---
title: "From framework to runtime: running agents with Foundry Agent Service"
category: "talks"
date: "2026-06-30"
time: "10:45am-11:05am"
track: "Track M"
room: "Track M"
speakers: ["Tina Manghnani", "Keiji Kanazawa"]
sourceLabels: ["Official conference schedule", "Public YouTube metadata"]
scheduleTrack: "Track M"
scheduleRoom: "Track M"
scheduleLabels: ["Track M", "Track M", "sponsor", "confirmed"]
---
# From framework to runtime: running agents with Foundry Agent Service

## Conference Context
- Date/time: 2026-06-30 · 10:45am-11:05am
- Track/room: Track M · Track M
- Speaker(s): Tina Manghnani, Keiji Kanazawa
- Session type/status: sponsor · confirmed

- Track: Track M
- Room: Track M
- Session type: sponsor
- Status: confirmed

## Session Description
See how agents move from frameworks into production systems. Learn how Foundry Agent Service provides hosted execution, scaling, and lifecycle management—combining models, tools, and orchestration into a production-ready runtime.

## Media Evidence
[AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft](https://www.youtube.com/watch?v=JhJKgRAmfIU) (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions).

- Source video: `youtube-JhJKgRAmfIU`
- Slide deck: [[youtube-JhJKgRAmfIU-dense-slides|Dense Slides: AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft]] — 4 visible slide image(s); 4 HTML recreation(s).
![[assets/dense-slides/JhJKgRAmfIU/slide-001.jpg]]
![[assets/dense-slides/JhJKgRAmfIU/slide-002.jpg]]
![[assets/dense-slides/JhJKgRAmfIU/slide-003.jpg]]
- Additional slide evidence: [[youtube-JhJKgRAmfIU-slides|Slides: AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft]], [[youtube-JhJKgRAmfIU-reconstructed-slides|Reconstructed Slides: AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft]]
- Slide-derived themes for `youtube-JhJKgRAmfIU`: does, handle, loot, bank.

## Evidence Graph
This evidence graph is generated from currently linked source material: official schedule text, related video pages, cached transcripts, visible slide text, dense/reconstructed slide pages, and AI slide-classification audits.

### Media Signals
- `youtube-JhJKgRAmfIU` — 2 slide-derived text signals
- Slide-derived themes for `youtube-JhJKgRAmfIU`: does, handle, loot, bank.
- Evidence links for `youtube-JhJKgRAmfIU`: [[youtube-JhJKgRAmfIU]], [[youtube-JhJKgRAmfIU-slides]], [[youtube-JhJKgRAmfIU-dense-slides]], [[youtube-JhJKgRAmfIU-reconstructed-slides]]

### Agent Reading Notes
Use these signals to refine the synopsis, topic links, people/company context, and method notes. If a source is a related external video rather than an exact official recording, keep it framed as supporting evidence.

## Transcript Status
Related video transcript availability: English auto-captions. Treat this as supporting context, not a recording of this exact scheduled session unless later confirmed. Not fetched yet.

## People
- [[tina-manghnani]]
- [[keiji-kanazawa]]

## Supporting Slides
- [[youtube-JhJKgRAmfIU-slides]] — extracted from the related public AI Engineer video.

## Slide Evidence
- Slide-only cropped deck: [[youtube-JhJKgRAmfIU-dense-slides]] (4 viable slide images).
- Related slide/OCR pages:
- [[youtube-JhJKgRAmfIU-dense-slides]]
- [[youtube-JhJKgRAmfIU-reconstructed-slides]]
- [[youtube-JhJKgRAmfIU-slides]]
- Slide-derived terms: `microsoft`, `azure`, `azure_ai_project_endpoint`, `foundry`, `loot`, `bank`, `initialize`, `service`, `endpoint`, `api_key`, `redteamplugin`, `problims`, `output`, `termnal`, `ports`, `node`, `smol`, `awss`

## Attendance Visibility
No high-confidence attendance icon signal is shown for this talk. The sampled video evidence was either low confidence, source-proxy-only, or did not expose a clear audience view.

## Synthesis
### Synthesized Breakdown
# From framework to runtime: running agents with Foundry Agent Service ## Conference Context - Date/time: 2026-06-30 · 10:45am-11:05am - Track/room: Track M · Track M - Speaker(s): Tina Manghnani, Keiji Kanazawa - Session type/status: sponsor · confirmed - Track: Track M - Room: Track M - Session type: sponsor - Status: confirmed ## Session Description See how agents move from frameworks into production systems. Learn how Foundry Agent Service provides hosted execution, scaling, and lifecycle management—combining models, tools, and orchestration into a production-ready runtime. ## Media Evidence [AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft](https://www.youtube.com/watch?v=JhJKgRAmfIU) (speaker-match related prior/adjacent AI Engineer video; captions: English auto-captions). - Source video: `youtube-JhJKgRAmfIU` - Slide deck: [[youtube-JhJKgRAmfIU-dense-slides|Dense Slides: AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft]] — 4 visible slide image(s); 4 HTML recreation(s).

### Speaker And Company Context
- [[tina-manghnani|Tina Manghnani]] — Product Manager at [[microsoft|Microsoft]].
- [[keiji-kanazawa|Keiji Kanazawa]] — Principal Product Manager at [[microsoft|Microsoft]].

### Topics Covered
- [[ai-sandboxes]]

### Derived Links And Source Material
- [[youtube-JhJKgRAmfIU]] — related YouTube source page.
- [[youtube-JhJKgRAmfIU-slides]] — slide evidence.
- [[youtube-JhJKgRAmfIU-reconstructed-slides]] — slide evidence.
- [[youtube-JhJKgRAmfIU-dense-slides]] — slide evidence.

### Novel Concepts / Clever Methods
- No highlighted novel concept has been detected yet.

### Evidence Boundary
This synthesis is based on the official schedule and linked source pages. It should be revisited when exact session recordings or transcript-backed secondary sources are available.