Microsoft presents: Building and shipping agents in Business Central
Building, testing and shipping agents in Business Central: creating and configuring agents in the client (27.4 and newer), model selection in version 28, task simulation, exporting definitions, packaging agents as extensions for production, the AL agent metadata interfaces, and AI evaluation tools for tests.
- Introduction to agents as a first-party product
- Agent configuration: name, language, region, and user access
- Profiles, permissions, and instructions - iterative improvement
- Model selection and agent configuration options
- Testing agents with task simulation and templates
- Task execution analysis: agent actions and user interventions
- Exporting and managing agent definitions
- Moving agents to production via extensions
- Agent template and project structure
- Copilot capabilities and agent lifecycle management
- Agent metadata provider and factory interface
- Agent metadata runtime configuration and optional interface methods
- Evolving agents for production complexity and user intervention
- AI evaluation tools, testing, and quality tracking
Overview
The session from BC TechDays presents agents as a first-party product in Business Central. It walks through creating an agent instance in the client, setting name, language, region and user access, and iterating on profile, permissions and instructions. It then shows testing with task simulation, task templates and the task log, including user intervention steps.
The second half covers shipping. Agents created with instructions in the client cannot run in production, so they are exported and packaged as an extension, with the speaker saying production is supported from version 28. The AL side covers the agent metadata provider enum, the factory and metadata interfaces, and the Copilot capability as a feature gate. The session closes with AI evaluation tools: data-driven, turn-based tests, YAML data sets, an agent test library, credit budgets and run history, available in sandbox only.
Key points
- Agents created with instructions in the client cannot run in production. They must be packaged as an extension and published to the production environment; the speaker says production is supported from version 28.
- Model choice is a dropdown in version 28 (GPT-4, GPT-4.1, with GPT-5 newer). In 27.4 the agent models list is not shown. Models differ in cost, and the speaker expects availability to grow as more models are validated.
- Test agents with task simulation (for email: subject, from, message, attachments) and reusable task templates. The task log shows each run’s steps, tools used, and user intervention requests.
- Export the agent definition from the agents list to collect profile, permissions, instructions, locale and version. Instructions can also be downloaded on their own for an extension.
- Disabling the Copilot capability deactivates all agent instances that use it. Re-enabling it restores them.
- AI evaluation tools run in sandbox only, use your own data sets, and can feed CI/CD. Agent tests are turn-based, use YAML data sets and an AI test type code unit, and depend on the AI development toolkit evaluation extension.
- Budget limits exist at environment and company level. They block new tasks but let running tasks finish, so spend can slightly exceed the limit. Test results show Copilot credits consumed per task; the total tokens column shows only test framework tokens (such as LLM as judge calls), not the agents’ own tokens.
Features
| Feature | Status | At | Evidence |
|---|---|---|---|
| Agent creation and configuration | status not stated, demoed | 1:51 | |
| Manage user access for agents | status not stated, demoed | 3:00 | |
| Profiles and permissions configuration | status not stated, demoed | 4:02 | |
| Agent instructions configuration | status not stated, demoed | 5:12 | |
| Agent model selection | status not stated, demoed | 6:09 | |
| Agent task simulation and testing | status not stated, demoed | 7:08 | |
| Task templates | status not stated, demoed | 8:07 | |
| Task log and execution tracking | status not stated, demoed | 8:53 | |
| Agent tools and capabilities | status not stated, demoed | 10:26 | |
| User intervention in agent workflows | status not stated, demoed | 11:44 | |
| Download agent instructions | status not stated, demoed | 12:55 | |
| Export agent definition | status not stated, demoed | 13:23 | |
