# Agentic Engineering with Claude Code or Codex > A two-day workshop for experienced developers: direct Claude Code or Codex through five projects, from problem framing to a reviewed, working AI product. [View programme page](https://tinkercademy.com/programmes/agentic-engineering-with-claude-code-or-codex/) - Audiences: Businesses, Public - Duration: 2 days - Domains: AI Engineering, Software Engineering - Platforms: Claude, ChatGPT, Git & GitHub, Node.JS, Python - Published: 2026-08-13 - Updated: 2026-10-22 ## Should I take Agentic Engineering or Prompt to Production? It depends on where you're starting. Take Agentic Engineering if you already write software for a living and are comfortable with a terminal, Git, pull requests, and at least one AI coding tool. You'll spend two days directing Claude Code or Codex through five projects, including an unfamiliar codebase and a team AI product. If you've only used chat tools or vibe coding apps so far, start with Prompt to Production, which teaches the terminal, Git, and GitHub first. Compare: [Prompt to Production](https://tinkercademy.com/programmes/prompt-to-production/) ## Course Overview AI coding agents can now plan, edit, test, and review software inside a development environment. This two-day workshop teaches you how to direct that work, keep it grounded in a real user need, and decide whether the result is ready to ship. It's for experienced software developers. Through five practical projects with **Claude Code or Codex**, you'll move from small individual builds to an unfamiliar agentic codebase and a team AI product. Along the way, you'll work with live data, persistent project instructions, reusable capabilities, parallel workflows, external tools, and structured review. The workshop combines product thinking with hands-on engineering. You'll spend less time typing every line and more time framing the problem, setting useful constraints, inspecting the agent's work, testing assumptions, and improving what you build. ## Lesson Outcomes By the end of this course, you will be able to: - **Frame a useful product before building it.** Identify the user, clarify the problem, control scope, and turn an idea into a plan an agent can act on. - **Direct an agent through a real codebase.** Provide durable context and constraints, manage long-running work, and choose when to prompt, plan, intervene, or rewind. - **Connect software to the wider world.** Work with live data, AI models, external tools, and reusable agent capabilities while handling configuration and secrets responsibly. - **Collaborate safely with people and agents.** Divide work, use branches and worktrees, review pull requests, and set clear goals and limits for parallel or cloud-based agents. - **Judge and improve the result.** Reproduce problems, test important assumptions, use evidence to prioritise changes, and polish a working product for its intended audience. ## Curriculum ### Setup and foundations Prepare Claude Code or Codex, GitHub, and the course tools. We'll look at how coding agents work inside a development environment, what changes when implementation becomes faster, and why the developer remains responsible for the outcome. ### Project 1: From problem to working product - Turn a short product brief into a focused application, review the agent's plan, and publish the result. - Practise managing context and recording instructions that should persist across a project. ### Project 2: Building with live data - Explore a real data source, decide who it could help, and build a small product around it. - Learn how to inspect unfamiliar inputs, recover from an unhelpful direction, and keep the build aligned with its purpose. ### Project 3: A deliberately small shared app - Scope and deploy a useful app for a specific group, gather feedback, and turn that feedback into clear engineering work. - Use reusable agent capabilities and parallel workflows to make and review improvements safely. ### Project 4: Working in an agentic codebase - Trace how an existing AI application works, including its model, tools, and external services. - Reproduce a problem, investigate it with coding and browser tools, implement a fix, and review the change through a pull request. ### Project 5: Team AI product - Define a user, desired outcome, and key assumption, then build one complete slice of an AI-backed product. - Extend the project with one deeper agent-engineering technique, improve the end-to-end experience, and present evidence of what worked. ### Presentations and conclusion Teams demonstrate their products, explain the problem and engineering choices, and reflect on the evidence, trade-offs, and next steps. ## Details **Dates and Times**: 10–11 Nov 2026, 19–20 Nov 2026 or 2–3 Dec 2026 (2 full-day sessions, 9:00 to 17:00). **Location**: CT Hub 2, Lavender. **Requirements**: Bring your own laptop. Modern Mac, Windows, or Linux laptops are supported. Participants should be comfortable using a terminal, Git, GitHub, and at least one AI coding tool such as Claude Code or Codex. **Prerequisites**: Experienced software developers. Comfortable debugging, reviewing pull requests, and working in a team. **Tools and accounts**: The course uses Claude Code or Codex as the main coding tool, with a second tool for comparison. The course setup provides six months of access to the selected 5x plan, using either Claude Code or Codex depending on final setup. **Fees** (excl. GST, as of October 2026): S$1,710 per participant. Minimum 10 participants to start. All quoted prices are in SGD and are before 9% GST. Invoicing terms available. ## Enquiries [Enquire now](https://tinkercademy.com/programmes/agentic-engineering-with-claude-code-or-codex/#enquire)