// Hello, World. I'm
Building intelligent automations that turn repetitive work into elegant, auditable pipelines. AI-native. API-first. Always production-ready.
I'm an AI automation engineer obsessed with turning manual, repetitive workflows into intelligent pipelines that reason, adapt, and deliver results — using LLMs as the brain and deterministic code as the muscle.
Every automation I build ships with Pydantic contracts (typed I/O on every tool), a ledger (full auditability and cost tracking), and vault-secured secrets. Not toy projects — production-grade systems that run at 2am without supervision.
from anthropic import Anthropic
from contracts import WorkflowInput, WorkflowOutput
from ledger import Ledger
class HEXAAgent:
"""Read spec → validate → run → audit."""
def run(self, spec: WorkflowInput) -> WorkflowOutput:
validated = spec.validate()
if validated.cost_estimate > self.threshold:
raise CostGuard(validated.cost_estimate)
result = self.execute_tools(validated)
self.ledger.record(result)
return WorkflowOutput.model_validate(result)Five production-grade automations — each with typed contracts, a cost ledger, vault-secured secrets, and a dry-run mode. No toy demos.
Got a workflow that needs automating? A process that should be smarter? A pipeline that keeps breaking? I'm interested. Let's talk.