AI app for it and development · no coding needed
Source-linked code assistant and admin console
Reduce tool switching while keeping code, context and review evidence in one owned workspace.
Made for: Software teams and developers working in existing codebases
What it does for you
The problem
Developers switch between several AI coding tools and lose project context, standards and review evidence.
What it gives you
Reviewed, source-linked code changes
What you give it
Repository filesrequirementsdesign inputsteam standards
Build your own version of Code2.AI, Code Snippets AI and more
One app with what these 4 AI tools do, yours to keep and change: Code2.AI, Code Snippets AI, Fei, EchoComet.
Everything these tools do, in one app
- AI code generation Generates code based on your project context or requirements.Found in Code2.AI, Code Snippets AI, Fei
- Codebase context awareness Uses your entire codebase to provide relevant suggestions and assistance.Found in Code2.AI, Fei, EchoComet
- Natural language queries Lets you ask questions in plain language to explain code or reasoning.Found in Code2.AI
- Multi-language support Works with multiple programming languages like Python, JavaScript, and Java.Found in Code Snippets AI
- Custom snippet libraries Allows you to save and organize your own reusable code snippets.Found in Code Snippets AI
- IDE integration Integrates with popular code editors and IDEs for a seamless workflow.Found in Code Snippets AI
- Regular snippet updates Keeps snippet collections up to date with new programming trends and standards.Found in Code Snippets AI
- Production-grade code Generates code that meets high standards and passes peer review on the first attempt.Found in Fei
- Codebase integration Works directly within your existing codebase, reusing components and hooks.Found in Fei
- Multiple input types Accepts inputs like Figma files, Jira tickets, screenshots, and plain text.Found in Fei
- Coding standards adherence Maintains your team’s coding standards and design system consistency.Found in Fei
- Requirement to code conversion Converts requirements into backend-ready code in minutes.Found in Fei
- Local code gathering Instantly gathers entire files or folders from your local codebase for AI analysis.Found in EchoComet
- API key enhancement Enhances AI prompts with additional context using your own API key.Found in EchoComet
- One-click copy to LLMs Copies code context to popular web-based LLMs like ChatGPT, Claude, Gemini, and Grok.Found in EchoComet
- Local processing privacy Keeps all code data on your machine without sending it externally.Found in EchoComet
- Token-count statistics Provides insights into lines, characters, and estimated AI token usage for better prompt management.Found in EchoComet
- Non-coding content generation Helps with tasks beyond coding, such as generating marketing content or product launch materials.Found in Code2.AI
How it works, step by step
- Generate code from project context or requirements
- Use the whole codebase for relevant suggestions
- Answer plain-language questions about code and reasoning
- Support multiple programming languages
- Save and organize reusable snippet libraries
- Integrate with common editors and IDEs
- Keep snippet collections updated with current standards
- Generate production-grade code that passes peer review
- Reuse existing components and hooks in the codebase
- Accept Figma files, Jira tickets, screenshots and plain text
- Enforce team coding standards and design system consistency
- Convert requirements into backend-ready code
- Gather entire files or folders from the local codebase
- Enhance prompts with additional context using the team's own API key
- Copy code context to web-based LLMs in one click
- Keep code data on the machine where required
- Report lines, characters and estimated token usage
- Generate non-coding content such as launch or marketing material
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before merging
- Export a versioned reviewed, source-linked code change set 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 code 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 code 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 links4 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 data195 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 switching while keeping code, context and review evidence in one owned workspace. For software teams and developers working in existing codebases, convert repository files, requirements, design inputs and team standards into reviewed, source-linked code changes. The benefit is a testable hypothesis, measured through accepted code changes per developer hour and corrections after review; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect repository files, requirements, design inputs and team standards, then follow this sequence: 1. Generate code from project context or requirements. 2. Use the whole codebase for relevant suggestions. 3. Answer plain-language questions about code and reasoning. Resolve uncertain cases with qualified reviewers, approve reviewed, source-linked code changes, and measure accepted code changes per developer hour and corrections after review 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. Final code review, security checks and merge decisions remain with the development team. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve code ownership, source attribution, license compliance and usage permissions. Development teams approve substantive changes and merge scope. One repository type and one primary language; final code review, security checks and merge decisions remain with the development team. 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 type and one primary language; final code review, security checks and merge decisions remain with the development team. Implement one approved input format, a bounded representative case set and the first two task modules: generate code from project context or requirements; use the whole codebase for relevant suggestions. Support the third module with operator review: answer plain-language questions about code and reasoning. 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, issue trackers, design files and permitted documentation sources. Code hosting, editor and IDE plugins, and CI destinations. Start with file exchange and validate destination specifications before promising direct commits. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Project and repository setup, Source-linked assistant workspace, Administrator console. Use a project list with repository status, a central editor and chat area, and a right-hand panel for sources, snippets, standards and review state. Let users compare generated code against the existing file. Display draft, changes requested and approved states. Provide an admin view of users, API keys, retention and export logs. Make the task-specific outcome reviewed, source-linked code changes visible beside its evidence, review state and value baseline.
