# juliato.dev > Developer portfolio by juliato. Self-taught developer building web apps, 3D experiences, games, and AI-powered tools. Taught himself to code at 16 using ChatGPT. ## About juliato is a self-taught developer who learned to code at 16 using ChatGPT. Focus areas: web development, 3D graphics, games, and AI. Makes things because he enjoys making — sites, games, art, half-finished weird little things. Uses AI to handle the tedious parts so he can stay in the creative work. Side projects so far include 2D and 3D rookie browser games, a web store, a rebrand site for CryptoHub Malta, plus whatever else caught his attention. ## Key Pages - [Home](https://juliato.dev/): Landing page with intro, hero, and site directory - [Projects](https://juliato.dev/projects): Full list of projects built — games, crypto platforms, business sites, AI tools - [Blog](https://juliato.dev/blog): Articles on development, innovation, and building things with code - [Contact](https://juliato.dev/contact): Contact form for project inquiries and collaboration - [About](https://juliato.dev/about): Coming soon - [GitHub](https://github.com/Jul1ato): Source code and open projects - [LinkedIn](https://www.linkedin.com/in/juliato/): Professional profile ## Projects ### VertAI URL: https://juliato.dev/projects/vertai Live site: https://www.vertaiapp.com/ Tech: Next.js, React, AI, Computer Vision, iOS, Android Overview: VertAI is an AI-powered vertical jump training app. Users record their jump with a smartphone camera, and the app's AI analyzes 8+ biomechanical markers — knee angle, trunk lean, arm swing, and more — then assigns a form grade and builds a personalized multi-week training program targeting the user's specific weaknesses. Key Features: Real-time form analysis from smartphone video, biomechanical grading (A–F) across multiple markers, personalized multi-week training programs, daily workout structure with progress tracking, and a marketing site built with Next.js paired with iOS and Android apps. ### CryptoHub Malta (Featured) URL: https://juliato.dev/projects/cryptohub Live site: https://cryptohubmalta.org Tech: Next.js, React, TypeScript, Figma Overview: A comprehensive crypto community website built for CryptoHub Malta. Designed from scratch in Figma, featuring a modern dark theme with clean UI elements. Built with Next.js and React for optimal performance and SEO. The site includes community information, event listings, and resources for crypto enthusiasts in Malta. Key Features: Custom Figma design with modern dark theme, server-side rendering with Next.js for SEO, responsive layout for all devices, community resources and event listings, and TypeScript for type-safe development. ### Sip & Grow Website URL: https://juliato.dev/projects/sipandgrow Live site: https://www.sipandgrow.org Tech: Next.js, React, TypeScript Overview: juliato's very first website project — a playground where he learned and experimented with modern web development. Built with Next.js and React, this site became the foundation for exploring web development fundamentals, responsive design, and component-based architecture. It's where the coding journey began. Key Features: Component-based architecture with React, server-side rendering via Next.js, responsive design for all screen sizes, integrated interactive 2D and 3D browser games, and TypeScript for maintainable code. ### 2D Browser Game URL: https://juliato.dev/projects/2dgame Live site: https://www.sipandgrow.org/game Tech: JavaScript, HTML Canvas API, Next.js Overview: A 2D browser game built entirely with JavaScript and HTML Canvas API. A deep dive into game development fundamentals — handling game loops, sprite animations, collision detection, and user input. Integrated into the Sip & Grow website as an interactive feature. Technical Details: Custom game loop with requestAnimationFrame, sprite-based character animations, pixel-perfect collision detection, keyboard and touch input handling, and seamless integration with the Next.js parent site. ### 3D Browser Game URL: https://juliato.dev/projects/3dgame Live site: https://www.sipandgrow.org/game3d Tech: Three.js, WebGL, JavaScript, Next.js Overview: An immersive 3D browser game built with Three.js and WebGL. Explores 3D graphics programming including scene management, lighting, textures, and real-time rendering. A significant step up from 2D, showcasing the power of modern browser capabilities for interactive 3D experiences. Technical Details: 3D scene management with Three.js, real-time WebGL rendering, dynamic lighting and texture mapping, camera controls and user interaction, and integration within the Next.js Sip & Grow website. ## Blog Posts ### AI SEO in 2026: A Technical Guide to GEO and llms.txt URL: https://juliato.dev/blog/ai-seo-2026-guide Published: April 5, 2026 Reading time: 6 min Keywords: GEO, AEO, RAG, AI SEO, llms.txt, generative engine optimization, schema.org, entity SEO Search used to mean a results page. Now the searcher might be a language model that never shows you a link. Here's what's actually different about optimizing for that, and what works right now. **The core shift** Traditional SEO optimizes a page to rank on a results