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QCon AI Highlights Engineering Challenges For Production
7.1
QCon AI Boston's early program, scheduled for June 1–2, 2026, spotlights the engineering work required to move AI from demos to reliable production systems. Speakers from Red Hat AI, Redis, Dataiku, RelationalAI, Netflix, Broadcom, DoorDash, Microsoft and Amazon will address themes including context engineering, agent explainability, advanced reasoning beyond RAG, security/governance, and GenAI platform infrastructure.
Key Points
- 1Emphasize context engineering over prompting to ensure models work under latency and limited-context constraints
- 2Highlight need for agent explainability and tool-call visibility to prevent cascading downstream failures
- 3Advocate platform features, retries, fallbacks, prompt versioning, and cost tracking for operational reliability at scale
Scoring Rationale
Practical and broadly relevant engineering coverage; limited novelty beyond a conference program and shallow technical depth.
Sources
Public references used for this report.
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