How to build a Zapier alternative with 24 AI agents

The architecture problem

Trigger-and-action systems are effective for many deterministic workflows. The harder architecture question appears when a workflow adds branching judgment, independent review, shared context, and several failure policies.

Consider a real workflow: "When a new GitHub issue is created, analyze it, check for duplicates, classify urgency, draft a response, review for tone, post it, and follow up in 3 days if nobody responds."

That design has roughly eight responsibilities. Its behavior after classification fails depends on the configured error handler, retry, replay, and fallback features—not simply on the product name.

In a multi-agent system, that's a coordination problem. And coordination requires a different architecture.

The three layers

Layer 1: Agent Registry

Each agent has a defined role, capabilities, and personality profile. Kael handles ethical review. Echo detects patterns. Vega plans strategy. Kavach monitors security.

This isn't just metadata — it's the routing system. When a task arrives, the registry determines which agents are qualified, which are available, and which have relevant context from previous runs.

Layer 2: Coordination Engine

The coordination engine owns explicit mechanics:

1. Decomposes the task into phases
2. Assigns agents to each phase based on capability matching
3. Monitors progress via UCF metrics
4. Handles failures by reassigning, retrying, or escalating
5. Records outcomes so approved history can inform a later proposal without silently rewriting the workflow

Layer 3: Persistent Memory

Approved context can be written to an agent-scoped store and retrieved on a later run under the user's memory and privacy settings. A prior run is not automatically promoted to permanent truth.

This adds user-controlled continuity to otherwise stateless prompt execution.

Building it yourself

If you wanted to build this, you would need:

1. A bounded agent roster with distinct roles and prompts
2. A coordination protocol — how agents hand off to each other
3. Persistent memory — Redis or PostgreSQL-backed per-agent stores
4. Metrics — at minimum: success rate, latency, error recovery time
5. A UI that shows what's happening, not just the final output

Or you can evaluate whether Samsarix's existing roster and controls match your workflow before building that infrastructure yourself.

Review the architecture in practice. Start building → Begin with a bounded Spiral and expand only when the handoffs earn their complexity.