Pathway · a route through lessons that already exist
Agentic Engineering for Software Teams
A guided route through lessons that already ship inside AI-Powered Development — read in their published order except for the one move the lessons themselves argue for, with a test at every stage for skipping what your team already does.
5 stages · 17 existing lessons · ~4.8 hours · Teams that ship code and want agents in the pipeline; tech leads approving the tooling
Nothing in this route is new. Every lesson below already ships inside AI-Powered Development, and every link goes to the lesson where it already lives — no URL moves for this page. Every one of the 9 trainings in the Meridian sequence already sends readers into The Prompting Playbook as preparation — you can check that on any of their pages. No training lists Agentic Engineering as recommended preparation — that gap is what this page is for: the order to read them in, and the tests for skipping what you already do.
Before you start
The route starts where the flagship stops. Module 19 lesson 1 puts it plainly: "Modules 1-11 covered the floor: install the tools, prompt well, chunk work, ship code." The heaviest dependency is Module 10 — both modules cite it for planning, for giving good instructions, and for the prompt basics they build on.
That prerequisite is Module 10: Planning & Orchestration — 4 lessons, 80 minutes, and the link opens its first one. It is not counted in the 17 above, because it is the floor this route stands on rather than part of it. Skip it if your team already plans before prompting, breaks work into chunks, writes instructions specific enough to act on, and debugs with the agent rather than around it.
The route
Use the two opening maps to find your gaps, then take Context Engineering before the later Agentic Engineering stages; the prompting stage can run in parallel. Each stage names the test for skipping it — a route you skim in twenty minutes is worth more than one you abandon in the middle.
- Stage 01
Decide whether your team needs this
2 lessons · 24 minBoth modules open with a self-assessment whose stated job is to route you. Read the two maps back to back and send people to the gaps they actually have, instead of marching everyone through the whole route.
Skip this stage if you have already run both self-assessments and know which items your team cannot do confidently today.
- Beyond the Prompt 12 min The team map: what changes when an agent stops answering and starts operating.
- How the Builders Prompt 12 min The craft map: seven techniques set against what Module 10 already taught you.
- Stage 02
The lesson the module tells you to read first
1 lesson · 20 minThis is the one place the route departs from the published order, and the lesson makes the argument itself: "Start with Lesson 2. Context Engineering underpins everything else. Even if you only read one lesson in this module, read that one." Later lessons on subagents, specs and runbooks all assume it, so it gets its own stage rather than a slot.
Skip this stage if you can already keep an agent sharp across a week-long project without context rot — the one skip to be most honest about, because every later Agentic Engineering stage builds on it.
- Context Engineering 20 min Context rot, compaction, retrieval, note-taking, isolation — and what makes a memory file actually constrain behaviour.
- Stage 03
Prompting craft
7 lessons · 103 minSeven techniques that improve any single agent turn. Kept in published order because they chain — the tags from Structure are the mechanism Grounding builds on, and the last lesson is a capstone that combines the six before it. Nothing here depends on the tooling stages, so a team splitting the work can run this in parallel.
Skip this stage if your team already primes with a role, shows examples, makes the model reason before answering, separates instructions from data, grounds answers in quoted sources, chains steps, and tests prompts against cases.
- Give the Model a Role 12 min Prime behaviour before the task: a specific expert, what they care about, how they answer.
- Show, Don't Tell 14 min Examples beat description — consistency, variety, and the refusal case.
- Let the Model Think 14 min Reasoning before the answer, parked in a scratchpad — a technique, not a setting.
- Structure and Format 15 min Tag the parts so instructions and data cannot blur, and name the output shape.
- Ground the Answer 16 min Quote first, answer second, and permit "not found" — the lesson calls this the biggest single win.
- Chain Your Prompts 14 min Split an overloaded prompt into steps that each do one job.
- Test and Keep What Works 18 min Success criteria and varied cases, one change at a time; combines the six above.
- Stage 04
Extend and orchestrate the agent
3 lessons · 62 minWhere "agents in the pipeline" becomes literal: reaching your systems through an external tool server, encoding team conventions once so they are enforced rather than requested, and running more than one agent on purpose.
Skip this stage if your team can already connect and vet a tool server, author a cross-tool skill and a hook that enforces a guardrail, and decompose work across parallel agents — and anyone reaching for worktrees is comfortable with branches and merges, which the lesson names as its own prerequisite.
- MCP: Extending Your Agent 20 min Connect an external tool server over MCP (the Model Context Protocol) — and vet it before you trust it.
- Skills, Hooks & Custom Commands 20 min Author a skill once for any tool; hooks enforce what a memory file only asks.
- Subagents & Orchestration 22 min Fan-out, pipeline, supervisor, debate — plus worktrees, which assume you are comfortable with branches.
- Stage 05
Run it as infrastructure
4 lessons · 81 minThe stage a tech lead is actually approving: unattended runs and the guardrails each one needs, a spec the team reviews and the agent executes, independent review before a risky change ships, and a runbook a cold agent can finish.
Skip this stage if your team can already run agents safely from a script or CI, decide when work needs a committed spec, send risky changes through independent review while skipping it for routine ones, and write a runbook a cold agent can finish.
- Headless Agents & CI 20 min Agents as a unix tool — script, cron, CI, cloud — and the guardrails each step needs.
- Spec-Driven Development 18 min A spec the team reviews and the agent executes; its own test is whether the question survives 48 hours.
- The Council Pattern 18 min Independent multi-model review before a risky change ships — and the list of times not to convene one.
- Runbooks: Docs Agents Execute 25 min Capstone: a five-phase runbook a cold agent finishes with no questions, graded by execution.
What this route does not cover
These lessons make a team effective with agents. They do not decide whether an agent may run in your organization, who answers when it breaks, or what one action is allowed to do. Each of those has an owner:
- Whether an agent may be deployed at all — the register, the evidence a reviewer can open, and the signed release decision. AI Assurance: System Risk and Release Decisions →
- What one action may do at one moment. Guarded Automation says it of this route directly: "Module 19 lesson 4's allowlist covers command-line interface (CLI) commands, not operational actions." Guarded Automation: Agents That Run Operations →
- Who is on call when something an agent touched breaks, who commands the incident, and which reporting clock started. Operating in Production: On-Call, Incident Command, and Reporting Clocks →
- The agent as a first-class identity: a named directory identity, an owning team, lifecycle and suspension rules, just-in-time elevation, and a queryable audit trail. This route covers token handling and least-privilege scopes; it does not cover governing the identity behind them. Zero Trust Implementation →
- The delivery controls beyond this route’s "the agent drafts, a human decides": pull-request-only output, approval enforced by the platform before CI runs agent code, required templates, scans and policy gates, and authorship provenance. Modern DevSecOps Foundations →
- Everything that has to be true around the agent before other people depend on what it built: a grounded answer proved rather than cited, evaluation on your own data behind a gate, the system register, the pager. A second route walks that, and shares no lesson with this one. AI Engineering: After the Demo Works →
Teams that ship code and want agents in the pipeline; tech leads approving the tooling