HACK NIGHTCompleted
Thu, Aug 27, 2026
See what happens when builders get in a room. Explore the projects, watch the demos, and meet the people behind them.
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Understand it. Use it at work. Nihongo Lens is a five-minute Japanese learning companion for foreign workers living in Japan. It turns a real workplace conversation—or something the user wants to say in English—into an understandable translation, a natural Japanese reply, audio practice, a practical shift mission, and personalized review cards.
Run a free AI search readiness audit. Check crawler access, schema, entity clarity, and citation-ready content—no signup or API keys required.
Start with a statement you encountered. Break it down into beliefs required for the statement to make sense. Choose if you agree with all of the required beliefs. Lets you see where you agree or disagree with someone.
This is a Next.js application for creating images and short videos for Instagram and TikTok directly within the browser.
best way to pay and get points recommendation
CallWall is a local policy firewall for coding agents. It sits between Claude Code / Codex and every tool call — observe or enforce — so agents can ship code without exfiltrating secrets, touching protected paths, or going off-intent. Hard rules first, semantic judgment second, human approve/deny when it matters. One dashboard. Fail closed.
TasteGraph is a personalized movie discovery system that moves beyond fixed genre tags and generic similarity scores. The system represents users, movies, genres, actors, and directors as a Neo4j knowledge graph. In parallel, an autoencoder compresses high-dimensional movie features and user preference signals into a compact 64-dimensional latent representation. Users select several favorite films, and TasteGraph builds multiple local taste neighborhoods instead of reducing their preferences to a single average point. It then recommends nearby movies and explains each recommendation through relationship paths in the graph. Our prototype demonstrates three core steps: 1. Select a favorite movie. 2. Calculate its local neighborhood. 3. Display nearby recommendations with explainable connections. The project combines graph relationships with learned representations to create recommendations that are more personal, exploratory, and understandable. The next step is to evaluate the system with a larger dataset and retrain a commercial version using only properly authorized data.
Career Canvas A canvas-first portfolio builder that turns connected career experiences into an evidence-backed portfolio. The problem Traditional resumes and portfolios force nonlinear careers into chronological lists. Projects, roles, certifications, achievements, and skills lose the relationships that explain how one experience led to another—and what evidence actually supports a claimed capability. The idea Career Canvas treats a career as a graph. People build their story spatially on an infinite canvas, using connected cards for companies, experiences, projects, certifications, skills, achievements, and goals. The same graph then becomes the source of truth for a structured portfolio. > A resume is a list, but a career is a graph. How it works 1. Create cards freely. Double-click the canvas to add any career card where it makes sense. 2. Connect experiences. Draw directed relationships between the work, learning, outcomes, and capabilities that belong together. 3. Derive new cards. Drag a connection into open space, choose a card type, and create a related card with the relationship already attached. 4. Build evidence-backed skills. Connect multiple projects, experiences, or credentials to one Skill; its supporting-source count updates from the graph. 5. Generate a structured portfolio. Switch to Portfolio to see the current graph organized into readable sections, with each Skill showing its connected supporting evidence—or clearly showing that evidence is still needed. Optional intelligence features extend the same graph without changing the core workflow: - Shisa AI skill suggestions: analyze an Experience or Project and review 3–5 suggested Skill cards before adding them to the canvas. - Neo4j graph analysis: sync the current cards and connections on demand, then identify the most connected career node and Skill hub. Both integrations run through server-side routes so credentials are never included in the browser bundle. Why this is different - Nonlinear by design: it represents relationships across a career instead of flattening them into one timeline. - Skills backed by evidence: capabilities are connected to the work that demonstrates them, not listed as unsupported keywords. - Spatial editing: people can think, arrange, and discover their story through direct manipulation of relationships. - Thinking interface to presentation interface: the canvas supports exploration; Portfolio turns that thinking into a clear narrative. - One source of truth: cards and connections in the graph drive the portfolio directly. Demo The canonical demo starts with a populated career graph: 1. Add a Project called Hackathon 2026. 2. Drag its connection handle into open space and create a Skill called Rapid Prototyping. 3. Connect the existing AI Automation project to the same Skill. 4. Confirm that Rapid Prototyping shows 2 supporting sources. 5. Open Portfolio and see both Hackathon 2026 and AI Automation listed as evidence for that Skill. The result is a visible relationship: Hackathon 2026 → Rapid Prototyping ← AI Automation. Technology - React 19 and TypeScript - Vite 8 - React Flow via @xyflow/react - Browser localStorage for versioned graph and viewport persistence - Node.js server routes for optional intelligence features - Shisa AI for career-evidence skill suggestions - Neo4j for on-demand graph synchronization and connectivity analysis - Lucide React icons and plain CSS - OpenAI Codex as a development and verification tool; the product does not use the OpenAI API Running locally Prerequisite: Node.js ^20.19.0 or >=22.12.0. Open the local URL printed by Vite. This is the canonical, browser-local Canvas and requires no backend or external credentials. The concurrently developed optional intelligence integrations are preserved as an explicit lab surface. To run them, copy .env.example to .env.local, provide the corresponding server-side credentials, then use: Open /canvas?labs=1 only when intentionally testing those integrations. To verify and run the production build: Current scope Career Canvas is a desktop-first prototype focused on graph authoring and graph-derived portfolio presentation. The working graph is saved in the current browser profile; Shisa AI suggestions and Neo4j analysis are optional, credential-dependent actions. Accounts, cross-device sync, collaboration, public sharing, export, and mobile optimization are outside this submission's scope. Future direction Future work could add role-tailored portfolio generation, richer graph recommendations, and deeper longitudinal career intelligence. These are future directions, not features claimed in this prototype.
The AI with given keywords can automatically search on instagram to find the matched KOLs information, helping KOL collaborators to work more efficiently. No need to spend time on searching for related KOLs.
Orbital: An Infinite Idea-Traversal Network Orbital is an AI-powered visual thinking environment that transforms a single idea into an explorable universe of related possibilities. Instead of presenting brainstorming as a document, list, mind map, or chatbot conversation, Orbital represents every idea as a planet within an infinite star map. Users begin by entering a concept they want to explore. That concept becomes the origin planet. Selecting it asks OpenAI to generate a new orbit of meaningful, contextually related product ideas. Each generated idea becomes another planet that can be selected, explored, and expanded indefinitely.
This application uses video recording to recognize objects and helps you find things based on previously recorded information. For example, you can use it to find forgotten items by recording yourself when leaving a hotel.
AgentPad turns any browser into a complete AI development environment. Start a private cloud workspace with VS Code, a terminal, live previews, persistent storage, and your preferred coding agent. Pay monthly or rent compute only when you need it.
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Recorded talks, technical context, and the workflow behind real product work.
RECORDED · TALK 01
SPEAKER · TALK 02Lead of Sales and BD · Shisa AI
RECORDED · TALK 03
Manager · CyberAgent, Inc.
RECORDED · TALK 05
DevRel Engineer · Qdrant
RECORDED · TALK 06
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