Practical guidance on AI agent architecture, permissions, evaluation, governance and production workflows.
AI agents connect model decisions to tools and business workflows. A production design needs a clear objective, bounded permissions, observable tool calls and a safe way to hand uncertain work to people.
Start by deciding whether a deterministic workflow is sufficient. For agentic work, evaluate task success, tool failures, data leakage and operating cost against a realistic baseline.
Explore the articles below for implementation and governance decisions. Our AI agent service page covers scoping a pilot around your data and operating constraints.
Showing 13–24 of 43 posts
Plan API modernization for AI agents with legacy integration strategy, scoped access, observability, contract testing, security controls, cost drivers, and rollout gates.
Use this AI agent skill security checklist to review reusable agent skills, permission manifests, sandboxing, provenance, audit logs, semantic scanning, and incident response before production use.
Use this AI data readiness checklist to score access, ownership, quality, permissions, retrieval, evaluation, governance, and workflow fit.
Plan an agentic SOC rollout with telemetry, triage agents, investigation workflows, human approval gates, playbooks, audit logs, and metrics.
Forecast and control agentic AI costs across model calls, context, tools, cloud workload, observability, review labor, caching, guardrails, and rollback.
Plan AI-native SaaS modernization with workflow selection, data readiness, agent architecture, pricing, governance, evaluations, migration gates, and phased delivery.
Use this 2026 AI agent identity governance checklist to manage non-human identities, scoped credentials, delegated authorization, guardrails, audit logs, and incident response.
Use this AI agent development lifecycle to plan workflow selection, owners, context, tools, evals, guardrails, release gates, monitoring, and evidence-based iteration.
Use this shadow AI governance checklist to inventory hidden AI use, classify data and code risk, approve tools, review agents, monitor evidence, and keep software delivery safe.
Use this MCP server security checklist to inventory servers, enforce OAuth and scopes, approve tools, protect secrets, log activity, prove rollback, and ship enterprise AI agent integrations safely.
Use this AI agent observability checklist to design traces, eval gates, guardrails, alerts, rollback runbooks, and incident evidence before production rollout.
Plan AI agents for production scheduling with ERP, MES, APS, constraints, planner approvals, shop-floor write-back, KPIs, and safe autonomy gates.
