Layer 1: Context
Context is the source of truth agents need: policies, customer records, brand voice, historical outcomes, and operator overrides. Without it, agents hallucinate strategy.
We design context schemas per business—Book Blaster, a boring acquisition, an infra project—not one generic warehouse.
Layer 2: Agents
Agents are role-based workers with goals, guardrails, and memory. They plan, call tools, and escalate when judgment is required. They are not chat windows; they are jobs-to-be-done embodied in software.
Orchestration matters: handoffs between research, execution, and QA agents mirror how good human teams operate—without replicating department bureaucracy.
Layer 3: Tools
Agents must act in the real world: ad platforms, email, ticketing, spreadsheets, ERPs, calendars. Tools are APIs and integrations with explicit permissions.
We prefer narrow, reliable tools over monolithic “do everything” suites. Reliability beats demo magic.
Layer 4: Feedback
Feedback captures outcomes and human corrections. It powers evals, fine-tuning priorities, and operator trust. Without feedback, you cannot tell if Agents as a Service is working.
This stack is how Huluku Labs builds AI-operated companies. Everything else—brand, infra, boring businesses—is an application of the same architecture.