Connecting the AI Loop with CoreWeave Forge
AI Field Day 9
•
24m
Shane Robbins from CoreWeave discusses the fundamental shift occurring as artificial intelligence initiatives transition from experimental pilots to production deployments. While pilot projects permit flexible timelines, limited users, and manual oversight, production applications demand rigorous reliability at scale, strong governance, security, and continuous improvement. Traditional software development operates linearly through building, deploying, and monitoring, whereas production artificial intelligence functions as a continuous cycle where deployment initiates an ongoing feedback loop. As a wider variety of businesses deploy commercial agents and customize models, relying on a patchwork of disconnected tools has become a critical liability that causes teams to lose vital signals and operational data between handoffs. The continuous operating cycle is defined by five key stages comprising run, observe, curate, improve, and evaluate. During the run and observation phases, instrumentation and tracing capture operational data to monitor how models and agents behave under real customer loads. Without effective curation and tracing, evaluations rapidly grow stale and prevent developers from understanding how applications are performing. In the improvement and evaluation stages, maintaining lineage and reliable benchmarks ensures that every newly deployed iteration builds directly on prior learnings, allowing engineers to pinpoint anomalies, refine models through post-training, and avoid repeating previous errors. To unify these fragmented processes, CoreWeave introduced CoreWeave Forge, an integrated environment designed to manage the full development and deployment loop. Built using technology from acquisitions and internal development, Forge brings together evaluation, tracing, post-training, and inference services while remaining completely agnostic to specific clouds, frameworks, or hardware models. Targeted at developers building or customizing models and agents, the platform features tools such as Aria to detect interactions that violate operational guardrails. Forge provides workflow automation and an available thirty-day free trial, allowing enterprises to eliminate manual development overhead and iterate on workloads without being locked into a single compute provider.
Recorded live in Santa Clara, California on October 14, 2026 as part of AI Field Day 9. Watch the full presentation at https://techfieldday.com/appearance/coreweave-presents-at-ai-field-day-9/ or visit https://coreweave.com/forge or https://techfieldday.com/event/aifd9/ for more information.
Recorded live in Santa Clara, California on October 14, 2026 as part of AI Field Day 9. Watch the full presentation at https://techfieldday.com/appearance/coreweave-presents-at-ai-field-day-9/ or visit https://coreweave.com/forge or https://techfieldday.com/event/aifd9/ for more information.
Up Next in AI Field Day 9
-
Post-Training on CoreWeave Forge
David Corbitt introduces CoreWeave Forge post-training, explaining how his background co-founding OpenPipe led to CoreWeave acquiring the company to bring accessible fine-tuning to enterprises. Forge provides an integrated environment where observability, post-training, and inference work togethe...
-
CoreWeave Inference From Model Traini...
Nisha Nadkarni, a specialist field engineer at CoreWeave, delivered a presentation on CoreWeave inference, detailing the process from model training to production scale serving. She introduced CoreWeave Forge as an additional development layer built upon CoreWeave's core compute offerings, design...
-
CoreWeave Agent Lens Intelligent Obse...
CoreWeave Agent Lens provides intelligent observability purpose-built for enterprise scale, monitoring agents to diagnose and fix issues. It is part of Forge, CoreWeave’s development layer for building and improving models and agents, specifically focusing on the agent development side. Forge uni...