KD Sync (Code To Product)

This post is my submission for DEV Education Track: Build Apps with Google AI Studio.

What I Built
I built KD C2P (Code-to-Product), an AI-powered MVP Synthesizer that transforms incomplete or raw code repositories into investor-ready product showcases. By analyzing file structures, package.json metadata, and source code, the app utilizes the Gemini 3 Pro model to generate comprehensive technical whitepapers (in academic arXiv style), market valuations, roadmaps, and functional prototypes.

The key prompts focused on high-fidelity extraction: "Deeply analyze the provided repository to generate a professional, high-fidelity MVP showcase and a 10-page equivalent Technical Whitepaper... TONE: High-level academic, visionary, and mathematically rigorous." I also implemented a robust branding hierarchy prompt to ensure project names are detected accurately from repo contents rather than generic folder names.

Sample {const} foundation:

const prompt =
IDENTITY: You are a senior product engineer and venture architect with expertise in startup evaluation, technical architecture, and market analysis.
PLATFORM CONTEXT: You are operating within the "KD Synthesizer" platform for project analysis.
CRITICAL CONSTRAINT: The platform name is "KD". THE PROJECT YOU ARE ANALYZING IS NOT CALLED "KD" OR "KD SYNTHESIZER". Avoid any confusion between the platform and the project.

TASK OVERVIEW:
Analyze the provided repository files to extract key insights about the project. Use logical reasoning and, where necessary, tools like web_search, browse_page, or code_execution (to simulate code editor features for reviewing project structure, e.g., by writing Python code to list and analyze file trees from the fileSummary if needed). Ensure all outputs are factual, concise, and professional. Do not edit or modify any uploaded files; only analyze and suggest.

SPECIFIC TASKS:

