Speaker
Abstract
The session explains why document AI that works in demos can fail in production: document structure can be lost during ingestion, rendering can break on edge cases, and extraction can vary across runs. When agents make routing or approval decisions, teams also need governance. The proposed foundation is deterministic document processing, confidence based routing that escalates uncertain cases, and audit trails built into the infrastructure.
Sponsored session
Session sponsored by
Nutrient SDKs let developers embed secure, high-performance document viewing, editing, signing, and AI-powered processing into any app — with full UI control and deployment flexibility.
$3,250, Conference (3 days). Current pricing ends November 20th. All pass options.
QCon San Francisco 2026 is a three day conference for senior software engineers, architects and team leads. An international program committee of working engineers selects every session. Patterns and practices, not products and pitches.
Slides & video
Video Not available
Part of the track
Sponsored Solution Track IIIFrom the same track
Tuesday 17 November
10:35 Pacific L-O Sponsored Feeling Faster Isn’t a Metric: Measuring AI’s Real Engineering Impact Jeremy Castile VP of Developer Research @GitKraken AI adoption in engineering is settled. In GitKraken’s 2026 State of AI in Engineering survey of 554 developers and engineering leaders, 96% of teams had adopted AI coding tools and 84% of developers said they feel more productive. Only about one in five can actually measure the impact. 11:45 Pacific LM Sponsored Notes From 300 Installs Inside Someone Else's Cloud Adam Hicks Senior Solutions Architect @Groundcover We run our storage and query backend inside our customers' own VPCs. They own the infrastructure. We own the pager. I'm the person who helps installs it, so I've watched this architecture meet a few hundred different production Kubernetes environments and I've kept notes on what went wrong. 13:35 Pacific LM Sponsored Why Your Document AI Fails in Production — And How to Fix the Infrastructure Underneath It Pavitter Josan Solutions Engineer @Nutrient The session explains why document AI that works in demos can fail in production: document structure can be lost during ingestion, rendering can break on edge cases, and extraction can vary across runs. When agents make routing or approval decisions, teams also need governance. 14:45 Pacific LM Sponsored Trust, but Verify: Delivering Quality with Agentic Workflows Adrian Hatch Solutions Engineer @Antithesis In spite of all the recent panic, nothing has really changed about software development. We’re worried about agents being unreliable. Newsflash: human devs are too. We’re worried about agents producing more code than we can read, but did you ever really do all your reviews within 24 hours? 15:55 Pacific LM Sponsored Your Agents Have Amnesia: Lessons from Building a Memory Layer for Multi-Agent Systems Hari Krishna Sunder Architect @YugabyteDB Multi-agent systems have a data problem nobody warns you about. Agent B sees Agent A's final output and nothing else; the reasoning, the dead ends, and whatever Agent A figured out three steps in all get thrown away. 17:05 Pacific LM Session Sponsored Session Details coming soon!