LiteLLM is the known option. agentgateway is the open one.
Comparing LiteLLM and agentgateway for enterprise AI platforms: licensing boundaries, security advisories, ops footprints, and open governance.
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Pragmatic field notes on AI agents, MLOps, cloud architecture, and engineering systems.
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Comparing LiteLLM and agentgateway for enterprise AI platforms: licensing boundaries, security advisories, ops footprints, and open governance.
AI coding agents amplify repository friction. How we redesigned an MLOps codebase around deterministic single-command gates, SQLite isolation, and AGENTS.md.
Running a remote Model Context Protocol (MCP) server behind multiple instances presents immediate infrastructure challenges.
A coding agent is only as useful as the spec you give it. That sentence sounds like a truism until you watch it play out for an afternoon.
AI Coding — or Spec-Driven Development — is a recent trend that amazes as much as it scares IT engineers.
Bridge the gap between engineering specs and AI agents using Agent Skills. Learn to inject ‘Senior Engineer’ context for production MLOps.
AI agent platform architecture in 7 layers, from interaction and development to observability and trust: how to serve, secure, and monitor enterprise agents.
Building AI applications is incredibly exciting. But let’s be honest: getting started can be challenging, especially in large organizations.
Tame your Python chaos! Learn how pyenv simplifies managing Python versions for AI/ML & MLOps, ensuring smooth, reproducible development.
This article dives deep into the essential tools and practices for achieving comprehensive observability in your AI/ML projects.
The MLOps Coding Course is an open-source resource specifically designed to bridge the gap between data science and software engineering.
In this article, I will outline the steps for configuring VS Code for data scientists and machine learning engineers.
Kubeflow Pipelines (KFP) is a powerful platform for building machine learning pipelines at scale with Kubernetes.
A fundamental trade-off that affects the design of programming languages and the success of software projects.