Anapoly Notebook | Digital Garden
Status: 🔸 Seed → ✅ Growing → 🔸 Well-formed → 🔸 Fruitful → 🔸 Retired
Transparency label: AI-assisted
Hybrid AI Systems
Businesses are moving away from giant, general-purpose, Large Language Models toward hybrid AI systems which offer a better balance of cost, speed, and control. A hybrid system combines different kinds of AI for different jobs. Small, specialised models handle most routine tasks because they are fast, cheap, and can be tailored to the business. A larger model is used only when something genuinely difficult needs deeper reasoning. An agent layer sits above them to coordinate the steps, call the right model at the right time, and hand decisions back to a human when judgement matters.
A hybrid AI system gives the business control over its own data. The agent and the small models usually run inside the organisation’s chosen environment, so sensitive information stays within its security boundary. Only specific tasks are sent to a larger external model, and only when policy allows it. This keeps day‑to‑day processing private while still giving access to more powerful models when needed.
For a small business, tools like Zapier provide a comparatively simple way to build such a system because they can execute the agent’s decisions without any bespoke engineering. Zapier is a straightforward automation platform. It connects apps together and runs simple “when this happens, do that” workflows using triggers and actions. It executes tasks like creating records, sending emails, or updating calendars. Zapier's recent AI features make workflow building easier, and they let you add a language‑model step when needed. These additions improve usability, but Zapier provides the plumbing, not the intelligence.
An agent is the part of the system that handles the flow of work, keeps track of what it has done, enforces rules, and sends things to a human when approval is needed. It isn’t itself a model; it is traditional, deterministic software. It provides the organising layer that turns AI capabilities into a controlled, reliable workflow. None of this layer relies on AI, so the uncertainty sits in the models the agent calls, not in the agent itself.