AI app for it and development · no coding needed
Source-linked development assistant and admin console
Consolidate coding assistance, review and task management into one owned console.
Made for: Software teams and engineering organizations building and maintaining codebases
What it does for you
The problem
Development work is spread across separate AI coding tools, so context, review and task tracking fragment and teams lose control of their own code and workflow.
What it gives you
Source-linked code changes with named-owner approval
What you give it
Repository codetask trackersterminal sessionsmodel choices
Build your own version of Fine, Amazon Q Developer and more
One app with what these 10 AI tools do, yours to keep and change: Fine, Amazon Q Developer, Helix, GoCodeo, OpenCode Superapp, Zero Setup AI Coding with OpenHands, Devin for Terminal, Jolt AI, OpenDevin, Pythagora AI.
Everything these tools do, in one app
- Autonomous task execution AI agents independently handle complete development tasks with minimal user input.Found in Fine, OpenDevin, Zero Setup AI Coding with OpenHands and 1 more
- Codebase understanding Analyzes your existing code to provide context-aware assistance.Found in Fine, Jolt AI
- Code generation Automatically writes code based on requirements or prompts.Found in Fine, GoCodeo, Pythagora AI
- Automated testing Runs tests on generated code to ensure functionality.Found in Fine, Pythagora AI
- Pull request creation Generates pull requests for code changes.Found in Fine
- Interactive code review Allows developers to comment and request revisions from the AI.Found in Fine
- Continuous learning Improves code quality over time by learning from interactions.Found in Fine
- Task management integration Connects with platforms like Linear and Jira to manage tasks.Found in Fine
- Multi-language support Supports programming languages including Python, JavaScript, and Java.Found in GoCodeo
- Real-time code completion Provides code suggestions as you type.Found in GoCodeo
- Error detection Identifies errors in code in real-time.Found in GoCodeo
- Context-aware suggestions Offers suggestions based on the current code context.Found in GoCodeo
- Code optimization tips Suggests ways to improve code performance.Found in GoCodeo
- IDE integration Integrates with popular code editors and IDEs.Found in GoCodeo
- Multi-model backend Allows choosing between cloud, local, or self-hosted AI models.Found in OpenCode Superapp, OpenDevin
- Voice control Enables interaction with the AI using voice commands.Found in OpenCode Superapp
- Supervised computer use Agents operate applications under human oversight with permission settings.Found in OpenCode Superapp
- Offline dictation Local speech recognition works without an internet connection.Found in OpenCode Superapp
- Custom widgets and extensions Users can build their own widgets and integrations.Found in OpenCode Superapp
- Web browsing AI can browse the web to gather information during coding.Found in Zero Setup AI Coding with OpenHands
- API calls Supports making API calls and integrating with external services.Found in Zero Setup AI Coding with OpenHands
- Terminal command execution Executes terminal commands and scripts directly.Found in Zero Setup AI Coding with OpenHands, Devin for Terminal
- Cloud session handoff Continues tasks in the cloud after local machine is shut down.Found in Devin for Terminal
- Fast onboarding Quick setup time to get started.Found in Devin for Terminal
- Benchmark performance Proven capabilities on engineering benchmarks and real-world tasks.Found in Devin for Terminal
- Automatic context file identification Automatically finds relevant files for the prompt.Found in Jolt AI
- Multi-file code modifications Supports changes across multiple files in large projects.Found in Jolt AI
- Code style matching Generates code that matches existing style.Found in Jolt AI
- Scalability for large codebases Handles codebases with millions of lines of code.Found in Jolt AI
- Integrated chat interface Provides a chat for questions, brainstorming, and documentation.Found in Jolt AI
- Open-source availability Encourages community contributions and transparency.Found in OpenDevin, Zero Setup AI Coding with OpenHands
- Local execution Can be run locally for control over deployment and data privacy.Found in OpenDevin, OpenCode Superapp
- Natural language interaction Describe project requirements in plain language to generate code.Found in Pythagora AI
- End-to-end development automation Covers planning, coding, testing, debugging, and deployment.Found in Pythagora AI
- Multiple specialized AI agents Dedicated agents handle specific tasks like code reviews and pair programming.Found in Pythagora AI
- Frontend and backend creation Generates frontend and backend based on specifications.Found in Pythagora AI
- Deployment options Choose between cloud or own infrastructure for deployment.Found in Pythagora AI
How it works, step by step
- Execute autonomous development tasks with minimal input
- Analyze existing code for context-aware assistance
- Generate code from requirements or prompts
- Run automated tests on generated code
- Create pull requests for code changes
- Support interactive code review with comments and revisions
- Improve suggestions from recorded interactions
- Connect with Linear and Jira task platforms
- Support Python, JavaScript, Java and other languages
- Provide real-time code completion as you type
- Detect errors in code in real time
- Offer context-aware suggestions from current code
- Suggest code optimization improvements
- Integrate with popular editors and IDEs
- Allow cloud, local or self-hosted model backends
- Accept voice commands for interaction
- Operate applications under human oversight with permissions
- Provide offline dictation with local speech recognition
- Let users build custom widgets and extensions
- Browse the web to gather information during coding
- Make API calls to external services
- Execute terminal commands and scripts
- Hand off sessions to the cloud after local shutdown
- Onboard quickly with minimal setup
- Track benchmark and real-world task performance
- Identify relevant context files automatically
- Modify multiple files across large projects
- Match generated code to existing style
- Scale to codebases with millions of lines
- Provide an integrated chat for questions and documentation
- Offer open-source availability for community contribution
- Run locally for deployment and data control
- Accept natural language project requirements
- Automate planning, coding, testing, debugging and deployment
- Use specialized agents for reviews and pair programming
- Generate frontend and backend from specifications
- Choose cloud or own infrastructure for deployment
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 development assistant and admin 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 development assistant and admin 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 links6 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare24 KB
- prompt-vps.mdThe same build on your own server (Docker)24 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria11 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
Consolidate coding assistance, review and task management into one owned console. For software teams and engineering organizations building and maintaining codebases, convert repository code, task trackers, terminal sessions and model choices into source-linked code changes with named-owner approval. The benefit is a testable hypothesis, measured through accepted changes per engineering 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, task trackers, terminal sessions and model choices, then follow this sequence: 1. Execute autonomous development tasks with minimal input. 2. Analyze existing code for context-aware assistance. 3. Generate code from requirements or prompts. Resolve uncertain cases with qualified reviewers, approve source-linked code changes with named-owner approval, and measure accepted changes per engineering 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 three 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 and one task tracker; final merge and deployment checks remain engineering. 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. Engineering owners approve substantive changes and deployment scope. One repository and one task tracker; final merge and deployment checks remain engineering. 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 and one task tracker; final merge and deployment checks remain engineering. Implement one approved input format, a bounded representative case set and the first two task modules: execute autonomous development tasks with minimal input; analyze existing code for context-aware assistance. Support the third module with operator review: generate code from requirements or prompts. 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
Developer-owned repositories, authorized task trackers and permitted model providers. 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 project list for repositories and tasks, a large central diff and chat canvas, and a right-hand panel for sources, model choice and permissions. Let users compare agent runs side by side. Display draft, changes requested and approved states. Provide a review link with comments anchored to the relevant file and line. Make the task-specific outcome source-linked code changes with named-owner approval visible beside its evidence, review state and value baseline.
