BLACKBOX AI offers developers a complete software development toolkit and platform for composing, checking, and building AI-powered software.
BLACKBOX AI’s primary feature is an AI coding assistant for VS Code. Beyond this core feature, the platform includes a coding agent and terminal-based development with an included command line interface (CLI). Additionally, BLACKBOX AI provides users with an app and web app development suite and an agent API.
Though BLACKBOX AI allows developers to generate code, the code requires review. Code generated by BLACKBOX AI needs to be inspected and tested to confirm it is safe and correct for production.
BLACKBOX AI is an AI coding and development platform that allows users to perform a myriad of development and coding tasks, as well as review and generate code. The platform provides coding assistants and agents for VS Code and other development environments.
Beyond basic autocomplete, its technology seems relatively advanced. Currently, the company says its technology can do things like:
- Generate and complete code
- Debug code
- Review code and suggest changes
- Generate and complete tests
- Write documentation
- Create projects and provide project-wide summary code
- Generate code for interactive command line applications
- Provide coding assistance with AI coding co-pilots
- Offer different AI models
- Work with GitHub and other coding platforms
- Create desktop and web applications and the code to control the applications
- Use its technology through an application programming interface (API)
For programmers just starting out as well as experienced programmers, BLACKBOX AI has applications.
What is the Difference Between Blackbox AI and Black-box AI?
BLACKBOX AI is a brand name of a software development platform.
Black-box AI is an artificial intelligence and complex systems theory in which the inner workings of a system are obscure or opaque to an outside observer.
When a person is interested in learning more about coding and wants a coding assistant, BLACKBOX AI is the software development platform that person is interested in learning more about.
What Can Blackbox AI Do?
The BLACKBOX AI platform can do a number of things related to software development. It can:
- Create code based on instructions given in plain language
- Explain code
- And more.
BLACKBOX AI can help describe code elements and rationale in code.
This includes describing functions and classes and the rationale for design decisions, and illustrating the flow of control and data in code.
The AI can also provide possible causes for errors and describe why code may behave in a particular way.
This can be very helpful when having to work with and understand code that has been developed by others.
3. Debugging
The AI can also be used for debugging by providing error messages and relevant code and having the AI explore possible solutions.
An example prompt for the AI to debug a piece of code may be as follows:
The developer of a node.js based API has provided a 500 server error for an end point for user login.
In this case, the AI should provide the rationale for the issue and recommend a change to resolve the problem.
It should not change any code outside of the function which implements the end point.
4. Refactoring
BLACKBOX AI can be used to assess and recommend changes to code to improve it’s overall readability and quality.
This may include refactoring large functions to be smaller, or removing redundant code, or improving the quality of type definitions in TypeScript.
The AI can assess code for callbacks and recommend improvements for readability by using async/await patterns.
The AI can also recommend changes to business logic to improve the overall quality of code.
5. Generate and Evaluate Code
The AI can also be used to generate and evaluate code.
As an example, the AI can generate tests for a function to calculate the total amount of an invoice.
These tests may consider cases with normal invoices, zero item invoices, invoices with discounts, invalid quantity cases, tax cases and cases with rounding.
It is the responsibility of the developer to validate that the tests generated by the AI cover the intended cases and behavior.
6. Create Documentation
BLACKBOX AI can create different types of documentation, including code comments, documentation for functions and other code elements, code element and program descriptions, readme files, and other types of program documentation. It can create explanatory texts for code changes and other technical documentation. It can also be used to generate commit messages.
Blackbox AI Features
BLACKBOX AI focuses on providing different features for software development. Some of its features are incorporated in code editing and reviewing, compiling, linking and running code, code refactoring, and code generation. Others are incorporated in the testing and debugging of a software application. It can also be used to create documentation for a software application.
BLACKBOX AI for VS Code
The VS Code extension provides programming related AI features and assistants directly from the code editor. According to the extension’s documentation, it can be used to generate code for software development, review code, and assist in other software development activities.
Using the extension
The extension can be installed and used by all users of the Visual Studio Code.
- Open the Extensions pane.
- Search for BLACKBOX AI
- Click the “Install” button.
