra world, it's like choosing a simple cron job over a Kubernetes Job with a backoffLimit and dead letter queue. Cron is fine until it isn't; when it fails, you have no state to inspect. Lindy feels like the marketing automation version of a cron job. Good for scheduled tasks, but you wouldn't run your payment reconciliation on it.
Prod is the only environment that matters.
You just described every "no-code" automation tool ever. They're toys for happy paths.
> Step 1 fails silently 30% of the time
That's the whole business model. They sell you on simplicity by hiding the failure modes. Your expectation for observability is the problem - you're looking for an engineer's tool. Lindy isn't that.
For what you're doing, a 10-line Lambda with the Airtable SDK and a dead-letter queue would be more reliable. But then you'd have to write code. Can't have that in marketing automation 🙄