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Sebastian Maniak on running AI agents in production — agentgateway, kagent, MCP, A2A, and the Kubernetes plumbing that keeps them fast, observable, and safe.
First Steps: agentgateway, F5 AI Guardrails, and the Enterprise UI
The previous post covered the new hard spend limits in Enterprise agentgateway v2026.6.3: model cost catalogs, dollar or token budgets, and a real 429 when a budget is exhausted. That solves the FinOps side of AI …
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View the full archive →Hard Spend Limits for LLM Traffic: AI Budgets in Enterprise AgentGateway v2026.6.3
Enterprise AgentGateway v2026.6.3 shipped on July 1st with a changelog line that FinOps-minded platform teams have been waiting for: Enterprise Budgets and …
Three Ways to Combine agentgateway with F5 AI Guardrails (and Where F5 Distributed Cloud Fits)
F5’s acquisition of CalypsoAI gave enterprises something a lot of security teams have been asking for: a dedicated AI runtime security layer — F5 AI …
Suspend & Resume Stateful Agents: kagent on Agent Substrate with kind
Suspend & Resume Stateful Agents: kagent on Agent Substrate with kind By Sebastian Maniak Agent sessions are bursty. A user asks a question, the agent …
agentgateway Standalone: A Cost & Tokenomics Dashboard in One Command
Introduction You’re routing LLM traffic through a gateway. But do you actually know what it costs? Not the rough monthly invoice from your provider — the …
Do AgentGateway Tool Modes and Headroom Stack? Measuring Two Token-Saving Layers Together
In a previous post I showed that Enterprise agentgateway can cut your LLM bill by changing how GitHub’s MCP tools are presented to the model — its …
GitHub MCP Token Economics: Why Search Mode Cuts Your LLM Bill by ~60%
Every time an LLM talks to an MCP server, it has to be told what tools exist. That tool catalog — the JSON schema of every tool, its parameters, and …