Effective Work with AI Agents
Hands-on workshop so developers get more from AI coding tools—without the confusion or cost creep
The Challenge
Many developers struggle with AI coding assistants: the tool doesn't do what they expect, costs spiral, and it's unclear when to use which feature. This workshop is for teams who use - or want to use - tools like Cursor, GitHub Copilot, or Claude for coding. It gives them a clear playbook and hands-on practice so they can work more effectively, keep costs under control, and reuse good habits across the team.
Our Approach
We started with safety and cost: how to restrict which files and folders the AI can access, so secrets and critical code stay protected. Participants learned simple habits like starting a fresh conversation for a new task, that keep usage predictable and costs down.
Next we covered how to get better results: choosing the right way to work for each task (not always the most powerful mode), and planning before asking the AI to code. The main idea: giving the AI a clear, focused context beats clever prompting.
Teams then saw how to write down their preferences and standards so the AI follows them project after project, and how to add custom shortcuts for routine tasks. We closed with optional integrations that let the AI use external tools and data when needed.
Participants tried the practices on real scenarios and took away a short handbook and shared exercises, so they could apply what they learned as soon as they were back at their desks.
The Results
Participants left with a shared way of working and concrete habits: protect what the AI can see, keep conversations focused, and pick the right mode for the job. They learned that clear context and simple guardrails matter more than prompt tricks. With the handbook and exercises, they could start applying what they learned the very next day.
Developers using AI coding tools Audience
Workshop + handbook + hands-on exercises Format
Practices you can use tomorrow Outcome
Technologies Used
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