AI Assistants insights
194 results found
Partner POV | Mastering Agentic Techniques: AI Agent Evaluation
AI model and agent evaluations differ fundamentally: models are assessed on static tasks for cognitive potential, while agents are evaluated on dynamic, end-to-end workflows. This article outlines five practical tips for agent evaluation, emphasizing task success, trajectory analysis, tool usage, reasoning quality, and transparent evaluation from inception.
Partner POV | Advancing AI Infrastructure for Agentic AI with NVIDIA DOCA In-Silicon Security
The AI era is driving a new class of infrastructure: AI factories that transform data into intelligence for autonomous AI agents operating at unprecedented scale. Powered by accelerated computing, AI factories enable enterprises to train, fine-tune, and deploy AI with greater speed and efficiency.
LLMaaS ChatBot
Compare large language models side by side using WWT's AI Proving Ground GPU cluster. Send the same prompt to multiple models at once and evaluate their responses in real time — measuring response speed, reasoning quality, and output style across leading open-source and proprietary models.
No setup required. The lab environment connects automatically to the LLMaaS AI Gateway, giving you direct access to production-grade inference endpoints used by WWT's AI engineering teams.
Sandbox Lab
•Introductory
WWT & NVIDIA NemoClaw Hackathon
40 engineers. 7 teams. One mission: build real, production-ready AI agents using NVIDIA NemoClaw Blueprints.
Copilot Cowork: Now generally available with multi-model capabilities, browser use and more
In this video, Charles Lamanna, EVP of Copilot, Agents, and Platform, shows Copilot Cowork's multi-model capabilities as he walks through the same steps he follows when prepping for a meeting with a customer — pulling deal status, risks, and open support cases from his CRM and work data, building an account summary and a visual map of his key contacts, and logging follow-ups back into the CRM. He then has Cowork draft an outreach email using a skill that makes it sound just like him. To close out the day, he has Cowork use the Edge browser to find availability and book a dinner reservation in real time — all without leaving Copilot Cowork.
Partner POV | AI Security is an Architectural Decision
Why governance must scale before AI Autonomy
Copilot Cowork goes GA. Is your organization ready to delegate work to AI?
Microsoft's Copilot Cowork is now generally available — and it marks a bigger shift than most organizations realize. Explore what changes when AI moves from assisting work to executing it, and what IT leaders must address around data governance, permissions, and accountability before scaling.
How to Choose the Right LLM
This hands-on lab teaches enterprise engineers how to systematically evaluate, benchmark, and select optimal large language models for distinct steps inside an agentic control plane.
The Bottleneck Just Moved — It Didn't Disappear
Most organizations adopt AI for development and discover that the bottleneck didn't disappear; it moved. Faster coding flows into the same constrained review, testing and release processes. DevOps taught us to map the whole value stream before optimizing any single stage. AI Native Engineering demands the same discipline, end-to-end, with the right operating model in place before you can measure success.
Cisco Live 2026: The Agentic Era is Here
Cisco Live 2026 unveiled Cisco's AgenticOps era, where AI agents work alongside IT teams, generating 450% more network traffic. Cisco's vertically integrated platform, Cloud Control, unifies management across domains, enabling humans and AI to collaborate seamlessly. This marks a transformative shift in IT operations, emphasizing autonomy with human oversight.
The Great Unlock: An Executive Guide to AI-Native Engineering
How C-suite leaders can turn AI-native engineering into faster execution, stronger customer outcomes and durable competitive advantage.
Cisco Live 2026 Signals a New Phase of Enterprise AI: Operational Reality
As AI agents, cyber risk and infrastructure demand accelerate, IT leaders must move beyond experimentation and build the visibility, agility and resilience needed to operate at AI speed. In this episode of the AI Proving Ground Podcast, we dive into the key lessons learned at Cisco Live 2026 and how enterprise business and technology leaders should think about them moving forward.