- If prompted, sign in to your BLACKBOX AI account.
Once the extension is installed, the coding agent can be directed to perform different programming related activities.
BLACKBOX AI CLI
The BLACKBOX CLI provides the same AI features of the BLACKBOX AI programming assistant for software development, coding and related activities for users of different operating systems. The CLI can be used to generate code, assist in debugging and testing a software application, create and review project documentation and other software related documentation, search and understand project files, refactor project code, and analyze and visualize performance metrics and other diagnostic information of a software application. The CLI can also integrate and manage other AI agents.
The coding agent can perform a variety of actions, including reviewing code and other files, understanding code changes, modifying code, and running development commands.
The Agent API allows users to build sophisticated interactions with the BLACKBOX AIs. Users have programmatic control over various aspects of agent interactions, from constructing and managing task lists to streaming agent conversations and working with files in the agent’s sandbox.
The Agent API allows developers to incorporate agent functionality in custom applications.
The Agent API is able to create agent tasks and interact with GitHub. Documents regarding the Agent API describe the runtimes of the Codex and Claude models, and other chat completions models.
To use agent workflows with GitHub, a user must have a GitHub account and the documentations states a pro account is required to use the configuration endpoint.
The BLACKBOX Builder is able to generate code from user input in a variety of applications.
The Builder can generate other components of an application and update existing components.
This is different from requesting a code snippet from a chat completions models.
To use BLACKBOX AI, one must have a target in mind.
To achieve the target, it is useful to provide relevant context. Context is everything for coding tasks.
This section contains information that is pertinent to completing the task. For example:
- Language
- Framework
- Architecture
- Database
- API
- Expected behavior
- Error messages
- Constraints
Testing
BLACKBOX AI extensions for VS Code allow context to be captured from code, files, folders, Git commits and URLs.
Step 3: Ask for a Plan Before Large Changes
For changes that may be advanced or complicated, ask the agent to provide an explanation of the plan prior to changing code.
An example of an adequate plan may be:
- Initially examine the code flow to determine where and how the defect may be occurring.
- Provide an explanation of the current code flow to determine where the defect may be occurring.
- Identify the files that require changes.
- Explain the potential solution to the defect and recommend changes to the code.
- Indicate the types of tests that need to be added.
Step 4: Make Many, Small Changes
It is appropriate to break down large, complicated tasks into smaller, less complicated tasks and sub-tasks.
An example of a large, complicated task may be:
- Build and populate the database.
- Provide access controls and protect the data.
- Establish and protect the application Programming Interfaces (API).
- Create and Validate the front end.
- Test and verify the application.
Step 5: Verify Changes and Explain Code
Because code is generated by a software application, there may be hidden dependencies and/or a loss of security controls.
Verify the changes addressed the issue and check for side effects.
Step 6: Perform Tests
Changes made by the AI should be validated by tests. Explore edge cases and check application logs.
Blackbox AI Example Prompts
When creating a prompt, one must include the context, the task, constraints, and the desired output.
Context:
Task:
Constraints:
Desired Output:
Generate a TypeScript Function: calculateShippingCost()
The function must have the ability to:
- Reject function execution if the weight is negative.
- Include type definitions for type safety.
- Write unit tests.
Debug Authentication Error
Users should be able to provide valid credentials and receive a session token.
Valid credentials are provided to the API, but an unauthorized response (HTTP 401) is returned.
For what reason is the authentication flow failing?
Explain your reasoning before proposing code changes.
Refactoring Code
What changes should be made to the code to improve the following?
- Readability
- Extract repetitive code
- Remove unneeded class state
- Maintain the current public class interface
- Write unit tests for the changes
API Security Review
What security concerns are raised by this implementation?
- Is users’ access controlled (i.e. authorized)?
- Is user input validated?
- Are SQL Injections or other Injectattacks protected against?
- Are secrets protected?
- Are dependencies managed?
- Is control flow and error handling secured?
Prioritize your findings.
No code changes are permitted at this time.
Is Blackbox AI Free?
Blackbox AI offers a free and a paid version of their product. The free version is limited and pricing can be expected to change.
