AI app for it and development · no coding needed
Source-linked software development assistant console
Reduce tool sprawl and review effort while keeping code decisions traceable.
Made for: Software teams and administrators building and maintaining codebases
What it does for you
The problem
Development teams rent several coding assistants, lose context between them, and cannot trace AI suggestions back to the code, ticket or policy they came from.
What it gives you
Reviewer-approved code changes linked to their sources
What you give it
Repository codeticketstestsdependency manifestscoding standards
Build your own version of Aide, SOTA SWE and more
One app with what these 10 AI tools do, yours to keep and change: Aide, SOTA SWE, M9 Developer, Cursor 1.0, Cursor, Fynix, Kilo Code for VS Code, Zed Agentic Editing, CodeX-Editor, Continue 1.0.
Everything these tools do, in one app
- AI code generation Generates code from scratch or based on natural language instructions.Found in Cursor, M9 Developer, Fynix and 2 more
- Context-aware code completion Provides intelligent autocompletion and suggestions based on the current coding context.Found in Fynix, CodeX-Editor
- Bug detection and debugging Detects bugs and offers debugging suggestions to fix errors.Found in SOTA SWE, M9 Developer, Cursor 1.0 and 2 more
- Automated code review Automatically reviews code or pull requests to catch issues and suggest improvements.Found in SOTA SWE, Cursor 1.0
- Code refactoring Suggests and performs code refactoring to improve readability and maintainability.Found in Fynix, CodeX-Editor
- Real-time collaboration Enables team members to collaborate on code in real time.Found in SOTA SWE, M9 Developer
- Version control integration Integrates with version control systems like Git for code management.Found in SOTA SWE, M9 Developer, Fynix and 1 more
- IDE integration Integrates seamlessly into popular integrated development environments.Found in M9 Developer, Fynix, Kilo Code for VS Code
- Natural language commands Allows interaction with the tool using plain English commands.Found in Cursor, Fynix, Kilo Code for VS Code
- Multi-file editing Supports creating and modifying multiple files automatically.Found in Kilo Code for VS Code, Zed Agentic Editing
- Command line execution Runs command line prompts directly from the tool.Found in Kilo Code for VS Code
- Background task management Runs long-running AI tasks in the background and notifies upon completion.Found in Zed Agentic Editing, Cursor 1.0
- Customizable AI settings Allows customization of AI behavior to match user preferences or coding style.Found in Aide, Fynix, CodeX-Editor
- Project management tools Includes task tracking and version control assistance for project management.Found in M9 Developer
- Automated documentation Automatically generates code documentation to maintain clarity.Found in SOTA SWE
- Jupyter Notebook support Enables AI-assisted coding in Jupyter Notebooks for data science.Found in Cursor 1.0
- One-click migration Imports extensions, themes, and keybindings from VSCode with one click.Found in Cursor
- Local security and privacy Provides local options and privacy mode to protect sensitive code.Found in Cursor
- Text continuation Generates coherent text continuations for writing tasks.Found in Continue 1.0
- Data analysis and visualization Interprets complex datasets and provides clear visualizations.Found in Aide
How it works, step by step
- Generate code from natural language instructions
- Complete code from current context
- Detect bugs and suggest fixes
- Review code and pull requests automatically
- Refactor code for readability and maintainability
- Support real-time team collaboration on code
- Integrate with Git version control
- Run inside common IDEs
- Accept plain English commands
- Edit multiple files in one task
- Execute command line prompts
- Run long AI tasks in the background and notify on completion
- Customize AI behavior to team style
- Track tasks and version control assistance
- Generate code documentation
- Support Jupyter Notebooks
- Import extensions, themes and keybindings in one click
- Offer local and privacy modes for sensitive code
- Continue text for writing tasks
- Analyze datasets and produce visualizations
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewer-approved code changes linked to their sources with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Source-linked software development assistant console with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Source-linked software development assistant console with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data196 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce tool sprawl and review effort while keeping code decisions traceable. For software teams and administrators building and maintaining codebases, convert repository code, tickets, tests, dependency manifests and coding standards into reviewer-approved code changes linked to their sources. The benefit is a testable hypothesis, measured through accepted changes per developer hour and rework after merge; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect repository code, tickets, tests, dependency manifests and coding standards, then follow this sequence: 1. Generate code from natural language instructions. 2. Complete code from current context. 3. Detect bugs and suggest fixes. 4. Review code and pull requests automatically. 5. Refactor code for readability and maintainability. Resolve uncertain cases with qualified reviewers, approve reviewer-approved code changes linked to their sources, and measure accepted changes per developer hour and rework after merge against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One repository language and framework set; final architecture, security and merge decisions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve code ownership, source attribution, license accuracy and usage permissions. Reviewers approve substantive changes and merge scope. One repository language and framework set; final architecture, security and merge decisions remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One repository language and framework set; final architecture, security and merge decisions remain human. Implement one approved input format, a bounded representative case set and the first two task modules: generate code from natural language instructions; complete code from current context. Support the third module with operator review: detect bugs and suggest fixes. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Team-owned repositories, authorized tickets and permitted documentation sources. Cloud code storage, IDE import/export and deployment destinations. Start with file exchange and validate destination specifications before promising direct deployment. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Repository and task intake, Editable change preview, Review and delivery. Use a thumbnail gallery for repositories and tasks, a large central editing canvas, and a right-hand panel for sources, constraints and comments. Let users compare versions side by side. Display draft, changes requested and approved states. Provide a reviewer preview link with comments anchored to the relevant file and line. Make the task-specific outcome reviewer-approved code changes linked to their sources visible beside its evidence, review state and value baseline.
