Agentic Engineering
Build faster with AI agents without lowering your engineering standards.
For engineers who already vibe-coded and want the discipline back: plan, delegate to agents, and keep tests, reviews, and quality gates in place.
€1,500
Course Overview
Direct AI agents to ship trustworthy software in 6 weeks
Start Date
September 16, 2026
Duration
6 weeks
Format
Online · Post-work · 2 sessions per week
Investment
€1,500
- Language
- English
- Instructors
- 2 practitioners
- Payment
- Single payment
- Certificate
- Yes, upon completion
What you will be able to do
By the end of the course, you'll have done all of this, for real:
Direct agents on real projects
Use coding agents effectively on non-trivial software, not just toy examples.
Write specs agents can execute
Break large projects into agent-compatible tasks with clear acceptance criteria.
Build verification loops
Tests, evals, linters, type checks, CI, and red-team workflows that reject bad output.
Spot jagged failures
Identify where agents will silently misunderstand intent and harden the design before they do.
Review AI-generated code
Catch security holes, bad data models, and overengineering before they hit production.
Ship a defended project
A working product with a spec, evals, security review, red-team report, and engineering defense.
Is this course for you?
Self-qualify before you enroll, takes under a minute.
Prerequisites
- Senior or mid-level software engineer
- Confident with Git, tests, and CI
- You've used Cursor / Claude Code / Copilot in the last 6 months (helpful, not required)
- You bring a non-trivial repo or are willing to start one
Not for you if
- You want to ship an autonomous agent product, pick AI Agents in Production
- You're new to programming, pick the Advanced AI Solutions
Curriculum. Six weeks. One real project.
From vibe coding to engineering discipline with agents in the loop.
From Vibe Coding to Agentic Engineering
Software 1.0, 2.0, 3.0. Agents as stochastic interns. Build the same idea twice, vibe-coded vs spec-driven, and make the quality gap visible. Deliverable: side-by-side write-up of vibe vs spec build with measured quality delta.
Specs, Context, and Control
Prompting isn't enough. Engineer the work environment: agent-readable repo guides, executable docs, and task templates that survive contact with reality. Author Claude Code skills (SKILL.md), .claude/settings.json hooks, and at least one MCP server scoped to your repo. Deliverable: AGENTS.md, three task templates, and one repo-scoped MCP server for your final project.
Verifiability, Evals & the Quality Bar
Tests as reward signals. Build evals, golden datasets, type checks, and CI guardrails so the agent's output can be rejected before it reaches main. Deliverable: golden dataset, LLM-as-judge eval, and a CI workflow that blocks regressing PRs.
Jagged Intelligence & Human Judgment
Where agents fail and why: hidden assumptions, leaky abstractions, security mistakes. Review AI-generated code and ship a risk register. Deliverable: AI-generated code review report and risk register on your repo.
Multi-Agent Workflows & Agent-Native Infrastructure
Planner, builder, tester, reviewer, red-teamer. Coordinate roles, sandbox tools, and design infrastructure agents can operate without breaking things. Deliverable: planner/builder/reviewer pipeline running on your repo with sandboxed tools.
Final Build, Red Team & Engineering Defense
Ship a project agents helped build. Defend it with tests, evals, security review, and a red-team report. Demo Day with peer and instructor critique. Deliverable: defended project with self red-team checklist and one peer red-team review.
Straightforward pricing
No "contact us" pages. Tiers auto-promote as dates pass.
Until 31 Aug
15 seats · 15 seats only
1 – 10 Sep
Limited seats
From 11 Sep
Standard enrollment
DGERT-certified training entity: individuals can deduct 30% of the fee on their IRS, and for companies the hours count toward the mandatory 40 hours of annual employee training.
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