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Building Smarter AI Agents: A Tool-Based Architecture for Modularity and Trust
Over the past year, our AI engineering team at GoDaddy has been rethinking how to make agent systems more modular, transparent, and production-ready. Instead of viewing an AI agent as a monolithic process, we’ve decomposed it into four core tools that separate decision-making from execution — a design that’s proving critical for scale and observability:
🧩 MemoryTool – maintains persistent context and user continuity
✅ CompletionTool – determines when a task is truly complete
💬 UserInteractionTool – manages clarifications, approvals, and confirmations
🔁 DelegationTool – enables agents to hand off tasks to other agents or humans
This approach makes every step of an agent’s workflow explicit, testable, and auditable, allowing us to scale AI systems in production with higher confidence. We see this as a step toward a more open, composable agent ecosystem — one where frameworks can interoperate and agents can build trust through transparency and version control.
Read the full write-up here → Building AI Agents at GoDaddy – An Agent’s Toolkit https://www.godaddy.com/resources/news/building-ai-agents-at-godaddy-an-agents-toolkit
We’d love to collaborate and exchange ideas with the community:
- How are you designing modular agent architectures?
- What design patterns or abstractions have helped you manage agent complexity?
Let’s build smarter, safer agents together.
#AI #Agents #Architecture #MachineLearning #OpenSource #AgentFrameworks #TrustInAI
Over the past year, our AI engineering team at GoDaddy has been rethinking how to make agent systems more modular, transparent, and production-ready. Instead of viewing an AI agent as a monolithic process, we’ve decomposed it into four core tools that separate decision-making from execution — a design that’s proving critical for scale and observability:
🧩 MemoryTool – maintains persistent context and user continuity
✅ CompletionTool – determines when a task is truly complete
💬 UserInteractionTool – manages clarifications, approvals, and confirmations
🔁 DelegationTool – enables agents to hand off tasks to other agents or humans
This approach makes every step of an agent’s workflow explicit, testable, and auditable, allowing us to scale AI systems in production with higher confidence. We see this as a step toward a more open, composable agent ecosystem — one where frameworks can interoperate and agents can build trust through transparency and version control.
Read the full write-up here → Building AI Agents at GoDaddy – An Agent’s Toolkit https://www.godaddy.com/resources/news/building-ai-agents-at-godaddy-an-agents-toolkit
We’d love to collaborate and exchange ideas with the community:
- How are you designing modular agent architectures?
- What design patterns or abstractions have helped you manage agent complexity?
Let’s build smarter, safer agents together.
#AI #Agents #Architecture #MachineLearning #OpenSource #AgentFrameworks #TrustInAI