Professional Certificate in Agent Building
Run a fleet of agents your team relies on. Inventory, governance, observability, rollback — the operator playbook that turns 'we built an agent' into 'we run a library.'
Why this instead of a traditional degree?
- Months of training — assumes engineering background
- $2,000-$10,000+ for certifications (PMI, ITIL, SRE)
- Focused on code-based systems — agents are an afterthought
- Built for centralized IT teams, not embedded operators
- Catches up to AI agents 2-3 years late
- 3 weeks — every lesson uses real agent tools hands-on
- Included with Pro subscription
- Built for non-engineer operators in marketing, ops, finance, HR
- Production-tested patterns from Salesforce, Stripe, Microsoft, Stanford research
- Up-to-date with 2026 EU AI Act + NIST RMF + cyber-insurance requirements
What you'll learn
Design and ship a 5-agent shared library for your team with named ownership, deprecation schedules, and documented runbooks for each agent
Diagnose production agent failures in under 15 minutes using natural-language observability (Sentry Seer, Langfuse) — without reading code
Architect a 3-agent multi-step workflow (orchestrator + workers) for a job-specific use case, avoiding the 4 known orchestration failure modes
Write a 9-section agent governance one-pager your CISO, cyber-insurance underwriter, and outside counsel can sign without rework
Evaluate the build-vs-buy decision for a given agent use case using a 6-question framework — vibe-coded vs SaaS product vs Claude Code bridge
Execute a 90-day phased rollout plan (knowledge audit → 1% pilot → 25% deflection) to a team of 10-50 with peer-champion adoption
Audit your own agent deployment for the 4 paper-governance detection signals an external auditor would flag
Run the 10-question privacy gate before authorizing any new connector for a team-shared agent
Curriculum
Orientation: From One Agent to a Fleet
Map the agent operator role, meet the 5 CISO questions every agent has to answer, and populate your team's first agent inventory.
Orientation: From One Agent to a Fleet
Portfolio Deliverable: Populated 7-column inventory for your team's existing agents with risk-tier classification
Start ModuleThe Agent Operator Mental Model
Single vs multi-agent shape test, the Module 1 covenant — ship a 2-agent workflow in 25 minutes — and the 4 ownership areas that compose the operator role.
The Agent Operator Mental Model
Portfolio Deliverable: Deployed 2-agent research-then-draft workflow with trust-signal verification
Start ModuleBuilding a Team-Shared Agent Library
Convert personal agents to team-shared with named ownership, the 3-part naming convention, the 5-section runbook, deprecation playbook, and the 1/3-mark cumulative review.
Building a Team-Shared Agent Library
Portfolio Deliverable: Re-named library + v0.1 runbooks for highest-stakes agents + at least 1 documented sunset
Start ModuleMulti-Agent Workflows
Re-engagement aha — the 4 orchestration patterns (orchestrator-worker, planning-execution, hierarchical, swarm), orchestrator design decisions, build a 3-agent chain, diagnose zombie workflows + hallucination loops.
Multi-Agent Workflows
Portfolio Deliverable: Deployed 3-agent chain (research → draft → review) with explicit hand-off schemas
Start ModuleConnecting Agents to Real Org Data Safely
Scope creep patterns, the 10-question privacy gate, compliance-friendly connectors in 2026, silent-breakage modes that traditional monitoring misses.
Connecting Agents to Real Org Data Safely
Portfolio Deliverable: Documented privacy gate for one connector + connector-health probe configured
Start ModuleObservability + Diagnosing Production Failures
The 2/3-mark aha — 'the error lives in the reasoning, not the code' — the 15-min diagnosis loop, natural-language observability tools tour, alert thresholds, cumulative review #2.
Observability + Diagnosing Production Failures
Portfolio Deliverable: Observability tool configured + 3 alerts tuned + 1 postmortem document
Start ModuleGovernance — Audit, Compliance, Rollback
EU AI Act + NIST RMF for non-engineers, write the 9-section governance one-pager, detect the 4 paper-governance signals, build the rollback playbook.
Governance — Audit, Compliance, Rollback
Portfolio Deliverable: 9-section governance one-pager for highest-stakes agent + self-audit results + rollback playbook
Start ModuleCapstone — Ship a 5-Agent Library for Your Team
Pick the team and 5 agents. Build the library overview. Write the 90-day rollout plan for one specific agent applying Stanford's Enterprise AI Playbook research.
Capstone — Ship a 5-Agent Library for Your Team
Portfolio Deliverable: Complete 5-agent team library + library overview + 90-day rollout plan for one agent
Start ModuleYour AI Toolkit
You'll use these tools throughout the program — most have free tiers sufficient for the exercises. Pro tiers needed for team-shared deployment.
The vibe-coding agent platforms — you'll already have one from the prerequisite course; this program extends to multi-agent
Free / $25-50/mo Team tierThe LLM behind your agents. Enterprise tiers ship zero-retention + SOC 2 + audit logs
$20-30/user/mo at Enterprise tierNatural-language observability — query your agent traces semantically, set drift/hallucination/cost alerts
Free tier or $99/mo Pro (Langfuse); ~$500-1500/mo team (Sentry)Workflow orchestration for multi-agent chains with state persistence
Free self-host / $50-500/mo cloudWhere your agents connect to real org data — Enterprise tiers give you SOC 2 + audit logs
Existing — Enterprise tier dependency for compliance postureMost exercises work with the agent platform you already have. Full operator-quality setup with observability + Enterprise LLM API + Team-tier agent platform: typically $100-500/month for a small team, scaling with usage.
