A product discussed on AI Engineer.

Foundry Local: Cutting-Edge AI experiences on device with ONNX Runtime/Olive — Emma Ning, Microsoft
Jun 27, 2025 · 22:52
Emma Ning, Principal PM at Microsoft, presents Foundry Local, a platform for building cross-platform on-device AI applications using ONNX Runtime and Olive. She argues local AI is essential for low-bandwidth, privacy-sensitive, cost-efficient, and real-time latency scenarios, noting that modern hardware and optimized models like Phi-4-mini and DeepSeek make it viable. Ning demonstrates Foundry Local's CLI, model benchmarking (Qwen 1.5B at 90 tok/s vs. Phi-4-mini with richer output), and a cross-platform document summarization app built with JavaScript SDK, running identically on Windows and macOS. She also previews a local agent with MCP servers (file system and OCR) that extracts receipt totals using Phi-4-mini. Customer testimonial from Sava (CEO of Pieces) highlights improved memory management and tokens-per-second, while another partner underscores ease of install and hybrid cloud-local solutions.

AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft
Jun 27, 2025 · 19:31
Keiji Kanazawa and Nagkumar Arkalgud of Microsoft present the AI Red Teaming Agent in Azure AI Foundry, arguing that adversarial testing is essential for building trustworthy AI agents. Nagkumar demonstrates the tool: it runs scans against RAG apps or models directly, using attack strategies like Caesar encoding and Base64 to simulate adversarial prompts across four risk categories (violence, hate and fairness, etc.). In a demo with GPT-4.0 with full guardrails, no attacks succeeded; switching to Phi-3 without guardrails yielded 5 out of 40 successful attacks in hate and fairness. The tool integrates with Azure AI Foundry's content filters, which apply both input and output guardrails, allowing engineers to iteratively test and mitigate vulnerabilities. The talk emphasizes that red teaming should be part of a broader risk mapping and evaluation lifecycle, and that trust is a team sport requiring collaboration between engineers and security experts.

Agentic Excellence: Mastering AI Agent Evals w/ Azure AI Evaluation SDK — Cedric Vidal, Microsoft
Jun 27, 2025 · 20:01
Cedric Vidal, Principal AI Advocate at Microsoft, demonstrates how to systematically evaluate AI agents using the Azure AI Evaluation SDK and AI Toolkit. He argues that evaluation must start early, covering four layers: model/safety system, system message, grounding, and user experience. He shows spot-checking models side-by-side in VS Code, building a web-scraping agent with Playwright MCP, and running batch evaluations with built-in quality and safety metrics like groundedness and fluency. Vidal also covers multi-turn and multimodal evaluation, using a violent image example where the SDK returned a score of 4 out of 5, allowing teams to set custom thresholds based on application context.

Building Code First AI Agents with Azure AI Agent Service — Cedric Vidal, Microsoft
Jun 27, 2025 · 1:54:06
Cedric Vidal, Principal AI Advocate at Microsoft, demonstrates building code-first AI agents with Azure AI Agent Service, using function calling, code interpreter, file search, and Bing grounding for a sales analysis use case. He creates a conversational agent that queries SQLite, generates pie charts from Python code, and blends product PDF data with relational data. The workshop explains stateful agents, tool routing (LLM generates JSON to call functions), and the limits of single-step agents versus multi-agent orchestration with AutoGen. Cedric addresses when to use Agent Service (managed persistence and tools) versus raw LLM endpoints, and covers MCP servers as a tool lifecycle manager. Key insights include using instructions to ground agent behavior and the need for eval frameworks for agent quality.
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