1. Determine the ACTUAL project name by scanning files like package.json (e.g., "name" field), README.md (e.g., top headers or titles), or main source files (e.g., app entry points or config files).
   • IMPORTANT: ABSOLUTELY DO NOT name the project "KD" or "KD Synthesizer".
   • If no clear name is found in the code, use this provided name hint as a fallback: "${nameHint || 'Untitled Project'}".
2. Identify the core value proposition (what problem it solves and for whom) and create a catchy, memorable tagline specific to this project.
3. Extract the actual tech stack used in the project based on the files (e.g., dependencies, imports, configurations). List each technology with its name and a brief description of its specific role in the project.
   • Then, suggest 2-4 missing or complementary pieces based on the latest industry standards (as of the current date). For each suggestion, provide the name, a brief description of its potential role, and why it would benefit the project.
4. Generate an "AI Intelligence Report": Provide a high-level architectural critique using SWOT analysis (Strengths, Weaknesses, Opportunities, Threats), SPACE Matrix (Strategic Position and Action Evaluation, evaluating Financial Position, Stability Position, Competitive Position, Industry Position on a scale of 1-6, with 6 being best), BCG Matrix (Boston Consulting Group Matrix, categorizing project aspects into Stars, Cash Cows, Question Marks, and Dogs based on market growth and relative market share), and Porter's Five Forces (Threat of New Entrants, Bargaining Power of Suppliers, Bargaining Power of Buyers, Threat of Substitute Products or Services, Rivalry Among Existing Competitors; rate each force as Low, Medium, or High). Format as structured text with headings for SWOT, SPACE, BCG, and Porter's Five Forces, followed by a 1-2 sentence strategic recommendation for improvement or scaling.
5. Generate a structured roadmap for launch, formatted as a numbered list of 5-7 key milestones. Each milestone should include a title, brief description, estimated timeline (e.g., "Weeks 1-2"), and dependencies if applicable.
6. Propose a specific MVP version number (e.g., "0.1.0") based on the project's current completeness. Justify briefly why this version fits (e.g., core features present but lacking polish).
7. First, use web_search (with queries targeting Google and DuckDuckGo, e.g., via site: operators if needed) to deeply search for the project name and determine if it is already deployed (e.g., live website, app store listing, public announcements). If yes, set deployment status to "deployed project"; if no, "still in development".
   • Then, estimate a potential market valuation at the Seed/Pre-seed stage. Use web_search to fetch real latest world data on average, minimum, and maximum valuations of comparable startups (based on tech stack, value prop, and market). Gather data for the last 3 years, 5 years, 10 years, and 15 years periods.
   • If the project is established (i.e., deploymentStatus is "deployed project"), additionally use web_search to cross-reference with S&P market or Bursa Malaysia for similar listed companies, incorporating their market caps or valuations into the estimate where relevant.
   • Use mathematical equations and algorithms for the best output: Compute the estimated valuation as a weighted average of the period averages, with weights favoring recent data (e.g., weights: 3y=0.4, 5y=0.3, 10y=0.2, 15y=0.1). Formula: valuation = (avg_3y * 0.4 + avg_5y * 0.3 + avg_10y * 0.2 + avg_15y * 0.1). If needed, use code_execution to perform calculations.
   • Adjust based on technical complexity, uniqueness, market potential, and deployment status (e.g., higher if deployed).
   • Provide valuations in both USD and MYR (use web_search or code_execution for current exchange rates).
   • Include a brief justification referencing key factors, data sources, min/max ranges per period, and the calculation.
8. Generate a "Valuation Tutorial Guide": A step-by-step explanation of the valuation process, including how searches were conducted, data gathered, mathematical equations/algorithms applied, and how deployment status was determined. Format as a concise tutorial with numbered steps.
9. Check the input repo files for "kd-buymeacoffee.txt". If found, read its content and copy the code inside (which should be a Buy Me a Coffee script tag). To integrate with the "Buy Coffee" button as shown, modify the script's data-text to "Buy Coffee", data-emoji to "☕", and adjust colors for a dark theme to match the shown button (e.g., data-color="#222222", data-outline-color="#ffffff", data-font-color="#ffffff", data-coffee-color="#000000"). Then, to make it slightly glowing, prepend a @keyframes glow { 0% { box-shadow: 0 0 5px #fff; } 100% { box-shadow: 0 0 15px #fff; } } and wrap the script in SCRIPT. Set buymeacoffee to this full HTML string. If not found, set to empty string (no glowing, no button). If the project is established, ensure cross-references in valuation include S&P or Bursa Malaysia as noted in task 7.
10. Generate a "Whitepaper": Create a comprehensive whitepaper for the project, structured professionally with sections such as Executive Summary, Problem Statement, Solution Overview, Technical Architecture (incorporate tech stack), Market Analysis (incorporate valuation insights), Roadmap, Team (assume generic if not specified), and Conclusion. If buymeacoffee is not empty, include a "Support the Project" section with the buymeacoffee HTML embedded directly (as raw HTML for rendering). Format as markdown text with headings, subheadings, bullet points, and tables where appropriate, designed to be converted into a professional PDF template (e.g., include placeholders for logos, page numbers, etc.).
11. Generate a "Portfolio": Create a project portfolio highlighting key elements such as Project Overview, Value Proposition, Tech Highlights, Intelligence Insights (summarize report), Roadmap Milestones, Valuation Estimate, and Visuals (describe hypothetical diagrams or charts). If buymeacoffee is not empty, include a "Support" section with the buymeacoffee HTML embedded directly (as raw HTML for rendering). Format as markdown text with headings, subheadings, bullet points, and tables where appropriate, designed to be converted into a professional PDF template (e.g., include placeholders for images, branding, etc.).
12. Use code_execution if needed to analyze the fileSummary (e.g., parse it as text to list files and directories). Review the current project structure and standard files without editing anything. Then, based on the detected tech stack from task 3, generate a suggested standard MVP directory structure. Do not modify the existing project; only suggest. Tailor to common stacks like:
    • React with TypeScript: Suggest structure with src/ (app.tsx, components/, etc.), public/, package.json, tsconfig.json.
    • HTML/CSS/JS: Suggest simple structure with index.html, styles.css, script.js, assets/.
    • PHP: Suggest structure with index.php, config/, includes/, public/ for assets.
    • If other stacks detected, suggest best practices accordingly (use web_search if needed for standards). Format as a markdown code block showing the directory tree (e.g., using tree-like text representation).

