Next Steps
Once you can sign in, give Robot a meaningful request, and understand the discovery and coordination flow, you can explore the deeper parts of Craftly Robot.
Explore Robot Architecture
Learn how Robot is structured internally, including its current Mixture of Experts (MoE) architecture with 62 specialized experts and the components responsible for context, memory, agents, tools, execution, and verification.
The broader industry direction for agentic systems increasingly emphasizes explicit orchestration, tool execution, handoffs/delegation, guardrails, persistent context, and tracing rather than treating a model call as the entire application.
Explore the Agent Model
Learn:
- What an agent represents
- How an agent receives a goal
- How agents reason about tasks
- How agents use capabilities
- How agents coordinate with other agents
- How identity and permissions affect interaction
Explore Agent Discovery
Learn how Robot identifies potentially relevant people, services, and capabilities within the Craftly ecosystem.
This section can also explain how agent capabilities are described, matched, and selected.
Explore Agent-to-Agent Negotiation
Go deeper into how agents:
- Discover one another
- Establish communication
- Exchange requirements
- Maintain task context
- Check alignment
- Negotiate conditions
- Return results
Build with Craftly
For developers and researchers, explore how to create agents and connect them to tools and external capabilities.
Modern agent frameworks commonly expose tools, resources, prompts, and agent-to-agent delegation as separate building blocks; MCP, for example, standardizes server-side tools, resources, and prompts that AI applications can discover and invoke.
Craftly's own development model can build on similar principles while maintaining its own architecture and ecosystem.
Explore the Robot Network
The usefulness of agent-to-agent coordination grows as more people, services, and capabilities become available.
A larger network means a greater pool of potential participants for discovery and coordination.
The long term direction is a system in which:
The Craftly Robot Experience
Craftly Robot can be summarized by one central idea:
AI should not stop at generating an answer when the user's real need is to get something done.
Traditional conversational AI can be represented as:
Craftly Robot is being built around:
That is the foundation of Robot's real world AI direction.
The purpose is not to remove humans from important decisions.
It is to remove unnecessary coordination work between humans, software, services, and intelligent systems so that people can describe what they need and let agents handle more of the work required to move that objective forward.
- You define the goal.
- Robot understands it.
- Agents discover and coordinate the right capabilities.
- You remain in control when the outcome matters.