Before the recent pricing changes, a paid version was offered, in addition to a free version, by a third party.
The information in this article becomes outdated quickly.
For example, articles with information about monthly subscription prices will not reflect prices of the product in the future. To find the price of the product, refer to the page with product prices.
What Models Does Blackbox AI Use?
One of the strengths of the current Blackbox AI product is its use of multiple models.
Blackbox AI provides an API which has agents for several models. Currently, it supports models from both OpenAI and Anthropic. Using this API, developers can integrate models in their applications.
Different models vary in terms of:
- Code generation
- Debugging
- Reasoning
- Refactoring
- Tasks involving long contexts
- Agent based interaction
- Efficiency
- Expensiveness
A developer is free to choose a model based on their use case.
Blackbox AI for Beginners
It is a common misconception that one has to be an expert programmer to use coding AI tools.
Using Blackbox AI, beginners can do the following:
- Get an introduction to programming concepts
- Write simple computer programs
- Create simple computer programs
- Understand the meaning of error messages
- Code in a different computer language
- Create computer programs which test and evaluate other computer programs
- Make simple adjustments to computer programs
- Explain computer programs
Although coding AIs can produce correct and working code, beginners should not fully depend on coding AIs for their work. A best practice is to explain the concept to the coding AI, understand the concept, and test the coding AI implementation.
It shifts the function of AI from a replacement for programming to a supplement.
Blackbox AI is for more experienced developers.
Instead of asking for code examples, users can ask Blackbox AI to do things like:
- Check out a repository
- Generate boilerplate code
- Refactor code
- Create and run tests
- Locate and fix code bugs
- Create and update code documentation
- Evaluate and give feedback on code
- Assist with migrating code
- Help with repetitive coding tasks
A featured component of Blackbox AI is the ability to write code at the project, Git commit, URL, and conversation levels.
For larger organizations, the real question is how the AI integrates with the organization’s current processes for developing and reviewing code.
Is it safe to use Blackbox AI?
The safety of the AI depends on the context and the input provided.
AI generated code might contain:
- Invalid/incorrect code
- Secure coding violations and code vulnerabilities
- Outdated code
- Code that does not appropriately handle/report errors
Most review the AI and state similar things. Most emphasize the importance of reviewing the generated code, adjusting the AI’s permissions, and controlling the AI through a framework agreement.
It is recommended that you review Blackbox AI’s privacy and security documentation and processing framework agreement to better ensure the safety of your organization’s code.
The controls and features offered by Blackbox AI depend on the type of contract you have with them. Features offered to one organization may not be offered to all organizations.
Features offered include end-to-end data/code encryption, data/code retention controls, SSO, RBAC, audit log controls, and data location controls.
Prior to using Blackbox AI for your organization’s code, you should review the code to remove sensitive information and ensure that codes, secrets, and keys are not embedded in the code.
- Examine repository permissions.
- Inspect dependencies generated.
- Examine significant changes to code.
- Complete automated software tests.
- Perform penetration tests.
- Understand your organization’s data retention policies.
- Verify your organization’s data privacy and security policies.
Traditional Programming vs. Blackbox AI
Although programming with the help of Blackbox AI is gaining popularity, writing computer code using traditional methods is not disappearing any time soon.
With Blackbox AI, traditional programmers can re-prioritize how they spend their time, and potentially reduce the effort required to accomplish coding tasks.
Blackbox AI can help users quickly create functioning prototypes.
Using Blackbox AI does not deprive programmers of the ability to control the end result.
Programmers still have the final say on the solution to a coding problem.
Blackbox AI can help automate some repetitive tasks and speed up the coding process, and perhaps assist in filling in missing parts of a developer’s code.
Blackbox AI compared to the Rest
According to results from popular search engines, Blackbox AI, along with tools such as GitHub Copilot, Cursor, Tabnine, Aider, Claude Code, and other AI-based coding tools, are the most sought after and used tools in the field.
Rather than focusing on which tool comes out on top, it is more helpful to define each tool in relation to the other tools in the same category.
Things to be Aware of
Potential Benefits
BLACKBOX AI offers several features to assist users with the following activities:
- Request AI assistance and integrate it with their coding activities.