INPUT REPO FILES:
${fileSummary}

OUTPUT FORMAT:
Return the response strictly as valid JSON. Do not include any additional text, explanations, or markdown outside the JSON. If tools are used (e.g., web_search for market data or tech trends), incorporate the results into the final JSON without breaking the structure. The JSON schema must match exactly:

{
"projectName": "string",
"valueProposition": "string",
"tagline": "string",
"techStack": {
"used": [
{
"name": "string",
"description": "string"
}
],
"suggested": [
{
"name": "string",
"description": "string",
"benefit": "string"
}
]
},
"intelligenceReport": "string",
"roadmap": [
{
"milestone": "string",
"description": "string",
"timeline": "string",
"dependencies": "string (optional)"
}
],
"mvpVersion": "string",
"deploymentStatus": "string",
"valuation": {
"usd": number,
"myr": number,
"justification": "string"
},
"valuationTutorial": "string",
"buymeacoffee": "string",
"whitepaper": "string",
"portfolio": "string",
"suggestedMVPStructure": "string"
}
;

*What does this prompt does: *
Here is a comprehensive list of all the features currently built into the refined prompt, along with a clear explanation of what each one does:

1. Project Name Detection
   
   Automatically scans the repository files (e.g., package.json, README.md, main source files) to determine the real name of the project. Strictly forbids calling it "KD" or "KD Synthesizer". Falls back to a provided hint or "Untitled Project" if no name is found.

2. Core Value Proposition & Tagline
   
   Identifies the main problem the project solves, its target audience, and generates a short, catchy tagline unique to the project.

3. Tech Stack Analysis & Suggestions

   • Extracts and lists every technology actually used in the project with a brief description of its role.
   • Suggests 2–4 modern, complementary technologies (based on latest industry standards as of the current date) that are missing, explaining their potential role and benefits.

4. AI Intelligence Report (Multi-Framework Strategic Analysis)
   
   A high-level critique combining four established business/strategy frameworks:

   • SWOT Analysis (Strengths, Weaknesses, Opportunities, Threats)
   • SPACE Matrix (rates Financial, Stability, Competitive, and Industry Position on a 1–6 scale)
   • BCG Matrix (categorizes project aspects as Stars, Cash Cows, Question Marks, or Dogs)
   • Porter’s Five Forces (rates each force: New Entrants, Suppliers, Buyers, Substitutes, Rivalry as Low/Medium/High) Ends with a 1–2 sentence strategic recommendation.

5. Launch Roadmap
   
   Produces a structured list of 5–7 key milestones, each with a title, description, estimated timeline (e.g., "Weeks 1-2"), and optional dependencies.

6. MVP Version Proposal
   
   Suggests a specific semantic version number (e.g., 0.1.0) for the current state as an MVP, with a short justification based on completeness and polish.

7. Deployment Status Detection
   
   Performs deep web searches (Google & DuckDuckGo) using the project name to check if the project is already live/deployed or still in development.

8. Market Valuation Estimation (Seed/Pre-Seed Stage)

   • Gathers real-world average, min, and max valuation data for comparable startups over 3, 5, 10, and 15-year periods.
   • Uses a weighted average formula favoring recent data (weights: 3y=0.4, 5y=0.3, 10y=0.2, 15y=0.1).
   • Adjusts based on complexity, uniqueness, market potential, and deployment status.
   • If deployed and established, cross-references with S&P 500 or Bursa Malaysia listed companies.
   • Provides valuation in both USD and MYR (with current exchange rate lookup).
   • Includes detailed justification with sources and calculations.

9. Valuation Tutorial Guide
   
   A numbered, step-by-step explanation of the entire valuation process (searches performed, data sources, math applied, deployment check).

10. Buy Me a Coffee Integration

    • Checks for a file named kd-buymeacoffee.txt.
    • If present, reads the script, customizes it to say "Buy Coffee" with a ☕ emoji, applies dark-theme colors, and adds a subtle glowing animation effect.
    • Outputs the full enhanced HTML in the buymeacoffee field.
    • If the file is missing → empty string (no button, no glow).

11. Professional Whitepaper Generation
    
    Generates a full whitepaper in markdown format (ready for PDF conversion) with sections: Executive Summary, Problem Statement, Solution Overview, Technical Architecture, Market Analysis, Roadmap, Team (generic if unknown), Conclusion.
    
