AI for developers

Build, debug and design with GabbyAI.

Use GabbyAI as a technical thinking partner for code, APIs, architecture, debugging, documentation and the decisions that happen around software development.

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Code and debugging Architecture and APIs Powered by SwishAI

GabbyAI Developer assistant

Ready

I need to design an API for a service with authentication and role-based permissions.

GabbyAI

Let's define the resources, authentication flow, roles and permission boundaries first, then we can map them into endpoints.

I also want it to be easy to extend later.

GabbyAI

Then we should separate authentication, authorization and domain logic so new roles and services can be added without redesigning the whole API.

Message GabbyAI

More than code generation

Software development is a chain of decisions.

Developers spend a significant amount of time thinking about systems, interfaces, failures, dependencies and trade-offs before and after code is written.

GabbyAI gives you a conversational workspace for that broader development process. Describe what you are building, provide technical context and continue refining the solution as new questions appear.

Move between architecture, implementation, debugging and documentation without having to reduce every problem to a single isolated prompt.

Across the development lifecycle

One AI assistant for different parts of the build.

Use GabbyAI from the first technical idea through implementation, investigation and documentation.

Architecture

Discuss services, application boundaries, components, data flows and technical trade-offs before implementation begins.

API design

Think through routes, payloads, authentication, permissions, status codes and integration patterns.

Implementation

Turn requirements into code, functions, components and smaller development tasks.

Debugging

Examine errors, logs and unexpected behaviour to reason through possible causes and next steps.

Refactoring

Explore ways to improve structure, readability and maintainability in existing code.

Documentation

Create starting points for technical notes, API documentation, explanations and implementation guides.

Think beyond the snippet

Give the model the context your system actually has.

Better technical conversations come from explaining the environment around the code, not just the line where something failed.

Requirements

Define what the system needs to do

Turn product or business requirements into technical components and implementation tasks.

Context

Explain your environment

Provide languages, frameworks, dependencies, database choices and infrastructure constraints.

Trade-offs

Compare possible approaches

Discuss the practical advantages and limitations of different designs before committing to one.

Integration

Connect systems together

Work through API integrations, authentication, data formats and communication between services.

Investigation

Follow the failure

Add logs, error output and observations as you narrow down where a problem is occurring.

Maintenance

Understand systems you did not write

Explore unfamiliar code paths, dependencies and application structure before making changes.

APIs and backend systems

Design the contract before worrying about every line of code.

Good APIs depend on more than endpoint names. Authentication, authorization, validation, resource ownership and error behaviour all shape the interface.

Use GabbyAI to reason through those decisions before implementation and revisit them as your requirements develop.

The same conversation can then move into schemas, handlers, database interaction and testing.

API design workflow

Define Resources and permissions

↓

Design Routes and contracts

↓

Implement Code, validation and tests

Developer responsibility

Generated code still needs engineering judgement.

AI can accelerate technical work, but generated code can contain bugs, security problems, inefficient approaches or assumptions that do not match your environment.

Review and understand suggested changes, test them in the relevant environment and apply the same engineering standards you would use for code written by a person.

Explore AI for coding → Explore private AI → Privacy & Trust →

Understand before merging

Review generated changes and make sure you understand their behaviour.

Test the implementation

Validate expected behaviour, errors and important edge cases.

Review security

Check validation, permissions, secrets and sensitive data handling before deployment.

Different kinds of developers

Useful whether you are learning, building or maintaining.

Backend developers

APIs, databases and services.

Work through authentication, schemas, queries, integrations and service architecture.

Frontend developers

Interfaces and application logic.

Discuss components, state, API interaction, browser behaviour and implementation approaches.

Infrastructure

Systems around the application.

Think through services, deployment, networking, configuration and operational troubleshooting.

Developers learning

Understand unfamiliar concepts.

Ask follow-up questions about languages, frameworks, protocols and software design.

Explore AI for students →

Developer workflow

Start with the system, not just the symptom.

Explain the environment

Describe the language, framework, service, dependencies and the behaviour you are trying to achieve.

Add relevant evidence

Provide code, logs, payloads or errors that help narrow the problem to the right part of the system.

Implement and validate

Apply the useful parts, test the result and keep refining the conversation when new information appears.

The AI platform behind the developer experience.

GabbyAI is powered by SwishAI, the artificial intelligence platform developed by Swish World Group. As SwishAI evolves, the capabilities available through GabbyAI can evolve with it.

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Frequently asked questions

Using GabbyAI as a developer.

Can developers use GabbyAI for coding?

Yes. GabbyAI can help developers generate and explain code, investigate problems, discuss architecture and work through technical decisions conversationally.

Can GabbyAI help with APIs?

Yes. GabbyAI can help discuss API design, endpoints, authentication, request and response structures, integrations and implementation approaches.

Can GabbyAI help with debugging?

GabbyAI can help examine logs, errors and code, reason through likely causes and suggest debugging steps when sufficient context is provided.

Can GabbyAI help with architecture?

Yes. You can use GabbyAI to discuss application structure, services, data flows, APIs, databases and technical trade-offs.

Can GabbyAI write documentation?

GabbyAI can help create starting points for API documentation, technical notes, explanations and implementation guides that you can review and refine.

Should developers review AI-generated code?

Yes. AI-generated code should be reviewed, tested and validated for correctness, security and suitability before production use.

Is GabbyAI privacy focused?

GabbyAI is developed around a privacy-first approach. Detailed information about data handling is available through the GabbyAI Privacy Policy and Privacy & Trust documentation.

Start building

Bring your next technical problem to GabbyAI.

Create an account and start working through code, architecture, APIs and debugging in conversation.

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