Agents
The Collaborative Layer of humandbots
Agents are goal-driven bots that plan, remember, and collaborate. They translate human intent into coordinated action and amplify capability through partnerships with other agents.
Bots vs Agents
Bots are the execution layer. Agents are bots with goals, memory, and collaboration logic—built to partner with humans and other agents.
What makes an agent
- Clear goal and success criteria
- Memory of context across steps
- Planning and tool selection
- Collaboration with humans and peers
Why relationships matter
Agents are most powerful in networks. A strategist agent can frame intent, a builder agent can execute, and a reviewer agent can validate outcomes.
Explore agent dynamics
Designing reliable human-agent systems
The most effective agent systems behave like disciplined teams. Start by defining the human decision points, then surround them with agents that gather context, propose options, and execute approved steps. This keeps humans in control of outcomes while letting agents operate at speed. The goal is not full automation; it is a tighter loop between intent and execution.
Map responsibilities before you map tools. If two agents own the same decision, you will get conflicting outputs. If no agent owns a decision, the workflow stalls. A simple responsibility matrix—who sets the goal, who breaks it down, who executes, who reviews, who archives—prevents most coordination failures and makes handoffs predictable.
Finally, invest in feedback. Measure how often humans intervene, how many revisions are needed, and where confidence drops. Those signals tell you where the agent network needs better memory, tighter orchestration, or fewer steps. When every loop ends with a learning captured by the Archivist, the system improves over time.
If you are starting fresh, choose a single workflow and run it weekly. Consistency will reveal where the system breaks and where human judgment needs to be explicit.