#productionai

Stop Building Fragile AI Agents Deploying AI agents into production requires careful...

A production-first checklist for self-hosting an OpenAI-compatible vLLM endpoint: auth, per-tenant quotas, streaming SSE, queueing, and redaction-safe logs.

Learn how to transition your local AI agent prototypes to production using NVIDIA Model-Optimizer, Paperclip, and Hindsight with robust sandbox security.

AI agents for DevOps and SRE are no longer hype in 2026—they are the operational standard. Microsoft saves 20,000 engineering hours per month with 1,300 Azure SRE agents, and PagerDuty resolves incide

LLM output is probabilistic by nature. Here's why production AI features need deterministic pass/fail rules around the model, not a bigger model, to ship reliably.

How to prevent AI agent failures in production with guardrails, not just prompts. A real case study from a recruiting automation project.

Token logs are table stakes. Here’s the minimum set of LLM application observability metrics for tools, RAG, caching, refusals, and privacy-safe logging that actually debugs production incidents.

My bot detected its own ban and then kept working for three and a half more days. Agent safety isn

Why 70% of AI projects never ship and how to build a production AI feature that actually works.

Inside RAG.NextUpgrad: hybrid dense + BM25 retrieval, cross-encoder reranking, and the confidence gate that refuses to answer on weak evidence.

DocuLens AI extracts, compares and compliance-checks business documents with schema-validated, deterministic scoring — not a free-text LLM summary.

There's a lot of excitement about what makes AI agents powerful — they reason, they choose their own...