page that a human clicks. AI SEO optimizes a page to be retrieved, quoted, and synthesized by a language model that may never send a click at all. Different audience, different objective. The old question: does my page rank for this keyword? The new question: when an AI answers this query, does my content make it into the answer? **Quick definitions** - GEO (Generative Engine Optimization): optimizing content to be retrieved, cited, and used by generative AI systems instead of ranked on a results page. - AEO (Answer Engine Optimization): precursor to GEO focused on being the answer to a direct question. - RAG (Retrieval-Augmented Generation): the technique where an LLM fetches documents before answering. GEO is about being the document it fetches. - Semantic chunking: breaking content into self-contained passages that retain meaning in isolation. RAG systems retrieve chunks, not whole pages. - Embedding: the vector representation of a chunk, used to match it to a query. - Entity: a discrete thing (person, product, concept) with a stable identity. Entity SEO is about being the authoritative entity for a concept. - Grounding: giving an LLM verified source material to reduce hallucination. - Citation surface: the set of places where an LLM might reference your content. ChatGPT, Claude, Perplexity, Google AI Overviews, Bing Copilot. - llms.txt: an emerging open spec for a markdown file at a site's root that summarizes content in a format LLMs can parse efficiently. **llms.txt and llms-full.txt** The llms.txt spec, proposed in 2024, is the simplest idea in AI SEO. A markdown file at the root of your site that lists your content in a format LLMs can parse without scraping HTML. Two files, two jobs: - llms.txt is the index. Short descriptions, links to important pages. A site map for machines that read. - llms-full.txt is the content dump. Full text of your important pages, stripped of HTML, ready to be chunked and embedded. Declare them in robots.txt with LLMs-txt and LLMs-full-txt directives, and link to them from your HTML head with a rel="llms-txt" link tag. Not every AI system reads these files yet, but the cost to add them is close to zero. **Schema.org as grounding data** Structured data (JSON-LD, schema.org) was built for Google rich results. It turns out to be near-perfect food for LLMs too. When you tag a page as BlogPosting with author, datePublished, wordCount, and articleSection, you're handing an LLM a pre-parsed fact sheet about the content. The schemas that matter most for AI right now: Article / BlogPosting for dates, author, word count, keywords. Person with sameAs linking to GitHub, LinkedIn, Wikipedia. Organization for entity grounding of companies. BreadcrumbList to tell the model where a page sits in a site hierarchy. FAQPage since LLMs love Q&A shaped content, it maps directly to how they output answers. HowTo for procedures. sameAs is the most underrated field. It connects your content to entity graphs like Wikidata, Wikipedia, and Crunchbase. If an LLM is trying to decide whether two "John Smiths" are the same person, sameAs is the link that proves it. **Entity-first, not keyword-first** Keyword SEO was about ranking for strings. Entity SEO is about being the authoritative node for a concept. Language models don't match keywords, they match meaning against an internal knowledge graph. You win when your site is the cleanest source on an entity. Practically: claim an entity and be consistent about it everywhere. Use the same canonical names across all pages. Link to external entities you reference. Keep a single authoritative page per entity, not three half-pages. **AI crawler directives** Different AI systems send different crawlers: GPTBot (OpenAI), ClaudeBot (Anthropic), PerplexityBot (Perplexity), Google-Extended (Google's generative models), CCBot (Common Crawl). Default position: allow them all. Blocking AI crawlers means opting out of being cited. **Semantic chunking for RAG** When a RAG system retrieves your content, it doesn't grab the whole page. It grabs a chunk, usually a few paragraphs. If the chunk doesn't make sense without the rest of the page, it gets discarded. Write chunks that stand alone: each H2 section should be understandable without the H1 context. Open sections with a one-sentence summary that restates the topic. Define acronyms the first time they appear in each section. Avoid "as mentioned above" or "we saw earlier." Every heading section is a standalone document in miniature. **Citation surface** Being cited by an LLM matters more than ranking on page one, because AI answers often don't show ten blue links. There's one answer, maybe three sources linked underneath. Surfaces to optimize for: ChatGPT with web search, Claude with web search and citations, Perplexity (citation-first by design), Google AI Overviews, Bing Copilot. What gets cited: recent, specific, well-structured content with clear authorship and timestamps. Generic content that reads like it was written by committee gets skipped. **What's bleeding edge right now** A few things moving fast as of 2026: - LLM-specific content formats: structured YAML frontmatter on pages, MCP (Model Context Protocol) endpoints exposing site data directly to agents. - Direct-to-LLM APIs: some sites publishing JSON feeds optimized for model consumption over HTML. - Verifiable content: cryptographic signatures on content to prove authorship and recency. - Conversational schema: Q&A pairs shaped for how people ask LLMs questions, not how they type search queries. - llms.txt proliferation: going from niche spec to default practice. **What to actually do** 1. Add llms.txt and llms-full.txt. 2. Declare them in robots.txt and in a rel="llms-txt" link tag. 3. Add JSON-LD schema to every page (Article, Person, Organization, BreadcrumbList). 