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Travis Muhlestein PRO

TravisMuhlestein

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posted an update 2 days ago
🚀 GoDaddy ANS API Now Live — Bringing Verifiable Identity to the Agent Ecosystem We just launched the Agent Name Service (ANS) API) publicly, along with the new ANS Standards site, extending decades of GoDaddy internet-scale trust into the emerging world of autonomous agents. ANS provides cryptographically verifiable identity, human-readable names, and policy metadata for agents — designed to work across frameworks like A2A, MCP, and future agent protocols. What’s new: 🔹ANS API is open to all developers — generate a GoDaddy API key and start testing registration, discovery, and lifecycle ops. 🔹ANS Standards Site is live — includes the latest spec, architecture, and implementation guidance. 🔹Protocol-agnostic adapter layer — supports interoperability without vendor lock-in. Why it matters: As autonomous agents continue to proliferate, we need neutral, verifiable identity to prevent spoofing, trust rot, and fragmented ecosystems. ANS brings DNS-like discovery and PKI-based validation to the agent economy. 🔗 Links Standards & docs: https://www.agentnameregistry.org/ API keys: https://developer.godaddy.com/keys Repo: https://github.com/godaddy/ans-registry PR: https://aboutus.godaddy.net/newsroom/news-releases/press-release-details/2025/GoDaddy-advances-trusted-AI-agent-identity-with-ANS-API-and-Standards-site/default.aspx Would love to hear thoughts from the community: What should a universal agent identity layer guarantee — and what should it avoid?
posted an update 11 days ago
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
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