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Designed and developed a multi-agent AI assistant using n8n and Google Gemini. The assistant routes user requests to specialized agents for web research, project management, email handling, calculations, and long-term memory retrieval using a vector database. It integrates Telegram, Google Sheets, Slack, Pinecone, and AI models to deliver intelligent, context-aware responses and automate daily workflows.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Handsign Arcade: play rock paper scissors on a beat.
Emoji cues fall down three lanes. You hit them by physically throwing 🪨 📄 ✂️ at the camera. The Lens reads your actual hand sign and shows you what it detected live, so a miss is never a mystery.
Keep hitting the lanes without dropping one and the COMBO kicks in!!
The idea: dance arcade, but on your phone, and your hands do the dancing. All down to testing your reflex 😆
The first idea that didn't work: I started with head nods and head shakes as
the input. Failed miserably. When your head moves to hit a cue, th cues move with it in frame, so you lose sight of the exact thing you're aiming at. Also nobody wants to look like they're head banging at their phone in public, so...
The second idea that didn't make the cut: music. It's a rhythm game with no
music, because syncing audio was harder than it was worth 🥹 So the rhythm is carried entirely by the falling cues. Visual, not audible, which means it plays fine on mute, which is how most people scroll anyway.
So much learned from this one. Built entirely in Easy Lens. Without further
ado, I present: Handsign Arcade ♥️
Best regards for this amazing challenge @Easy Lens and @Contra
Interesting and fun idea 😆
AI can help founders build products faster than ever. But building is only half the journey.
In this episode, I share a real engineering lesson about why products that look "finished" often aren't ready for production and what actually happens between a working prototype and a successful launch.
Building is no longer the bottleneck. Launching is.
#FounderEngineeringJournal #AgenticAI #AISaaS #ProductEngineering #StartupFounder #AIEngineer #MVP #Launch #ProductDevelopment #BuildInPublic
founderinsightsaisaasstartupmvpAI Engineer Full Stack DevelopmentSoftware DevelopmentGoogle GeminiLovableRork
Absolutely; AI can accelerate development, but strong launch planning, validation, and execution are what turn a prototype into a successful product.
Hype, hype and hype... It's the first page of the notebook that I write in tells me.
I was building automated workflows around Signalwatch, and it got me thinking about all the hype.
Hype around just one piece of the puzzle, LLMs. They just predict the next word while generating... No magic.The better they are trained, the better the output. Super helpful in a lot of contexts...
Tool calling. Helpful, but if LangChain and RAG + LLMs, for example, are not included where appropriate, ta ta, bye bye.
Automation. Someone bringing me a glass of water, for example, isn't something to be automated or waste resources or tokens on...
This brings me back to structural understanding, especially python + machine learning basics where you train a model based on a small piece of dataset you download from hugging face, for example... a lot becomes clear here
