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 16-20 of 78 articles in Product.

Product

Facio's Interpretability Discipline: How AI Agents Make Decisions That Customers, Auditors, and Regulators Can Actually Understand

Jul 23, 2026Product

Facio's Interpretability Discipline: How AI Agents Make Decisions That Customers, Auditors, and Regulators Can Actually Understand

AI agents make decisions that affect real people: a loan is approved or denied, a claim is paid or rejected, a customer is offered a discount or not, content is flagged or allowed. The people affected deserve an explanation. Auditors demand one. Regulators require one. Naive agents produce outputs without explanations; the team can't tell why the agent decided what it decided. Facio's interpretability discipline gives every decision a structured explanation: what data the agent saw, what reasoning it followed, what alternatives it considered, and why it chose this path.

Product

Facio's Anti-Abuse Discipline: How AI Agent Systems Detect and Stop Prompt Injection, Loops, and Exfiltration Before Damage Is Done

Jul 22, 2026Product

Facio's Anti-Abuse Discipline: How AI Agent Systems Detect and Stop Prompt Injection, Loops, and Exfiltration Before Damage Is Done

AI agents in production face a new category of abuse that traditional systems weren't built for. Prompt injection turns instructions into weapons. Cost-exhaustion loops burn through thousands of dollars in minutes. Data exfiltration smuggles customer data out through tool calls. Token-budget attacks exploit context windows. Without anti-abuse discipline, AI agents become unwitting accomplices. Facio's anti-abuse discipline gives the runtime the structural defenses: input sanitization, loop detection, exfiltration monitoring, and circuit-breaker isolation.

Product

Facio's Dead-Letter Discipline: How AI Agent Systems Handle the Work That Will Never Succeed

Jul 21, 2026Product

Facio's Dead-Letter Discipline: How AI Agent Systems Handle the Work That Will Never Succeed

Some work is destined to fail. A task references a deleted record. A request asks for an action that violates policy. An integration points at a service that no longer exists. Naive agents retry these tasks forever, burning resources and never succeeding. Facio's dead-letter discipline gives every task a maximum retry budget, a quarantine path for work that can't succeed, and a recovery workflow for work that can be fixed. Failed work is contained; the system stays healthy; humans review what matters.

Product

Facio's Compliance Mode: How AI Agents Operate Inside Regulated Industries Without Becoming the Compliance Problem

Jul 20, 2026Product

Facio's Compliance Mode: How AI Agents Operate Inside Regulated Industries Without Becoming the Compliance Problem

AI agents in regulated industries — finance, healthcare, legal, tax, government — face a different operational reality. Every action must be traceable. Every decision must be explainable. Every data access must be authorized. Every output must be auditable. Naive agents become compliance problems: untraceable decisions, unlogged data access, unauditable outputs. Facio's compliance mode bakes regulatory expectations into the runtime: mandatory audit trails, data minimization, deterministic replays, and exportable evidence packages.

Product

Facio's Disaster Recovery Discipline: How AI Agent Systems Survive When the Database, the Region, or the Provider Goes Down

Jul 19, 2026Product

Facio's Disaster Recovery Discipline: How AI Agent Systems Survive When the Database, the Region, or the Provider Goes Down

Production AI agents depend on many systems: databases, model APIs, queues, message brokers, authentication services, secret stores. Any of these can fail. A database corruption takes down session state. A cloud provider incident takes down a region. A model API outage takes down reasoning. Without disaster recovery discipline, these failures cascade into extended outages. Facio's DR discipline gives AI agent systems the structural patterns to survive disasters: backups, replication, runbooks, drills.