What are you building, and what does your stack look like?

We're building Copus — a curation platform where people save, organize, and share the best content they find online. Think of it as turning your bookmarks into a living knowledge network others can discover.

Stack: Next.js + TypeScript on the frontend, Node.js backend with PostgreSQL. Elasticsearch for search and discovery, Redis for caching. We also built a Chrome extension for the save-from-anywhere workflow.

For auth we went with NextAuth.js — easy to set up with multiple providers. The hardest part has honestly been building good content discovery without just becoming another algorithmic feed. We lean heavily on human curation, which is kind of our whole thesis — real people surfacing the best stuff beats algorithms.

Thanks Ryan! Love that you are taking the anti-algorithm route too. It is honestly the hardest design challenge — resisting the urge to just optimize for engagement. We have been experimenting with letting people subscribe to curators they trust instead of feeds, which has worked really well. Would definitely be down to chat — we are actually launching Copus on PH tonight so this week is a bit wild, but let me check out your calendar link after the dust settles!

@ryan_hendrickson Great questions! The primary interface is actually both — we have an iOS app, but the real magic happens through WhatsApp and Telegram. Users manage their entire day (reminders, todos, calendar, meeting notes) just by chatting in WhatsApp without ever opening another app. The voice note feature you liked is a big part of that — you can dictate a task while driving and Aria just handles it.

For billing, we're using RevenueCat + App Store subscriptions on iOS. Kept it simple for now since we're iOS-first — it handles entitlements cleanly and has great analytics built in. Happy to connect if you want to dig deeper!@ryan_hendrickson Thanks so much! The primary interface is actually the messaging platforms — WhatsApp and Telegram are the core experience. The iOS app is more of a companion dashboard. The big insight was that people already have WhatsApp open all day, so we meet them where they are instead of asking them to open another app.

For billing, we're on Stripe — works great with RevenueCat on the iOS side for in-app purchases. Happy to share more if useful!

Building Social Intel (https://socialintel.dev) — Instagram influencer search API for AI agents. The twist: payment via x402 micropayments (USDC on Base). Agents find the API, call it, and pay automatically. No subscription, no API key for the caller. Stack: FastAPI + fastapi-x402 + MCP server. Anyone else building in the x402/agent payments space?

Building Genie - an AI analyst inside Databox. Users ask questions in plain English ("Why are leads down this week?") and get instant answers, charts, and dashboards from their connected data sources.

Stack for the AI layer: LangGraph for agent orchestration (evaluated several frameworks - LangGraph gave us the control we needed for stateful, multi-step tool-calling without abstracting too much away), LangSmith for tracing, Claude + OpenAI depending on task complexity, AWS Bedrock for RAG. We also just shipped Databox MCP so users can query their live data from Claude, ChatGPT, or any MCP-compatible tool.

On auth/billing - we're an established SaaS so we have our own systems, but the most interesting challenge on the AI side has been usage metering. Every Genie response chains multiple tool calls, and the cost per conversation varies wildly depending on what the user asks. We landed on a credit system where simpler tasks cost less and complex ones cost more - transparent to the user, visible right next to each response.

The hardest part wasn't the AI. It was making sure every answer traces back to real data. Confident-sounding wrong answers are worse than no answer when someone's making a business decision.

@Ryan Hendrickson

I just built my first saas product (Streamster.shop) as a solopreneur, and here's what I'm using:

Auth: Supabase Auth

Billing: Stripe

Permissions: Started with simple boolean flags. Now moving to RBAC. My advice: plan early.

My secret sauce:

I'm actually a manager at a B&B and not a developer. My "co-founder" is AI. It wrote 90% of the code. Although it was expensive, I used OpenClaw + Codex + Opus.

The hardest part wasn't the tech — it was staying focused on what actually matters to users vs. what I thought mattered and looked cool lol

Happy to hop on a call!

Hey @ryan_hendrickson ,

I am building @ZapDigits . Helping marketing agencies with client reporting and dashboards. I've been working on it for more than 1 year now. A few months back I quit my full time job. Launched on Product hunt twice. 1st time product of the day and second time 3rd. We have 25+ native integrations and counting.

Stack is simple: Next.js, Prosgress, AWS fargate, AWS S3 and a few lambda functions.

Building Murror, an AI app for young people dealing with loneliness and isolation. The core idea is that a lot of people don't have anyone they can really talk to without judgment, and Murror tries to be that space.

Stack is React Native for mobile, Node/Express on the backend, PostgreSQL, and we're using a mix of Claude and some fine-tuned models for the emotional support layer. For auth we went with Supabase which made things a lot simpler early on.

The hardest part honestly isn't the stack, it's figuring out how to make something that feels genuinely warm and not like a chatbot. That's been most of the work.

Hey Ryan,

I am building livedemo.ai
Stack is JS with MongoDB

- React + Redux - Frontend
- Express Backend
- MongoDB database
- MongoDB as queue
- C# and Swift for Desktop Apps
- Mux for video streaming and cutting
- ElevenLabs for voiceover
- ChatGPT 5 for AI features

Working on a privacy-first web tools app — keeping it simple with no auth for most features, and using basic Stripe billing + minimal backend only where truly needed.