The runtimes, protocols, and plumbing beneath agents. · 55 articles
When you sell an AI agent as a service, the version you shipped last Tuesday is the contract. The moment a prompt, a model, or a tool schema
An agent mesh is an infrastructure pattern that treats autonomous AI agents the way a service mesh treats microservices: a dedicated layer t
Persistent memory is what makes an AI agent feel useful instead of amnesiac, but every fact an agent remembers is a fact someone now has to
If you're building an agentic AI service, you'll choose between a framework (a library you wire together yourself, like LangGraph or the Ope
Agents don't use inference the way chatbots do. A single autonomous task can fire dozens of model calls, lean hard on prompt caching, and de
Agent telemetry is the structured record of what an autonomous agent did, why, and at what cost, and the industry is converging on OpenTele
Most agent demos run synchronously: a request comes in, the agent thinks, calls a few tools, and returns an answer in one breath. That model
Most teams blame "slow models" for slow agents, but profiling almost always tells a different story. In a typical multi-step agent run, raw
Most people assume the model API is the whole cost story for Agentic AI-as-a-Service. It isn't. When you actually decompose a running agent'
A supervisor-agent architecture puts one coordinating agent in charge of a team of specialized worker agents. The supervisor reads the task,
Traditional CI/CD assumes deterministic code: the same input yields the same output, so a green test suite means you can ship. Agents break
Autonomous AI systems break the security assumptions most infrastructure was built on. A traditional service does what its code says; an age
Caching is the single highest-leverage cost lever for agentic AI-as-a-Service, and most teams leave 40-90% of the savings on the table. The
Most agent stacks bolt authentication on at the end, reusing a service account and a static API key. That works in a demo and quietly become
Durable execution engines give AI agents a memory of where they were when something broke. They persist every step of a workflow so that whe
Computer-use agents are AI systems that operate software the way a person does, moving a cursor, clicking buttons, typing into fields, read
During a gold rush, the people who reliably get rich aren't the prospectors, they're the ones selling shovels, denim, and railroad tickets.
Agent workloads break the assumptions inference stacks were built on. A chatbot makes one call and waits for a human; an agent makes dozens
Most teams reach for fine-tuning when their agent misbehaves, then spend weeks training a model that still fails the same way. The hard trut
Basic RAG, embed a query, pull the top-k chunks, stuff them in the prompt, was built for chatbots that answer one question and forget you
If you're building agents-as-a-service in 2026, the framework you pick quietly decides your cost structure, your debugging ceiling, and how
Agent sandboxing is the isolation layer that lets an autonomous AI agent execute untrusted code, browse the web, and call tools without givi
Most agent failures aren't model failures. They happen in the messy seam between the model deciding to call a tool and that tool actually ru
Most demos of agentic AI run for ninety seconds. Real work runs for hours, days, or weeks, and that gap is where the engineering actually l