Production AI agents, in practice
What we learn building the execution layer for enterprise AI — orchestration, governance, guardrails, evaluation, and the gap between demos and production.
Production AI Agents: From Demo to Real Execution
A practical framework for moving AI agents from impressive demos to governed, observable production workflows your business can rely on.
Multi-Agent Workflows Beyond Prompt Chains
Why prompt chains break in production, and how DAG orchestration, map-reduce fan-out, and manager-worker delegation deliver reliable multi-agent systems.
Approval Gates for AI Agents: A Design Guide
When humans should stay in the loop of agent execution, what to gate, and how to scope approvals so governance does not become a bottleneck.
AI Agent Observability: What to Log for Every Run
Traces, tool spans, guardrail events, and cost — the minimum record every production agent run needs, and how each feeds evaluation.
AI Agents in Salesforce: Safe Writes at Scale
Patterns for embedded AI agents in your CRM — propose-approve-commit writes, parallel lead enrichment, and guardrails for customer PII.
AI Agents in the Engineering Inner Loop
PR review, on-call investigation, and triage — where agents genuinely help engineering teams, and how to define them as code with an IaC SDK.
Automate Ticket Triage with AI Agent Guardrails
Tier-1 support automation that survives contact with real customers: classification pipelines, draft-first responses, and honest deflection metrics.
AI Agent Glossary: Platform Terms Defined
Agent, workflow, tool, guardrail, policy, trace, eval — the vocabulary of production agent platforms, defined precisely and without hype.
Build Your First AI Agent in 10 Minutes
A guided walkthrough from zero to a working support triage agent — builder steps, guardrail preset, first test run, and reading your first trace.