- Choose from a selection of models.
- Generate code.
- Identify and suggest solutions to bugs.
- Understand and assist with larger project activities and tasks.
- Work from a command line interface (CLI).
- Create coding agents.
- Generate apps and software.
- Interact with APIs to assist with agent activities and tasks.
The platform provides documentation that describes features and functions beyond computer code completion.
Potential Shortcomings
limits of coding with AI include:
- Producing correct and valid solutions to user requirements and problems.
- Generating and adding new and unknown bugs to the code and project.
- Modifying project and code files.
- Introducing code project complexity and complexity to the code.
- Using and employing out-dated and obsolete coding standards and codes.
- Not identifying edge cases and conditions.
- Producing and implementing codes that contain vulnerabilities and security breaches.
Third-party users reviewing and evaluating the platform express concerns about the quality of output generated by the AI, as well as its reliability and performance when assisting with more complicated and larger activities and tasks.
How to Effectively Use the BlackBox AI Platform
In your interactions with the BlackBox AI, consider the following:
- Provide precise details to describe your coding tasks.
- State what should not change.
- Ask for assistance to code tests and implementation.
1. Create Tests
“Now create tests covering normal behavior, invalid input, edge cases, and error cases.”
2. Review Before Accepting Changes
When suggesting changes to workflows that involve interacting with agents, review the changes and the resulting diff before accepting the suggestion.
3. Give Agents Bounded Tasks
A better, more definable task would be something like this:
Resolving the issue with the checkout form validation bug.
This task specifies an end point, and does not allow for interpretive Freedom, like the previous example.
There are a number of characteristics of a good blackbox AI workflow.
There are a total of 7 steps in the workflow.
Incorporating and automating these steps will result in an end to end AI coding assistant.
The risk with using an AI coding assistant is prevalent when programmers take the suggestion of the AI and implement it without thoroughly reviewing the changes.
Generating as much code as possible is not the goal of using the AI coding assistant.
The goal is creating the optimal, correct, and useful code for the specified task.
Frequently Asked Questions About Blackbox AI
What is Blackbox AI Used For?
BLACKBOX AI is used to perform various software development tasks such as coding, testing and documentation, and other tasks like software project development and debugging. It can also be used to generate software codes.
Is Blackbox AI a Coding Tool?
Yes. BLACKBOX AI is a tool to assist software development. Its products include coding tools, coding agents, and an API. BLACKBOX AI also offers a service to build software applications.
Can Blackbox AI generate software applications?
Although BLACKBOX AI can assist in application development, a generated application requires further editing to include other functionalities like testing.
Is Blackbox AI available for Visual Studio Code?
Yes. BLACKBOX AI has released an extension to Visual Studio Code, which, in addition to coding tools, includes an AI assistant.
What is Blackbox AI’s Command Line Interface?
BLACKBOX AI allows users to develop software using AI tools and codes on various computer operating systems by providing Command Line Interfaces.
Can I use Blackbox AI to develop applications on GitHub?
The BLACKBOX Agent API allows users to develop and monitor AI agent tasks for GitHub.
Does Blackbox AI provide an Agent API?
Yes. The BLACKBOX Agent API allows users to develop software applications and manage AI tasks.
Should developers be permitted to rely on AI-generated code?
Developers must review and test code generated by AI. AI-generated code poses risks for many common software development activities. These risks are magnified for code developed for authentication, financial transactions, and other security-sensitive code including code for updates and changes to a database or other secured systems. AI-generated code should not be deployed for production systems without being reviewed and tested by human developers.
Finally, thoughts on Blackbox AI
BLACKBOX AI’s initial concept was to provide an AI-based code completion tool. However, during its recent years of development, the team has expanded the scope of the tool to include IDEs and terminal functions, as well as additional features. At the core of BLACKBOX AI is a coding agent and application generator.
From the perspective of software developers, the level of benefit provided by BLACKBOX AI is dependent on a number of factors, including the developer’s experience, the coding conventions and best practices governed by the organization, the type and complexity of the application being developed, and the model employed by BLACKBOX AI.
