Practical writing for agentic engineering teams.
Public articles designed to help software teams understand the discipline behind agentic systems and find their way into the Academy.
Start with the transformation roadmap
The Agentic Transformation Roadmap
A phased roadmap for moving from isolated AI experiments to governed, measurable, organization-wide agentic capability.
Foundations and concepts
What Is Agentic Engineering?
A beginner-friendly explanation of agentic engineering as the professional evolution beyond vibe coding.
A Practical Guide to Building Agents
A practical introduction to the model, tools, and instructions that make up a useful AI agent.
LLM Agents in 2025: Definition, Use Cases, and Tools
A plain-English map of how LLM agents moved from reactive chat to autonomous task execution.
How to Build an AI Agent with LLMs
A low-barrier introduction to the building blocks of LLM-powered agents.
The Six Levels of Agentic Engineering
A ladder for understanding how teams move from manual supervision to higher levels of agent delegation.
Implementation and design patterns
Choose a Design Pattern for Your Agentic AI System
How to choose between single-agent, sequential, loop, coordinator, swarm, and human-in-the-loop patterns.
The Ultimate LLM Agent Build Guide
A production-minded view of memory, context, tools, guardrails, and multi-agent reliability.
Design Patterns for Agentic AI Systems
A pattern-oriented approach to coordinating machines that reason, delegate, and work together.
Agentic Engineering: Systems Architecture First
Why agentic engineering is mostly architecture, contracts, failure analysis, observability, and eval design.
Designing and Deploying Production-Grade Agentic AI Workflows
A lifecycle view of workflow decomposition, MCP integration, tool design, deployment, and maintainability.
LangGraph, MCP, and Production Agentic Systems
How LangGraph, MCP, and agent observability fit into production-grade agentic system design beyond simple framework demos.
Architecture, governance, and security
From Prompt-Response to Goal-Directed Systems
How agentic AI architecture evolves from stateless response generation to goal-directed control loops.
Production-Grade Autonomous AI Systems
A technical guide to reflection, tool use, planning, multi-agent collaboration, and enterprise reliability.
From Craft to Constitution
A governance-first paradigm for turning agent development from brittle craft into principled engineering.
A Threat Model for Generative AI Agents
How ATFAA and SHIELD frame the security risks unique to autonomous, tool-using AI agents.
AI Agent Identity Security: The 2026 Deployment Guide
Why production agents need explicit identity, scoped delegation, and enforceable trust boundaries.
Part VIII — The Agentic Business
The Educational Science Behind the CAE Certification
How the Certified Agentic Engineer exam is built on Bloom's Taxonomy, mastery learning, constructive alignment, and credentialing standards recognized by education researchers worldwide.
The Economics of Agentic Engineering
How to think about agentic engineering through unit economics, leverage, marginal cost, and measurable business outcomes.
Building and Leading Agentic Teams
How engineering leaders can organize roles, rituals, review loops, and operating standards for teams that use agents every day.
AI Product Management
A product management guide for AI-native features: choosing workflows, defining success, managing uncertainty, and shipping responsibly.
Vendor and Model Strategy
How to choose models, vendors, routing strategies, fallback plans, and governance practices without locking the business into brittle dependencies.
Legal, IP, and Compliance
The practical legal and compliance questions teams must answer before using agents in real business workflows.
Organizational Change Management
How to move an organization from scattered AI experiments to durable agentic capability without creating fear, chaos, or unmanaged risk.
Competitive Strategy in an AI-Native Market
How agentic capability changes competitive advantage, speed, defensibility, customer experience, and operating models.
Human-in-the-Loop Design: When Supervision Is Non-Negotiable
A manager's framework for deciding when agents need human oversight — and how to design review gates that don't become rubber stamps.
Working Effectively with Engineering Teams on Agentic Projects
How product and project managers can collaborate productively with engineers on agentic systems — including what to ask, what not to assume, and how to manage the information asymmetry.
Case Study: The Runaway Automation
A customer service AI at a financial services firm begins making decisions outside its original scope. You are the PM. What do you do in the first 48 hours — and what does this case reveal about agentic project governance?
Identifying Agent-Ready Workflows: Fit vs. Force
A practical framework for evaluating which workflows are genuinely suited to agentic automation — and which ones will waste budget, create risk, and disappoint stakeholders.
Writing Acceptance Criteria for Probabilistic Outputs
Traditional acceptance criteria assume deterministic behavior. Agentic systems are probabilistic. Here is how to write acceptance criteria that are honest, testable, and actually useful.
Defining 'Done' When the Agent Decides What to Do Next
Agentic projects resist traditional definitions of 'done.' This chapter provides a framework for setting completion criteria that account for probabilistic behavior, evolving capability, and organizational readiness.
Managing Scope Creep in Autonomous Systems
Scope creep in agentic projects has a unique character: it often comes from the agent itself, not from stakeholders. Here is how to recognize it, contain it, and prevent it from becoming a governance failure.
Negotiating Scope, Resources, and Timelines with Engineering Teams
Agentic projects create unique negotiation dynamics between product, project management, and engineering. This chapter provides frameworks for reaching agreements that are realistic, durable, and honest.
