About eight weeks after handing agentic coding to everyone, merged pull request volume doubles, everyone celebrates, and then the second number arrives: review times climb, change failure rates creep up, and nobody can answer an auditor asking who approved the change an agent wrote at two in the morning. This course stood out because it rebuilds the software lifecycle itself, providing the gates, evals, and audit evidence that actually hold.

This Course Offers

• A complete AI-native SDLC framework: You will run the six-stage loop where each stage commits an artifact the next stage reads, from intent and spec to diff, review, and incident.
• Practical skills in agent controls and feedback loops: You will write PreToolUse hooks, build a feedback loop so agents verify their own work, and stand up a continuous eval suite.
• Knowledge of review policies and production gates: You will write a review-policy file with severity thresholds and nit caps, and set a production gate that agents cannot pass without authorization.
• Expertise in governance and audit evidence: You will map gates to NIST SSDF, ISO/IEC 42001, and SOC 2, and build statistical control bands that self-diagnose breaches.

Why We Love This Course

1. It treats governance as a first-class concern. Every play names what is enforced, what the evidence is, where it is logged, and who approves. You can tell it is designed for regulated environments.
2. It is built around a realistic enterprise case study. You follow Meridian Pay, a 640-person payments platform with FCA, DORA, PCI-DSS, and SOC 2 obligations. This practical context makes the learning concrete.
3. It delivers artifacts, not just notes. You finish with templates, hooks, eval starters, and a defensible 90-day rollout plan. This practical focus ensures immediate value.
4. It is taught by an experienced practitioner. The course is designed by a seasoned professional, bringing deep, practical knowledge of engineering leadership and AI governance.

Rebuilding your SDLC around agentic AI is essential for organizations that want to keep the speed without losing control. This course provides a clear, practical, and comprehensive path to doing it right, and it is backed by a money-back guarantee if it does not meet your expectations.

• This course is perfect for engineering leads and staff engineers whose review queue became the bottleneck.
• It is ideal for platform engineering and DevEx teams who own guardrails.
• The course is also great for heads of engineering, application security, QA, and release managers accountable for AI-written code.

• Working knowledge of Git, including branches, pull requests, and branch protection, is required.
• You should have used Claude Code or a comparable agentic CLI for real tasks.
• A conceptual understanding of CI pipelines is helpful.

Interested in exploring more lessons? Check out our full course library to continue building your skills and advancing your learning journey.