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PQI — Solo Python tool that analyzes Polymarket prediction markets with a 7-agent LLM council and prints ranked, reasoned recommendations (research project, not deployed). Python; Anthropic Claude API, asyncio, Pydantic, DuckDB analytics.
The network for creativity
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Connect with clients, get discovered, and run your business 100% commission-free
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Most travel apps feel like impersonal search directories that you can clearly tell were made for your typical traveler - you know, the one that's going on vacation and leaving all worries behind?
But that's not us. We are freelancers, which means we get the freedom to travel, but also means client work also gets the freedom to travel alongside us. What a lucky bastard!!
Well, this app reimagines the digital nomad journey in the city I know best, Lisbon, through the lens of a local friend. It blends a work mode with vetted co-working spaces with a gamified travel scrapbook, ensuring you experience the authentic culture of the city while building a physical visual log of your stay - no matter the budget you're on!
🛠️ The Tech & Design Workflow
To get to this final working prototype, I utilized a connected pipeline across Figma’s advanced tool ecosystem:
⭐️ Figma Design: used as the initial creative sandbox to establish the visual identity, typography, and layout foundations.
⭐️ Figma Make: transformed my static design inspiration into a living, interactive, code-backed prototype with several back-and-forth iterations.
⭐️ Figma Weave: used to create a custom filter to add to user's photos, using its node asset pipeline.
📊 Architecture & Scalability
Instead of hardcoding a long database, all the co-working spaces and travel quests are stored in an external Google Sheet exported as a live, public CSV. This allows for instant, real-time data updates without redeploying code, making the app entirely scalable at any time.
Also, every recommendation and description for the co-working spaces was written by me from personal, first-hand visits. The travel quests are a blend of personal recommendations and some of my bucket-list items - maybe you'll cross them off sooner than me!
💰 Monetization & The Organic Growth Loop
To keep the platform 100% free for users, the plan is to develop affiliate agreements with co-working spaces and paid local experience hosts, earning small commissions per booking.
On the other hand, completing quests rewards users with points. And while currently displayed as a "coming soon" placeholder, the road map plans to allow users to redeem these points for real-life gift cards to drive long-term user retention.
Lastly, there's some built-in word of mouth, since the scrapbook features a prominent share button on your custom-filtered photos. This turns users into organic brand ambassadors when they share their custom-doodled memories with family back home or on social media.
Figma Design project: https://www.figma.com/community/file/1649623170040464186
Figma Make project: https://www.figma.com/community/file/1649623797184817979
Working app: https://tempo-slush-47265679.figma.site/
Great job Silvia 😍 🔥 🙌
Hi everyone 😊
Really excited to share FigmaCrews — a multi-agent AI studio I built for the #ConfigMakeathon (@figma x @contra 💙)
FigmaCrews is basically my proposal to Figma — what if Figma had a built-in AI team?
Right now, designers leave Figma constantly. Research, strategy, content, planning — all happening in different tools, then coming back to design. That's a broken workflow.
So I built a working prototype to show what it could look like.
You get 6 AI agents inside Figma: Manager, Researcher, Digital Marketer, Designer, Figma Designer, and a QnA agent. Give one command to the Manager, and watch the team get to work — in real time, without leaving Figma.
The idea is simple: Figma is already where design lives. In the AI era, it could be where the entire creative workflow lives.
I built this using:
Figma Make — the full experience runs here
Figma MCP — connecting the agents and making it real
This is my proposal. And I think Figma should build it 🙂
Would love to hear — which agent would help your workflow the most?
This is really cool! Great work!
I Take AI Slop and Turn It Into Product
At SanganakHQ, I've done this at least half a dozen times now. Same story every time.
Founder builds with Claude, Codex, Bolt, Replit, Lovable, v0. And it works. Real users, real payments, real data.
But under the hood? 50K, 100K+ lines of AI-generated code glued together. Functions duplicated dozens of times. Auth mixed into UI. Hardcoded secrets. No tests. Fix one bug, three more appear.
It works the way a house of cards works.
Then they message me: "We're scaling. Can you make this production-ready?"
So I audit every line. Separate what's solid (usually 20%) from what needs to be rearchitected. Build a day-by-day migration plan with exact pricing. Move it to a real stack: Next.js, Supabase, Vercel, proper auth, proper RLS, proper CI/CD.
The irony: the AI features are usually the cleanest part. The mess is everything around it. Business logic, payment flows, membership tiers. The stuff AI generated fast but never thought through.
Smart founders, solid ideas, AI got them to a working product. But "working" and "production-grade" are two very different things.
If your app runs on AI-generated code and you're about to scale, get it audited before you find out the hard way.
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