4. Use sameAs on your Person schema. 5. Write content in self-contained chunks with clear H2 structure. 6. Keep publish and modified timestamps visible and accurate. 7. Don't block AI crawlers unless you have a specific reason. Traditional SEO isn't going away. But the next ten years of search optimization are about being the source an AI reaches for, not the link a human clicks. ### Why Innovating is Great URL: https://juliato.dev/blog/why-innovating-is-great Published: February 22, 2026 Reading time: 5 min Keywords: innovation, development, creativity, technology, building Innovation isn't reserved for billion-dollar labs or Silicon Valley garages. It's a mindset anyone can adopt — and as a developer, it's the most powerful tool in your toolkit. **Innovation Starts Small** When most people hear "innovation," they think of groundbreaking inventions — the iPhone, self-driving cars, artificial intelligence. But real innovation often starts much smaller. It's the moment you look at a problem and think, "there has to be a better way to do this." I've experienced this firsthand. When I was building my first website, I wasn't trying to reinvent the web. I was just trying to make something that worked. But that simple act of creating something from scratch — turning an idea into a working product — that's innovation at its core. **Building Beats Planning** One of the biggest traps I see is over-planning. People spend months perfecting an idea in their head, waiting for it to be "ready." But innovation doesn't come from thinking about building. It comes from actually building. "The best way to predict the future is to create it." When I built a 3D browser game with Three.js, I didn't have a master plan. I started with a blank canvas, experimented with WebGL rendering, and figured things out as I went. The result wasn't perfect, but it existed — and that mattered more than any plan ever could. **Why It Matters for Developers** As developers, we're in a unique position. We have the ability to take an idea and make it real — sometimes in a matter of hours. That's a superpower most people don't have. And with AI tools accelerating our workflows, the gap between idea and execution has never been smaller. Here's what innovating as a developer has taught me: - You learn faster by doing. Reading documentation is useful, but nothing beats the lessons you learn when your code breaks at 2 AM and you have to figure out why. - Failure is part of the process. Every bug you fix, every feature you scrap, every project you abandon — they all compound into experience that makes your next project better. - Small innovations compound. A cleaner way to structure your CSS, a smarter approach to state management, a more efficient workflow — these small improvements stack up over time. **The AI Angle** We're living through one of the biggest innovation waves in history. AI is changing how we write code, how we design, how we think about problems. Some people see this as threatening. I see it as the greatest opportunity of our generation. Using AI in my workflow hasn't made me less of a developer — it's made me a faster one. It handles the repetitive tasks so I can focus on what actually matters: the creative decisions, the architecture, the user experience. That's where real innovation lives. **Just Start** If you're reading this and you have an idea — a project, an app, a game, anything — just start building it. Don't wait until you know everything. Don't wait until the conditions are perfect. The best time to innovate was yesterday. The second best time is now. Innovation isn't about being the smartest person in the room. It's about being the one who actually ships something. Build it, break it, learn from it, and build something better. That's the cycle. And it's a great one to be part of. ## Skills **Frontend**: HTML, CSS, JavaScript, TypeScript, React, Next.js, Three.js **Backend**: Node.js, Python **3D & Graphics**: Three.js, WebGL, HTML Canvas API **AI & Automation**: Machine Learning, AI Agents, Automation Tools, AI-assisted coding workflows **Design**: Figma, modern dark UI, component-based design systems ## Contact Open to project collaboration, freelance work, and interesting conversations. - Website: https://juliato.dev - Contact form: https://juliato.dev/contact - GitHub: https://github.com/Jul1ato - LinkedIn: https://www.linkedin.com/in/juliato/ ## AI Discovery Files - Sitemap: https://juliato.dev/sitemap.xml - Robots: https://juliato.dev/robots.txt - LLMs index: https://juliato.dev/llms.txt - LLMs full (this file): https://juliato.dev/llms-full.txt