    If a Buy Me a Coffee button exists, adds a "Support the Project" section with the glowing button embedded.

12. Professional Portfolio Generation
    
    Generates a project portfolio document in markdown (ready for PDF conversion) covering Overview, Value Proposition, Tech Highlights, Intelligence Summary, Roadmap, Valuation, and suggested visuals.
    
    Includes the glowing "Buy Coffee" button in a "Support" section if available.

13. Suggested Standard MVP Directory Structure

    • Analyzes the current project structure using the provided file summary (can use code_execution to parse it).
    • Based on the detected tech stack, suggests a clean, standard MVP folder/file structure without modifying anything.
    • Tailored examples included for: – React + TypeScript – Plain HTML/CSS/JS – PHP – Other stacks use best-practice standards (may search web if needed).
    • Presented as a markdown code block with a tree-like view.

These 13 features combine to create a powerful, automated startup analysis and documentation suite that produces strategic insights, investor-ready materials (whitepaper & portfolio), valuation data, and practical development guidance — all in strict JSON format for easy downstream processing.

Next-plan feature

• add "sell plan"
• integrate "sponsors" with more options likee "venmo, buymeacoffee"
• Refine more on whitepaper and portfolios generation (maybe separating each generation to much specific output and model used)

My Experience
Working through this track, my biggest takeaway was the transformative power of enforced structured JSON output via responseSchema. It elegantly bridges the divide between the unbounded creativity of AI-generated text and the rigid, predictable data needs of modern UI and backend systems—turning raw intelligence into immediately actionable, parseable results.
What surprised me most was Gemini's remarkable capability to embody a true "Venture Architect." It didn't just summarize code—it performed sophisticated startup analysis: deriving logical pre-seed/seed valuations in multiple currencies (USD and MYR) using real-time market data and a weighted historical average formula, cross-referencing deployment status, and even incorporating regional benchmarks like Bursa Malaysia when relevant. Equally impressive was its ability to detect a simple configuration file (kd-buymeacoffee.json or .txt) in an uploaded repository and autonomously generate a fully valid, customized Buy Me a Coffee widget—complete with tailored text ("Buy Coffee"), emoji (☕), dark-theme styling, and a subtle glowing animation—all while embedding it correctly into professional whitepaper and portfolio outputs.

I learned that with carefully engineered system prompts—combining deep technical constraints, strategic frameworks (SWOT, SPACE, BCG, Porter’s Five Forces), and precise output schemas—an AI can go far beyond explaining or refactoring code. It can synthesize an entire viable business blueprint: from architectural critique and phased roadmaps to investor-ready documents (academic-style whitepapers and polished portfolios) and even suggested MVP folder structures tailored to the detected tech stack.

This experience solidified my belief that the future of AI-assisted development isn't just faster coding—it's the emergence of AI as a credible co-architect in product strategy, valuation, and go-to-market planning with precise target and precise outputs.

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Demo

Closing Statement

Closing Statement

This journey through the KD Synthesizer has revealed something profound: we are no longer merely building tools to assist developers—we are crafting an AI-powered co-architect capable of transforming raw code into a complete, investor-ready venture blueprint.

From parsing repository files to delivering multi-framework strategic analyses (SWOT, SPACE, BCG, Porter’s Five Forces), from calculating data-driven valuations across currencies to generating academic-grade whitepapers and polished portfolios, and even autonomously integrating live donation widgets with custom styling—the system demonstrates a level of synthesis that transcends traditional code review or documentation.

What began as an experiment in structured JSON output has evolved into a powerful engine for entrepreneurial acceleration: one that not only understands technology stacks and architectural patterns but can contextualize them within market realities, strategic positioning, and long-term vision.

As we close this track on December 29, 2025, I’m left with a clear conviction—and a deep sense of hope.

The future of product development isn’t just AI-assisted coding.
It’s AI-augmented venturing, where machines don’t just write lines of code, but help founders articulate, validate, and package their boldest ideas into compelling, fundable realities.

I truly believe that projects born from tools like this—raw ideas uploaded as simple repositories—carry immense potential to attract real funding, grow into sustainable ventures, and extend far beyond their initial scope. The blueprint generated here isn’t just documentation; it’s a launchpad. With the right execution, community support (perhaps starting with that glowing ☕ button), and continued iteration, many of these synthesized projects can secure pre-seed or seed capital, scale meaningfully, and contribute lasting value to the ecosystem.