| Production agent deployment via extensions | status not stated | 15:45 | |
| Agent template for AL projects | status not stated, demoed | 16:40 | |
| Copilot capability feature gate | status not stated, demoed | 18:03 | |
| Agent metadata provider enumeration | status not stated | 19:19 | |
| Agent factory interface | status not stated | 20:17 | |
| Agent metadata interface for runtime configuration | status not stated | 22:32 | |
| Take agent task execution interface | status not stated | 23:18 | |
| Optional interface methods | generally available (roadmap Evolve AL interfaces with default implementations) | 23:50 | “This is a feature that’s coming up. Actually, Quintin here worked on it, and he’s a he’s ready to release it almost” (23:50) |
| Complex agent scenarios with user intervention | status not stated | 24:33 | |
| AI evaluation tools for agents | status not stated, demoed | 26:54 | |
| Copilot credit consumption visibility in tests | status not stated, demoed | 27:29 | |
| Agent instance experimentation | status not stated, demoed | 27:42 | |
| AI evals suite page | status not stated, demoed | 28:07 | |
| Budget controls for agent tests | status not stated, demoed | 30:14 | |
| Agent task drill-down and troubleshooting | status not stated, demoed | 31:22 | |
| Copilot credit consumption visibility for non-admins | status not stated, demoed | 33:33 | |
| Test run history and trend tracking | status not stated, demoed | 34:03 | |
| Turn-based test design pattern | status not stated, demoed | 34:27 | |
| AI development toolkit evaluation extension | status not stated, demoed | 36:19 | |
| Agent test library | status not stated, demoed | 36:42 | |
| Data-driven agent test approach | status not stated, demoed | 35:51 | |
| AI test suite XML configuration standard | status not stated, demoed | 38:36 | |
| AI test type code unit | status not stated, demoed | 39:58 | |
| AI test type property | status not stated, demoed | 39:16 | |
| Agent test context code unit | status not stated, demoed | 40:42 | |
| YAML-based test data sets | status not stated, demoed | 41:40 | |
| Run turn and wait method | status not stated, demoed | 42:59 | |
| Data-driven agent test framework | status not stated, demoed | 44:01 | |
| Agent debugging with break on next | status not stated | 44:59 |
A status with a roadmap link comes from the Microsoft 365 roadmap feature this part of the video covers (matched by Haiku; links Opus dropped are not used); other statuses need a status word in the video itself.
AL objects mentioned
As heard in the captions. A name that matches one object page by exact type and name links to it; the others stay as named.
- other “agent” at 1:51
- other “agent models list” at 6:22
- other “task template” at 8:07
- other “task log” at 8:53
- other “agents list” at 13:23
- enum “agent metadata provider” at 19:35
- interface “factory” at 20:17
- interface “agent metadata” at 22:32
- interface “take agent task execution” at 23:18
- page “AI evals suite pages” at 28:07
- codeunit “agent test context” at 40:42
- codeunit “AI test context” at 41:23
- codeunit 4321 “Agent” at 43:22
- page 4316 “Agent List” at 45:25
Not found in BC28-30: enum “agent metadata provider”, interface “factory”, interface “agent metadata”, interface “take agent task execution”, page “AI evals suite pages”, codeunit “agent test context”, codeunit “AI test context”.
Quotes
- 0:04 “Agents are no longer just experiments. They’re becoming a first-party product inside of Business Central.”
- 1:30 “This is all available for you today. You can look at it in the client. Um from 27.4 and newer.”
- 2:37 “Maybe this instance of my agent needs to work in a certain locale. Maybe it’s a US decimal points or it’s a European decimal”
- 4:16 “As you mature the agent, you need to come back and figure out if the agent is seeing too much or not seeing enough”
- 6:22 “you wouldn’t even see this agent models list. That would be for 28 where you have now this drop down”
Disclaimers in the video
- 6:22 subject-to-change: I expect that when we validate more and more models, we will increase the availability here
- 23:50 coming-later: This is a feature that’s coming up. Actually, Quintin here worked on it, and he’s a he’s ready to release …
- 27:53 preview: this is available in sandbox only since this is a testing tool, but you’d be running this before going to production
Presenters (as heard): Blazhe, Stefan, Quintin.
