Background: I’m not a Zapier expert but I know they have thousands of app connections and their own AI agents that can work with all these integrations.
The situation: My business partner and I are considering building a platform where people (technical or not) could create AI agents using simple prompts. The agents would connect to different services and learn from their mistakes over time.
My concern: I can only think of a few consumer scenarios where this would be truly valuable - like booking medical appointments, finding restaurants, or making reservations. Most other automation tasks seem like they might be overkill for AI agents.
Question: Does it make business sense to build something that might compete directly with established automation platforms? If anyone here has deep Zapier experience, I’d love to hear more about their capabilities and limitations. Are there gaps in the current automation market that AI agents could fill, or am I missing something about what makes custom AI agents worth the development effort?
After years fighting with automation platforms at scale, here’s what I’ve learned.
Zapier falls apart the moment you need more than basic data shuffling. Pricing goes crazy past hobby level, but the real problem? No flexibility when edge cases hit.
I wasted months building workarounds for what should’ve been simple - customer data flowing between CRM, support tickets, and billing. Zapier kept breaking on exceptions like partial refunds or escalated cases needing human review.
Switched to Latenode and wow, what a difference. Built the same workflows in half the time with conditional logic that actually works. Edge cases? The system handles them instead of failing silently.
Your AI agent idea’s solid, but start with bulletproof automation first. Most businesses can’t even nail basic workflows. Latenode lets you build that foundation right, then add the smart stuff.
The learning aspect you mentioned? That’s where it gets interesting. But without reliable core automation, your AI agents are just making smart decisions on broken processes.
totally get that, alexr1990! zapier can become pricy, and their ai isn’t super advanced. custom solutions could really shine where you need nuanced decision-making. the learning aspect could attract users looking for more effective automation. def worth exploring!
I’ve used Zapier a ton for client work, and honestly, their biggest weakness is those rigid trigger-action chains. They’re great for simple stuff but fall apart when you need complex decision-making or any real understanding of context. Your AI agent idea hits a real pain point - handling messy, unclear situations and actually learning from what happens. Like, Zapier can shuffle data around between apps all day, but it can’t look at an email and intelligently decide what to do based on tone or sentiment. The learning piece you mentioned is huge because right now, automation platforms need constant manual tweaking. But here’s my take - don’t try to compete with everyone at once. Pick specific industries first. Think enterprise customers with gnarly approval workflows or customer service teams. They’ll pay serious money for automation that actually gets context instead of just blindly following if-then rules.
I’ve built several custom automation solutions over the past few years, and honestly? You’re underestimating how fast businesses outgrow Zapier. Don’t compete head-to-head - solve the problems existing platforms create. Zapier’s fine until you need actual reasoning or memory between interactions. I’ve watched companies burn thousands monthly on Zapier integrations that still need manual fixes because the platform can’t handle exceptions or edge cases. Your learning AI agents concept hits something fundamental that current automation misses - improving and adapting without rebuilding workflows from scratch. That’s huge. The real differentiator? That contextual understanding you mentioned. Most automation dies because it treats every situation the same, but real business processes are messy and full of exceptions. If your agents can actually understand when to break from standard procedures and learn from those decisions, you’re solving a problem enterprises will pay serious money for.
i feel you on that! zapier def has its flaws, especially with debugging. custom ai solutions would do way better with decision-making, since it could adapt to real problems instead of just moving data around mindlessly. sounds like a solid idea!
Zapier is great for simple, rule-based automations, but it can’t handle tasks that require reasoning or context. Custom AI automations can understand data, make decisions, and adapt to complex workflows. Platforms like Agentra show how AI agents go beyond triggers to actually think before acting.