@ -4,7 +4,21 @@ The new ABP Studio release introduces a deeply integrated set of features design
At the center is **ABP Agent**, our AI coding assistant. Around it are long-standing ABP Studio capabilities that have been brought together into a single development loop. Together they turn ABP Studio into a single place where you architect and code your ABP solutions.
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## Meet ABP Agent
ABP Agent is the AI coding assistant built into ABP Studio. It operates in three modes, each tuned for a different stage of work:
- **Agent mode**: the implementation mode. The agent reads the solution, writes and edits files, builds the affected projects, runs your apps, watches the runtime, and iterates until the change works end-to-end.
- **Plan mode**: read-only planning. The agent investigates the codebase, researches the official ABP documentation, and produces a structured implementation plan (Problem, Solution, Workflow Diagram, Files Affected, Expected Result). When you are happy with the plan, a single click promotes it into Agent mode and the implementation starts from the plan.
- **Ask mode**: read-only Q&A. The agent explains how something works, draws diagrams, and answers questions about your code without touching any files.
The agent is **ABP-aware by default**. It is instructed to prefer ABP base classes over plain POCOs, repositories over direct `DbContext` injection, `ApplicationService` over plain services, the ABP permission system over `[Authorize(Roles=…)]`, localized strings over hardcoded text, `BusinessException`/`UserFriendlyException` over plain `Exception`, the distributed cache abstraction over raw memory cache, and background job abstractions over hand-rolled hosted services. When it is unsure about an ABP feature, it consults the official ABP documentation as a primary source of truth, not random blog posts on the web.
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@ -25,22 +39,10 @@ ABP Agent and the surrounding ABP Studio features were built to close exactly th
---
## Meet ABP Agent
ABP Agent is the AI coding assistant built into ABP Studio. It operates in three modes, each tuned for a different stage of work:
- **Agent mode**: the implementation mode. The agent reads the solution, writes and edits files, builds the affected projects, runs your apps, watches the runtime, and iterates until the change works end-to-end.
- **Plan mode**: read-only planning. The agent investigates the codebase, researches the official ABP documentation, and produces a structured implementation plan (Problem, Solution, Workflow Diagram, Files Affected, Expected Result). When you are happy with the plan, a single click promotes it into Agent mode and the implementation starts from the plan.
- **Ask mode**: read-only Q&A. The agent explains how something works, draws diagrams, and answers questions about your code without touching any files.
The agent is **ABP-aware by default**. It is instructed to prefer ABP base classes over plain POCOs, repositories over direct `DbContext` injection, `ApplicationService` over plain services, the ABP permission system over `[Authorize(Roles=…)]`, localized strings over hardcoded text, `BusinessException`/`UserFriendlyException` over plain `Exception`, the distributed cache abstraction over raw memory cache, and background job abstractions over hand-rolled hosted services. When it is unsure about an ABP feature, it consults the official ABP documentation as a primary source of truth, not random blog posts on the web.
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## How ABP Agent Sees Your Application: The Analyze Engine
Before ABP Agent answers anything, it needs to *understand* your solution. This is where the **Analyze** feature does the heavy lifting.
When you open a solution, ABP Studio analyzes every package and builds a structural map: the application's **skeleton**. It identifies what each type actually is in ABP terms: an aggregate root, an entity, a value object, a repository interface or implementation, a domain service, an application service or interface, a DTO, an integration service, a controller, an HTTP API, a background job or worker, an event handler, an ETO, a SignalR hub, a DbContext (EF Core or MongoDB), a permission/feature/setting provider, a global feature, a Mapperly or AutoMapper profile, a fluent validator, a menu contributor, a data seed contributor, an options class, an ABP module with its `[DependsOn]` chain, and many more.
@ -70,6 +72,8 @@ The agent also scopes builds intelligently. It can build a single project, a sin
This is the half of ABP Agent that no general-purpose AI IDE can replicate, because no general-purpose AI IDE has a first-class runner for distributed .NET solutions.
**Solution Runner** is the ABP Studio feature that knows about every runnable thing in your solution: web apps, microservices, gateways, identity servers, background workers, CLI applications, mobile and SPA front-ends, plus the Docker containers your stack depends on (databases, caches, message brokers). Apps are grouped into folders and can be launched as a coherent set under a named *run profile*. You start everything with one click; ABP Studio handles ports, dependencies, restart-on-failure, and embedded browser previews.
@ -126,6 +130,8 @@ The Task Runner integration is what makes the *After* phase especially valuable.
## Git & GitHub: Reviewing and Committing Without Leaving the IDE
ABP Studio now ships a full Git client with deep GitHub integration. The goal is simple: once the agent finishes a change, you should be able to review, commit, push, branch, and respond to review feedback **without ever leaving ABP Studio**.
The Git side covers everything you'd expect:
@ -151,8 +157,6 @@ Two AI-assisted touches make this loop especially smooth:
The result is a *closed loop*: the agent writes the change, you (or the AI reviewer agent) review the diff, you let the agent fix the comments, you commit with an AI-suggested message, you push, and you head to GitHub for the pull request, all from inside ABP Studio.
İsmail ÇAĞDAŞ
4 months ago
GitHub
