Production AI
13 pieces on Production AI, including 1 step-by-step guide.
Guides
News & Analysis
We Planted 20 Wrong Figures for 4 LLM Editors. Here's What Survived
We replayed real edit prompts against Sonnet 4.6, DeepSeek V4 Pro, GPT-5.6 Sol and Gemini 3.1 Pro. Self-reported confidence told us nothing.
AI’s New Deployment Layer: Interfaces, Not Generated Text
OpenAI, Google, and Reka are competing for schemas, identity, and actuation—not chat quality. Machine-consumable actions now define AI deployment.
OpenAI Decisions API Beta: 10x Faster Typed Answers, $0.10 Input
OpenAI's gpt-6-luna Decisions endpoint returns probabilities, choices and scores at $0.10 per million input tokens, with no output fees and a vendor-stated 10x speedup.
Uber Eats Cuts Search Latency 50% With Pipeline Rewrites, Not New Models
Uber reports a 50% cut in Uber Eats search latency by redesigning retrieval, hydration, ranking, and ad-serving — no model changes required.
Constrained Inference Beats Generation on Speed, Cost, and Predictability
Three September 2026 releases show that replacing open-ended token generation with deterministic or classification-style inference produces faster, cheaper, more reliable AI systems.
Infrastructure Rewrites, Not Model Weights, Drive 2026 AI Gains
Four independent engineering efforts show runtime routing, service rewrites, and kernel fusion outperforming model compression on production AI systems.
Production AI Fails on Architecture, Not Model Intelligence
Enterprise AI deployments stall because the harness breaks, not the model. Three failure modes prove why domain-specific architecture beats scaling.
Five Context Failure Modes That a Model Upgrade Cannot Fix
Redis advocate Ricardo Ferreira catalogues five production context failures and the pipeline architecture—not model swaps—that resolves them.
Five MLOps Assumptions That Silently Pass Failed Agent Runs
MLOps monitoring reports healthy on runs that failed. Here are the five structural assumptions that break when a model starts calling tools.
Pipeline Architecture, Not Better Models, Drives 2026's Biggest AI Gains
Four independent deployments—AWS, Cloudflare, Fanatics, and async Bedrock—achieved step-change results by decomposing monolithic agents, not upgrading models.
LLM Judge Approved Its Own Errors: Three Biases Explained
A production SQL pipeline approved wrong queries for weeks. The judge and generator shared the same model — and that structural flaw caused the incident.
Stop Hand-Tuning Prompts: A Production Workflow for Automated LLM Optimization
Move beyond trial-and-error prompting with a measurable workflow for evaluating and optimizing LLM prompts in production systems.