Xpectrum AIThe word “agent” covers four genuinely different shapes of work. Picking the wrong one is why projects stall: an open-ended planner where a fixed path was needed, or a rigid flow where the work was never predictable. Start from the shape, then build.
Autonomous agent
Give it a goal instead of a route. It plans its own steps, hands subtasks to subagents with their own clean context, and works from its own knowledge base and instruction. Vision included.
For work with no fixed pathAI chatbot
The same shape as the autonomous agent, without tools or subagents. It answers from your client's knowledge base, follows the instruction you write, and has no action it could take by mistake.
For answering, not actingAgent flow
You define the classes a request can be routed into, each chained to its own knowledge base and tools, so a billing question never reaches the shipping tools. The LLM composes what comes back into a single response.
For production paths that need determinismMulti-state agent
Each state gives the user a set of options, answers on the one they pick, and waits before the next state opens. An intake or a booking gets gathered one choice at a time, and the run closes off at the end.
For dialogue that advances step by stepWhere it shows up
A support agent should not be rebuilt because the next client wants WhatsApp instead of web chat. The knowledge, tools, and memory stay put. Only the surface changes.
Next step
The second one is faster than the first, because the knowledge layer, tool definitions, approval gates, and traces already exist. Start with one client conversation and watch the whole loop run once.