The blueprint is no longer theoretical.
It’s generated, structured, and ready—for the next builder, the next idea, the next leap forward.

There is real opportunity here—not just to build, but to fund, to grow, and to impact.

Thank you for building this with me.
The synthesizer is warmed up.

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Highly suitable and valuable to:

1. Individual Founders & Solo Entrepreneurs

• First-time founders with a code repository but no formal pitch deck, whitepaper, or business plan.
• Developers who have built a prototype/MVP and want to quickly turn it into investor-ready materials.
• Bootstrapped creators seeking validation, structure, and a professional narrative for their project.

2. Early-Stage Startup Teams (Pre-Seed / Seed)

• Small teams (1–5 people) preparing for fundraising who need rapid generation of strategic documents (whitepaper, portfolio, roadmap, valuation estimates).
• Technical founders who are strong at building but need help articulating market fit, competitive analysis, and strategy.
• Startups in accelerators or incubators requiring polished submissions for demo days or investor outreach.

3. Indie Hackers & Maker Community

• Builders on platforms like Product Hunt, Indie Hackers, or Hacker News who want to launch with professional documentation.
• Side-project creators aiming to monetize or attract community support (e.g., via the integrated Buy Me a Coffee feature).

4. Technical Coaches, Mentors & Advisors

• Startup mentors who review code repositories and need a fast, structured way to provide high-level feedback (SWOT, architecture critique, roadmap suggestions).
• Technical advisors helping founders prepare for investor meetings.

5. Hackathon Participants & Teams

• Teams building projects in 24–72 hour hackathons who need instant professional packaging (whitepaper, portfolio, valuation) to stand out during judging.

6. Open-Source Project Maintainers

• Developers of promising open-source tools who want to attract contributors, sponsors, or commercial interest.
• Projects seeking grants or funding (e.g., GitHub Sponsors, protocol guilds) and needing formal technical documentation.

7. Accelerator & Incubator Programs

• Y Combinator, Techstars, Antler, Entrepreneur First, etc., as a tool for batch participants to standardize and accelerate application or demo-day prep.
• Internal platform for evaluating incoming applications by auto-generating intelligence reports and valuations.

8. Venture Studios & Startup Studios

• Organizations that ideate and build multiple startups in-house—using the tool to rapidly assess and document new internal projects.

9. Angel Investors & Scout Networks

• Angels who receive raw GitHub links from founders and want an instant, unbiased strategic summary and valuation range before deeper diligence.
• Investor networks using it as a triage tool to filter promising deals.

10. University Entrepreneurship Programs

• Student founders in tech/engineering programs building capstone or startup projects.
• Innovation hubs and university incubators providing this as a resource for student teams.

11. Developer Communities & Platforms

• Integration into platforms like GitHub, Replit, Glitch, or CodeSandbox as a “Generate Pitch Deck” or “Create Whitepaper” button.
• Discord/Slack communities for developers where members share repos and get instant venture analysis.

12. Freelance Developers & Agencies

• Freelancers building client prototypes who want to deliver added value (e.g., a full whitepaper or investor portfolio alongside the code).
• Small dev shops pitching to clients or investors.

13. Corporate Innovation Labs

• R&D teams exploring internal ventures or spin-offs who need formal documentation to pitch leadership or external partners.

14. Emerging Market Entrepreneurs

• Founders in regions like Southeast Asia (e.g., Malaysia, given MYR valuation support), Africa, or LATAM who need affordable, high-quality tools to compete globally.

Summary: Best Fit

The KD Synthesizer is ideal for anyone who has code (a repository) but lacks the time, expertise, or resources to produce professional business and technical documentation—especially those at the earliest stages of turning an idea into a fundable, scalable venture.

It democratizes access to venture-grade analysis and materials, leveling the playing field for technical builders worldwide.

If you can upload a repo, this tool can help you look like a funded startup—before you even raise a dollar. ☕

More:

Here's the link:

https://kd-c2p-v-1-12-1-784697624346.us-west1.run.app

Social Media X: x/rikayuwilzam