Case Study: The Moving Goalposts
Midway through a 3-month agentic project, the engineering team tells you the agent cannot reliably hit the accuracy threshold you promised stakeholders. You have two weeks until the board presentation. Resolve it.
Cost Per Successful Task: Building the Financial Model
A step-by-step guide to building the financial model that makes agentic automation legible to finance teams, executives, and boards — including NPV, payback period, and sensitivity analysis.
Build vs. Buy vs. Configure: A Decision Framework for Agentic Systems
How to make the build-buy-configure decision for agentic systems without defaulting to the wrong answer based on cost alone, technical preference, or vendor enthusiasm.
Negotiating AI Vendor Contracts: Leverage, Clauses, and Red Flags
What every product and project manager must know before signing an AI vendor agreement — the clauses that protect you, the terms that expose you, and how to negotiate from a position of knowledge.
Budget Planning and Cost Controls for Agentic Projects
How to build an agentic project budget that accounts for variable costs, failure recovery, ongoing maintenance, and the hidden expenses that derail financial performance in the first year.
Measuring and Communicating ROI to Stakeholders
How to measure the ROI of agentic initiatives in ways that are honest, credible, and persuasive to the finance teams, executives, and boards who will fund the next phase.
Case Study: The Vendor Lock-In
Your primary AI vendor announces a 40% price increase and new data retention policies that may violate your compliance requirements. You have a $2M annual contract up for renewal in 60 days. What's your play?
AI Governance Frameworks: What Every PM Must Know
A practical introduction to AI governance for product and project managers — what frameworks exist, which ones apply to your organization, and how governance decisions translate into project constraints.
Compliance in Regulated Industries: Healthcare, Finance, and Legal
How agentic systems interact with the specific compliance requirements of healthcare, financial services, and legal — and what project managers in these industries must account for in scope, design, and governance.
Risk Classification for Agentic Workflows
A practical risk classification system that helps product and project managers assign the right governance controls to the right workflows — without over-engineering low-risk automation or under-protecting high-risk decisions.
Incident Management and Root Cause Analysis for Agent Failures
How to run an effective incident response and root cause analysis when an agentic system produces a significant failure — including the questions to ask, the stakeholders to involve, and the documentation to produce.
Ethical Leadership in Agentic Systems: Beyond Compliance
The ethical responsibilities that product and project managers carry when deploying autonomous systems — including displacement, algorithmic fairness, accountability gaps, and the limits of compliance as an ethical standard.
Case Study: The Bias Discovery
Your HR team's AI screening tool has been rejecting candidates from certain zip codes at a 3x higher rate. Legal says it's not illegal. Engineering says it's a data problem. Three executives want three different responses. What do you recommend?
Translating Agentic Capability to Executives and Boards
How to communicate what agentic systems can and cannot do to executives and board members who need to make resource allocation decisions — without oversimplifying, overselling, or losing the technical credibility that makes you useful.
Stakeholder Communication Frameworks for Uncertain Systems
How to communicate honestly and effectively with diverse stakeholders — employees, customers, regulators, and partners — when the system you are deploying behaves probabilistically and its performance will change over time.
Role Design in an AI-Native Organization
How organizations are redesigning roles, responsibilities, and career paths as agentic systems take on work that previously required dedicated human capacity — and what this means for hiring, retention, and organizational structure.
Career Pathways in Agentic Product and Program Management
How the CAMP credential maps to career trajectories in agentic product management, program management, and AI transformation leadership — including the skills, experiences, and transitions that define each path.
Case Study: The Transformation Mandate
The CEO announces the company is going 'AI-first' in 90 days. You've been named the transformation lead. Design the 90-day plan — workflow selection, governance structure, communication plan, and success metrics.
The CAMP Capstone: The Agentic Transformation Brief
The CAMP capstone project integrates all five curriculum sections into a single strategic deliverable — a complete Agentic Transformation Brief for a real or composite organization, peer-reviewed for professional judgment across all domains.
What Is Forward Deployed Engineering in AI?
A practical guide to forward deployed engineering in AI: what FDEs do, how the role differs from solutions engineering, and why agentic AI makes the function more important.
Forward Deployed Engineer vs. Solutions Engineer: What Changes in AI?
A clear comparison of forward deployed engineers, solutions engineers, sales engineers, and implementation consultants in the age of agentic AI systems.
Agentic Product Management: A Practical Guide for PMs
How product managers should scope, evaluate, launch, and govern AI agents and agentic workflows without treating probabilistic systems like ordinary software features.
Agentic Project Management: How to Deliver AI Agent Projects
A delivery playbook for project managers and program managers leading AI agent initiatives, from scope control to risk reviews and stakeholder communication.
Certified Agentic Management Professional: What CAMP Proves
What the CAMP credential is designed to validate for product managers, program managers, executives, and leaders responsible for agentic AI transformation.
Agentic AI Jobs: Career Paths for Engineers, PMs, and FDEs
A career map for agentic AI jobs, including agentic engineers, forward deployed engineers, AI product managers, agent operations, and governance roles.