About this program
The agent operator role didn’t exist in 2024. By 2026 it’s the highest-leverage non-technical position on any team running AI in production. While the rest of the market struggles with the 90% gap between “we have agents” and “agents make us money” — only ~5% of enterprise pilots show measurable returns per MIT NANDA — the operator role is what closes that gap. Inventory, observability, governance, rollback. Documented process plus a spreadsheet plus a named individual on the line. No coding required.
This program is built for non-engineer operators in marketing, ops, finance, HR, customer success, admin — the people whose teams have started shipping agents but whose AI program quietly drifts into paper-governance territory because nobody owns what happens between deploy and decommission. By the end of 8 modules, you will have shipped a complete 5-agent team-shared library, with a governance one-pager your CISO can sign, an observability stack that catches drift before customers do, and a 90-day rollout plan grounded in Stanford’s 51-deployment research. The Capstone is not a theory exercise — it’s the operations stack your team needs to deploy on Monday morning.
This is the program people will come to when they realize ‘we built an agent that works for me’ isn’t the same as ‘we run a library our team relies on.’ The role is new. The work is real. The teams that learn this in 2026 are the ones whose AI deployments actually convert into the measurable returns the rest of the market is missing.
Prerequisites
Complete these 3 courses before starting the program. They build the foundation: understanding how AI works, building your first agent, and knowing the connector landscape — so this program can focus on what no course covers: team-scale agent operations.
Understand how AI works, write powerful prompts, and build practical skills from scratch. The baseline AI literacy this program builds on.
Build a working AI agent for your job in one afternoon — no Python, no terminal. The foundational hands-on experience this program extends to team scale.
Build real ChatGPT Workspace Agents that send emails, post to Slack, and run on schedule. Familiarity with a second agent ecosystem broadens the operator's toolkit.
Frequently asked
Do I need to be technical to take this program?
No. This program is built for non-engineer operators in marketing, ops, finance, HR, customer success, and other non-tech roles. Zero coding required — you'll work in spreadsheets, Notion docs, and the same vibe-coding tools you used in the prerequisite course.
What tools will I actually use?
The vibe-coding tool you already know (Lovable, Bolt.new, or Replit Agent), an LLM provider (Claude or ChatGPT Enterprise tier), one observability tool (Langfuse or Sentry Seer), and your existing org tools (HubSpot, Slack, Google Workspace, etc.). All are accessible via web UI — no terminal, no Python, no Kaggle.
How is this different from a traditional DevOps or SRE training?
DevOps/SRE assume engineering background and focus on code-based systems. This program is for non-engineers running AI agents — the failure modes, observability tools, and governance frameworks are agent-specific. Traditional ops training will catch up to AI agents in 2-3 years; you need this knowledge now.
Will AI replace the agent operator role?
Quite the opposite. As organizations adopt more agents, the operator role becomes more important — someone has to own inventory, monitoring, governance, and rollback. Agents can run themselves operationally; they cannot decide their own governance posture or take responsibility when they fail. The operator role is one of the highest-leverage non-technical positions in 2026.
What prerequisites do I really need?
The 3 prerequisite courses (AI Fundamentals + Vibe Code Your First AI Agent + ChatGPT Workspace Agents for Non-Engineers) OR equivalent experience: you've built at least 2 working agents and understand basic prompt engineering. If you've shipped one agent and it works, you're ready.
What do I get when I finish?
A verifiable Professional Certificate in Agent Building certificate with credential ID (AAB-XXXXXX), a complete 5-agent team-shared library you can deploy in your job, a 90-day rollout plan, and the operator framework that lets you handle any future agent your team adopts. You can also continue to the Master Certification in Agent Strategy (planned) for board-level governance and AI fluency framework design.
How long does the program take?
3 weeks at 6-8 hours per week. Each lesson is 15-25 minutes. The Capstone is the biggest single time investment (~6 hours over a week). You can go faster or slower depending on your schedule and how much you implement at your actual job.
Is this program recognized by employers?
The role is new (2026) and few employers have specific listings for it yet — but the FUNCTION is what every team running agents needs. Your Capstone library (5 agents with full operator-quality artifacts) is a portfolio piece you can show directly. Many learners use the Capstone artifacts as the proof point for an internal role designation as 'AI Operations Lead' or similar.
Do I need coding or technical skills?
No coding. No reading code. You'll work with structured documents (spreadsheets, runbooks, one-pagers), natural-language observability queries, and vibe-coding tools — all accessible via web UI. The program explicitly excludes anything requiring Python, JavaScript, or terminal usage.
What if my team doesn't have many agents yet?
You're early — that's the advantage. This program teaches the framework for OPERATING agents your team will adopt over the next year. The Capstone's 5-agent library tolerates 2-3 proposed agents (not yet built) if you're at the start of the agent journey. The framework applies whether you have 2 agents or 20.
How does this prepare me for the Master Certification in Agent Strategy?
This program teaches operator-quality (APPLY/ANALYZE level Bloom's). The future Master Certification extends to strategic (EVALUATE/CREATE) — build-vs-buy at the org level, AI fluency frameworks for hiring, multi-team agent governance, board-level reporting. Each module produces a handoff to those master-degree topics; your research/ folder will contain the connecting threads.
What about EU AI Act compliance — does this actually help?
Yes. EU AI Act high-risk obligations activated August 2, 2026. This program teaches the deployer obligations (Articles 26-27) every non-engineer operator needs to satisfy: inventory, fundamental rights impact assessment, human oversight, audit trail, named accountable individual. Your Capstone's 9-section governance one-pager IS the EU AI Act compliance artifact for each agent.
What's the difference between this program and the prerequisite courses?
Courses teach building. This program teaches OPERATING — the role between 'agent built' and 'agent in production safely at team scale.' The prerequisite courses shipped you one agent for yourself; this program teaches you to run many agents for your team, with the governance, observability, and rollback discipline that turns agents from liability into asset.
