MLOps news and analysis on Web Pulse: 742 curated articles tracking the latest MLOps developments, tools, and research, updated continuously from vetted sources.
InfoQ published a six-article series titled "Securing the AI Stack: From Model to Production" on June 5, 2026, outlining a roadmap for deploying resilient AI systems. The series identifies data poisoning, AI-driven phish…
Teams building AI applications are discovering that embedding pipelines for retrieval-augmented generation (RAG) systems are fundamentally a data engineering problem, not a new AI discipline. The process of ingesting, ch…
The InfoQ article series "Securing the AI Stack: From Model to Production" examines how AI's shift from experimentation to production has created a volatile security landscape defined by data poisoning, AI-driven phishin…
Mike, in collaboration with Anthropic's Claude, argues that code review does not scale to the volume of code produced by AI agents, and that validation must replace it as the primary safeguard. The engineer contends that…
A developer built a multi-tenant documentation system for CitizenApp using Astro Content Collections, replacing a headless CMS with static Markdown files versioned in Git. The system generates tenant-specific help docs a…
Stateflow Labs has released two open-source Python SDKs, ALGOgent Runtime and Adaptive Runtime, designed to solve state persistence and recovery problems in AI and automation systems. The lightweight ALGOgent Runtime pro…
OpenAI has released a guide detailing techniques for optimizing large language model outputs, including evals, prompt engineering, and fine-tuning. The company recommends developers continuously measure and tune model pe…
FerryAPI has published a template for AI API gateway fallback policies that classifies traffic into five tiers—critical user-facing, non-critical user-facing, internal automation, batch jobs, and experiments—each with it…
A developer spent a month attempting to build a system that could predict multi-agent AI failures before they occur, pre-registering all signals and metrics to avoid confirmation bias. The experiment failed cleanly, with…
FerryAPI has introduced a four-layer cost attribution stack for SaaS teams that call multiple LLM providers, enabling per-request tracking by tenant, feature, assistant, thread, and model. The system uses an OpenAI-compa…
A developer has released LLMhop, a stateless HTTP router that directs OpenAI-compatible API requests to the appropriate LLM inference backend based on the model name in the request body. The single-binary tool, built in …
A developer has outlined a practical method for auditing AI API costs by team and user, addressing the common problem of unexplainable invoice spikes. The approach requires request-level attribution, joining gateway trac…
Citigroup deployed an AI document-processing system that cut the document-review stage for U.S. account openings from roughly one hour to 15 minutes, according to Tim Ryan, the bank's head of technology. Ryan told Reuter…
FerryAPI has published a practical staging checklist for teams evaluating OpenAI-compatible AI API gateways, emphasizing that the gateway should allow apps to switch providers by simply changing the base URL and API key …
Intencion launched a product analytics tool designed specifically for AI agents in production, capturing every user interaction end-to-end including intent, agent steps, and outcomes. The tool installs with one line of c…
A developer built a cost-attribution system for LLM usage by tagging every gateway span with `team.id`, `project.id`, and `feature.id` alongside OpenInference token-count attributes, shipping those spans through an OTel …
Mendral, an AI DevOps agent developer, cannot provide a single accuracy metric for its CI failure diagnosis agent despite processing 36,564 investigations across 5.7 million CI jobs and 14.4 billion log lines in the last…
At Observe 2026, Arize AI launched new Arize AX capabilities designed to automate the agent improvement loop for production systems, including Signal for continuous failure detection, agent orchestration for automated in…
Agentic AI is driving enterprises to prioritize operations platforms as the most critical infrastructure layer, surpassing models and data science talent in importance. The shift to hybrid environments makes operational …
The New Stack published a guide detailing how Azure Kubernetes Service (AKS) can secure AI agent workloads on shared GPU clusters using four control layers: networking, policy enforcement, container image scanning, and r…