Here's a confession: when we first started building Fantomu, we built workflows and called them "agents." They worked fine, but they weren't actually agentic. They were just scripts with better branding.
It took us months to realize the difference. And once we did, everything changed.
Workflows vs. Agents: The Real Difference
Imagine you're following a recipe. A workflow is like that recipe—step by step, predetermined. If you run out of an ingredient, you stop. There's no adaptation, no decision-making, no intelligence.
An agent is more like a skilled chef. They look at what's available, make decisions about substitutions, adjust cooking times based on how things look, and pivot when something goes wrong. They evaluate, decide, act, and then evaluate again.
That's the fundamental difference. Workflows execute. Agents think.
The Four Pillars of True Agency
After rebuilding Fantomu's core systems, we've identified what actually makes something agentic:
1. Decision Loops
An agent doesn't just execute steps—it continuously evaluates its situation. After each action, it asks: "Did that work? What's the current state? What should I do next?"
This creates a loop: evaluate → decide → act → evaluate again. The agent can take different paths based on what it discovers, not just follow a predetermined script.
2. Autonomous Failure Handling
When a workflow fails, it stops. When an agent fails, it analyzes why and tries a different approach.
Maybe the API endpoint is down, so it tries a different one. Maybe the data format is unexpected, so it adapts its parsing. Maybe it needs more information, so it asks for clarification.
The key is that the agent makes these decisions itself, without human intervention.
3. Context Awareness
An agent understands where it is in the process. It remembers what it's already tried, what worked, what didn't, and what the current state of the system is.
This context informs every decision. An agent won't retry the same failed approach three times—it learns and adapts.
4. Structured Decision-Making
This is critical: never parse natural language for decisions. Always use structured outputs with defined schemas.
Instead of asking an LLM "What should I do?" and trying to parse "I think you should retry with exponential backoff," define a schema:
{
"action": "retry" | "clarify" | "abort",
"strategy": "exponential_backoff" | "different_endpoint" | "manual_review",
"reasoning": "string",
"confidence": 0.0-1.0
}This eliminates ambiguity and parsing errors. The decision is always clear and actionable.
What We Learned the Hard Way
Rebuilding Fantomu to be truly agentic wasn't easy. We had to throw away months of work and start over with a different architecture.
But the results speak for themselves. Our agents now handle edge cases we never anticipated. They recover from failures gracefully. They feel intelligent, not scripted.
Most importantly, they actually solve problems we couldn't solve with workflows alone.
The Honest Truth
Here's the thing: most problems don't need agents. A well-designed workflow is often simpler, faster, and more reliable.
But when you need something that can adapt, make decisions, and handle the unexpected? That's when true agency becomes invaluable.
And that's what we're building with Fantomu—not just automation, but actual intelligence.