Claude Code Intermediate - english - virtual



Kursarrangør: Glasspaper AS
Sted: Nettkurs / Nettstudie
Hele landet
Type:Nettkurs og nettstudie
Studie / yrkesutdanning
Undervisningstid: kl 09:00 - 16:00
Varighet: 1 day
Pris: 10.900

We provide virtual course about Claude Code Intermediate in english. The problem at team scale is not whether Claude Code works. It is that every engineer uses it differently. One person plans carefully and ships clean diffs. Another pastes a ticket into the terminal and merges whatever compiles.

Course description:
The reviewer sees both in the same PR queue and the review standard drifts down to match the worst contributor. The answer is not another tool. It is one shared operating model the whole team actually uses.

Course objectives:
• Run one shared plan - spec - build - verify - review loop across a mixed-maturity team
• Write a CLAUDE.md that a new engineer can use in their first session without asking questions
• Turn tickets into implementation-ready briefs decomposed into reviewable units
• Use Claude Code safely for refactoring, test generation, and debugging without creating review debt
• Review an AI-assisted diff against a verification checklist instead of taste
• Compose skills, memory, and slash commands into shared workflows
• Ship a team-ready set of shared prompts and skills as version-controlled assets

Important information:
1) Pre-Course Self-Assessment:
• Every participant takes a 10-minute online self-assessment before the course. This lets day one open with "here is what this room already knows and where the shared gaps are" instead of generic material.

2) Take-Home Template Pack:
• Every participant leaves with a versioned template pack checked into a real repository. The pack is not a slideware deliverable. It is a working set of 10 to 20 files.

3) 30- Day Follow-Up:
• Two weeks after delivery, the instructor runs a one-hour follow-up with the cohort

The agenda is fixed:
• What has actually been adopted
• What broke
• What got quietly abandoned

Course content:
Module 1 - Where Uneven Adoption Actually Breaks Things:
A short walkthrough of the telemetry: bigger PRs, longer review cycles, higher change failure rates in teams that adopted AI coding without shared standards. Participants self-diagnose their own team against the same pattern.

Module 2 - Context That Survives The Team:
CLAUDE.md as a living document, not a setup step. What belongs in it, what does not, how to keep it short, and how to stop it from drifting.

Lab:
• The room co-writes a CLAUDE.md for a supplied legacy codebase, with actual review

Module 3 - From Tickets To Implementation-Ready Briefs:
Decomposing a feature into reviewable units before any agent touches the repo. How to write a brief that a junior engineer and Claude Code can both act on.

Lab:
• Each participant briefs a real ticket from their backlog and has it reviewed by the room

Module 4 - The Quality Loop: Refactoring, Testing, Debugging
Safer refactoring patterns. Generating tests that check behavior, not implementation. Debugging with explicit hypotheses

Lab:
• A live refactor of a brittle module, with verification steps that would catch a silent regression

Module 5 - AI-Assisted Code Review That Actually Catches Things:
What to look for in an AI-generated diff that a human diff would not have. Verification checklists for business logic, edge cases, error paths, and regressions. When to reject and re-plan instead of asking for fixes.

Lab:
• The room reviews three AI-generated PRs and grades them

Module 6 - Composing Shared Workflows:
The highest-leverage move at team scale is composition: a PR review workflow that chains a slash command, a CLAUDE.md context, a skill, and a subagent is worth more than any one of those used alone.

We walk through three canonical compositions:
• Automated PR review
• New-engineer onboarding
• Documentation-on-commit

The room builds one end to end for its own stack

What participants leave with:
• ACLAUDE.md the team co-authored and agreed on
• Three shared skills scoped to the team's stack
• One fully composed team workflow checked into a repo
• A written AI-assisted PR review checklist
• A one-page Monday plan covering ownership and rollout

Instructors: Rogier Muller & Vasilis Tsolis

Rogier Muller is CTO of BlueMonks Group, an Amsterdam-based fintech compliance company, and co-founder of several companies. He`s a lifelong coder who moved early into AI-assisted software development. Today, he is the only person in the world to combine official ambassador roles across the three leading agentic engineering platforms: Cursor, Claude Code, and Codex.

Rogier has hosted numerous events worldwide and works closely with engineering teams, founders, and AI tooling companies on the practical adoption of agentic software development. His specific expertise is using agentic engineering in highly regulated environments, including but not limited to fintech, financial services, KYC/CDD, AML, GDPR, AFM-supervised contexts, auditability, data isolation, and compliance-heavy software delivery.

Vasilis Tsolis is a pioneer in document intelligence and agentic coding helping teams to change how they work across industries. He is an official Ambassador for Cursor, OpenAI Codex and n8n. He is the partner of Cognitiv+, an AI consultancy and software factory that helps organisations practically implement and adopt AI with enterprise confidence.

He has co-founded several companies and trains development teams across the US and EU on AI-assisted coding, with a consistent focus on integrating it into real workflows without losing control of the codebase. Background: engineering and law, twenty years across AI, construction, energy, and tech. Vasilis has worked with JPMorgan, Intel, PwC, and others along the way.

Target audience:
Software engineers, senior developers, and tech leads inside a team that has been using Claude Code, Cursor, or Copilot unevenly. The course assumes a mix of enthusiasts and skeptics. That mix is the whole point.

Prerequisites:
• At least two weeks of hands-on use of an AI coding assistant on real work
• Familiar with Git, PRs, and review on an existing codebase
• Has read at least one AI-generated PR critically
• Has completed the pre-course self-assessment

Language:
• The course is given in english

Course material:
The course fee includes course documentation and exercises

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