Models are not the moat
Any team can call the same foundation models. Features that were novel six months ago become table stakes. Competing on “we use AI” is already meaningless.
What compounds is context: customer history, SKU-level margins, brand voice, escalation rules, local regulations, and what happened the last hundred times you ran a workflow.
The context layer
We treat context as infrastructure—not a one-off RAG demo. Structured and unstructured sources feed a layer agents read and write to: CRM, ads, support, finance, and operator notes.
Book Blaster’s context is a book and its market. A laundromat’s context is machines, routes, and customer messages. A data center’s context is load, contracts, and community commitments.
Feedback closes the loop
Context without feedback rots. Every agent action should generate signal: did the campaign work, did the ticket resolve, did the owner approve the draft? That signal updates the context layer so the next run is better.
This is why Huluku Labs invests in operating systems, not wrappers. The moat is the loop, not the prompt.