The Intent Extraction Loop is the fundamental pattern for agentic workflows. It describes how intent flows from specification to execution.
1. Specification (Gherkin + Figma)
↓
2. Semantic Extraction (LLM as parser)
↓
3. Canonical Form (DAG of operations)
↓
4. Execution (Deterministic runtime)
↓
5. Verification (Prove fidelity)
↓
6. Audit Trail (Prove execution)
Input: Gherkin scenario + Figma design
Scenario: Process refund
Given a completed transaction
When the customer requests a refund
Then deduct from merchant account
And credit customer payment method
And send confirmation email
The LLM is used only for understanding, not execution.
Task: Extract entities, relationships, and constraints.
Output:
{
"entities": {
"transaction": "completed",
"customer": "identified",
"merchant": "identified"
},
"operations": [
"deduct_from_merchant",
"credit_customer",
"send_email"
],
"constraints": [
"transaction must be completed",
"customer must be verified"
]
}
Convert to a DAG (Directed Acyclic Graph):
verify_transaction
↓
deduct_from_merchant ← verify_merchant
↓
credit_customer ← verify_payment_method
↓
send_email
↓
log_audit_trail
This is deterministic. No ambiguity.
The runtime executes the DAG:
Prove that execution matches specification:
Generate a proof that execution was faithful:
{
"specification": "Process refund",
"execution_trace": [
{"step": 1, "operation": "verify_transaction", "result": "success"},
{"step": 2, "operation": "deduct_from_merchant", "result": "success"},
{"step": 3, "operation": "credit_customer", "result": "success"},
{"step": 4, "operation": "send_email", "result": "success"}
],
"fidelity": "100%"
}