Markdown source

Vertical Mobility: Building an AI Inference Platform That Scales from MVP to Trillion-Parameter Workloads

Conference Context

Session Description

The future of AI inference is not one-size-fits-all. This talk explores a multi-tiered architecture that supports the full AI lifecycle, from rapid, pay-per-token experimentation to dedicated, SLO-bound production and extreme-scale, self-managed deployments. Learn about lessons learned from CoreWeave’s inference stack as performance, cost, and control requirements evolve.

Media Evidence

No related AI Engineer channel video found yet.

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

No linked video, transcript, or slide source has been attached yet.

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

No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

People

Notes

Synthesis

Synthesized Breakdown

Vertical Mobility: Building an AI Inference Platform That Scales from MVP to Trillion-Parameter Workloads ## Conference Context - Date/time: 2026-07-01 · 12:05pm-12:25pm - Track/room: Inference · Track 9 - Speaker(s): Rita Zhang, Sitanshu Gupta - Session type/status: session · confirmed - Track: Inference - Room: Track 9 - Session type: session - Status: confirmed ## Session Description The future of AI inference is not one-size-fits-all. This talk explores a multi-tiered architecture that supports the full AI lifecycle, from rapid, pay-per-token experimentation to dedicated, SLO-bound production and extreme-scale, self-managed deployments. Learn about lessons learned from CoreWeave’s inference stack as performance, cost, and control requirements evolve. ## Media Evidence No related AI Engineer channel video found yet.

Speaker And Company Context

Topics Covered

Derived Links And Source Material

Novel Concepts / Clever Methods

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.