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Agentic Development in Business Central: Using Instructions to Guide Your Coding Agent

Roberto Corella July 24, 2026 AL · Agentic Development · GitHub Copilot

When we talk about agents in Business Central, we almost always think of end-user features: a copilot that helps issue an invoice, analyze sales, or answer a question inside the app. But there's another use, less visible and just as powerful: applying agents to the development process itself — using them to write AL code, create tables, pages, and the rest of the objects that make up an extension.

This article opens a series on agentic development in Business Central, starting with its most basic building block: instructions.

GitHub Copilot agent mode in Visual Studio Code, generating AL objects for Business Central

What is agentic development

Agentic development means working with a coding agent — in this case, GitHub Copilot in agent mode inside Visual Studio Code — that doesn't just autocomplete lines, but carries out complete tasks: it creates tables and pages, reads app.json to understand the project's context, and proposes changes that the developer can accept or discard.

The goal isn't to replace the development team, but to increase its productivity, delegating repetitive or structural work so the team can focus on design and business logic.

The problem with starting from zero

Asking an agent for something as simple as "create a table and a page called Logging with the following fields: ID, Description, Time, Date" works, but the result reflects exactly what was typed in the prompt: field names appear as-is, with no naming conventions, no company prefix, and sometimes no consistent choice of language.

It's a decent starting point, but not the result most teams need to keep code consistent across developers.

Instructions: the first building block of agentic development

To fix this, GitHub Copilot lets you define persistent instructions that the agent automatically reads whenever it works on a given file type. In an AL project, this is organized as follows:

From that point on, any instruction you define becomes a rule the agent follows automatically, without the developer having to repeat it in every prompt.

Example of an instructions file with an applyTo header targeting .al files

What kind of rules are worth defining

For AL, some of the most useful instructions are:

Repeating the exact same initial prompt (create the Login table and page) once these instructions are in place changes the outcome completely: the agent respects the prefix, applies PascalCase, follows the defined naming pattern, and uses English field names — because now it's part of a rule, not a one-off preference.

Result generated by the agent once naming and language instructions are applied

Why this matters

Instructions aren't a decorative feature: they're how you make sure a coding agent behaves according to the team's standards instead of improvising on every interaction. The clearer the instruction, the less room the agent has to make its own calls — like picking a field's language without ever being asked to.

This is just the first piece of agentic development applied to Business Central. Future entries will add more pieces: other tools, additional configuration, and examples that take this workflow beyond the basics.

If your team is already experimenting with coding agents on AL projects, defining a solid instructions file is the step with the best return for the least effort.

Watch the full walkthrough — the video below (in Spanish) shows this exact example live in Visual Studio Code, from the first ungoverned prompt to the fully-instructed result.

Video walkthrough

If you found this content useful, you can buy me a coffee — it helps me keep writing and recording. Thank you!
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