Facio Blog

Practical notes on human-reviewed AI agents.

Payload-powered product notes, security writing, HITL patterns, and operational guidance from the Facio runtime: long sessions, Placet approvals, audit trails, memory, providers, channels, tools, and Docker-first operations.

Showing 31-35 of 78 articles in Product.

Product

Facio's Kill Switch: How AI Agent Workflows Stop the Moment Something Goes Wrong

Jul 8, 2026Product

Facio's Kill Switch: How AI Agent Workflows Stop the Moment Something Goes Wrong

Every production AI agent workflow needs a kill switch — a way to stop all in-flight executions the moment something goes wrong. The agent that processed 1,000 customer refunds correctly before hitting an edge case that causes incorrect refunds; the agent that compiled 50 PRs cleanly before encountering a malicious dependency; the agent that published 100 social posts before being tricked into a policy violation. Without a kill switch, the damage compounds. With one, damage stops at the moment of detection. Facio's kill switch discipline is what makes autonomous AI agent operations survivable.

Product

Facio's Deploy Discipline: How AI Agents Ship Code Without Breaking Production

Jul 7, 2026Product

Facio's Deploy Discipline: How AI Agents Ship Code Without Breaking Production

An AI agent that can write code but not deploy it is a development tool. An AI agent that can both write and deploy is a team member. The difference is huge — and so are the risks. Production deployments are where good code meets reality: networking, dependencies, secrets, traffic patterns, monitoring. Without discipline, an agent deploying code can take down production in seconds. Facio's deploy discipline gives agents the structural patterns to ship code safely: pre-deploy verification, canary rollouts, automated rollback, post-deploy validation.

Product

Facio's Policy Engine: How AI Agents Stay Aligned With Business Rules Even When the Model Wants to Stray

Jul 6, 2026Product

Facio's Policy Engine: How AI Agents Stay Aligned With Business Rules Even When the Model Wants to Stray

An AI agent that follows business rules is valuable. An AI agent that improvises around business rules is a liability. The naive approach to alignment — putting rules in the system prompt — fails because the model can be social-engineered, distracted, or simply wrong about when a rule applies. Facio's policy engine is a runtime enforcement layer that makes business rules architecturally binding: every agent decision is checked against the policies before execution. Rules can't be bypassed because the runtime refuses to execute non-compliant actions.

Product

Facio's Cost Guardrails: How AI Agents Stay Inside the Budget Without Surprising the Finance Team

Jul 5, 2026Product

Facio's Cost Guardrails: How AI Agents Stay Inside the Budget Without Surprising the Finance Team

AI agents burn money quietly. A misconfigured agent makes 10x the necessary API calls. A runaway agent loops on a problem for hours. A clever agent uses the most expensive model for every task because it doesn't know cheaper ones work. By the end of the month, the finance team is asking questions that the engineering team can't answer. Facio's cost guardrails give teams the structural discipline to predict, track, and cap AI agent spend before the invoice arrives.

Product

Facio's Task Dispatch: How Hundreds of AI Agents Get the Right Work at the Right Time

Jul 4, 2026Product

Facio's Task Dispatch: How Hundreds of AI Agents Get the Right Work at the Right Time

A single AI agent is a workflow. A fleet of AI agents is a system. The fleet needs dispatch — a way to route incoming work to the right agent at the right time, balance load across agents, prioritize critical work over routine work, and ensure no agent gets overwhelmed. Naive fleets have no dispatch: every agent polls for work, work piles up at the busiest times, and the team ends up with a different problem than the one they were trying to solve. Facio's task dispatch is the structural discipline that turns agent fleets into systems.