This experiment explores a different approach to interact with EA4ALL.AI capabilities using a personal architect assistant who can autonomously assign tasks to the best fit agent for the job asked by the user.
Why This Exists
Enhance user experience by providing a more personalised and interactive way to interact with EA4ALL.AI capabilities.
- Automate and accelerate core EA activities, turning manual work into intelligent, adaptive workflows.
- Empower architects to focus on strategic innovation, collaboration, and value-driven design.
- Synthesizes complex business and technical knowledge.
- Automates documentation, modelling, and repetitive tasks.
- Provides natural language access to architectural insights.
- Enhances collaboration, scalability, and adaptability.
- Supports design exploration, decision validation, and stakeholder alignment.
- Free up architects’ time to focus on strategy and innovation.
What This Experiment Explores
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Iteration 1: Safety checking, Routing, Application Memory, Agentic Workflow, Multi-Agents, ReAct, RAG, Evaluations
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Iteration 2: Increased autonomy, Cashing, Short-term Memory
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Iteration 3: Long-Term Memory, Personalisation, A2A
Current Status
This experiment is in the Validating phase and continuous evolution, with active UI refactoring and ongoing exploration of agent behaviors and orchestration patterns.