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Webflow now shows agent presence on the canvas.
We've been editing Webflow sites using AI agents more and more everyday. So seeing their presence on the website, what they target, which page they're on is a great quality of life update!💙
Seeing which page the agent is on is a real quality of life win. Does it show live cursors too?
I can see which elements/components are being selected in some cases, yes!
The network for creativity
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MOVVA is now featured on Contra 🤍
I’m especially happy about this because working on this template was a creative outlet for me.
I wanted to build something useful for a business: a website that covers what a studio needs when it opens, from an easy-to-use schedule to clearly structured class information, with a solid foundation for SEO.
At the same time, I wanted it to feel beautiful. To bring a sense of movement, lightness, and the joy of taking a class into the design. To capture that friendly atmosphere that makes you want to walk into a studio and give it a try.
Thank you, Contra team!
Huge congrats on getting featured! 🤍 MOVVA looks stunning - love the mindful movement vibe and that hero image. Super useful concept for studios. Well deserved feature!
$15,000 from one browser game takes 1 to 15 million plays.
I did the math because my first web game, built with Claude Code, went live on CrazyGames today.
Bolt Pit is a Three.js arena shooter. It has earned $0 so far, because CrazyGames keeps ads off during the Basic Launch test, which runs until November 5.
Only games with good numbers get a Full Launch, and that's where the ad revenue share starts.
The formula:
Revenue = sessions × ads per session × eCPM ÷ 1,000 × your share
eCPM is what advertisers pay per 1,000 ads. CrazyGames allows at most one midgame ad every 3 minutes. The share isn't public, and reports range from 40% to 60%, so I used 50%. The rest are my assumptions, based on reported ad rates:
Low: 1 ad per session, $2 eCPM = $1 per 1,000 plays. You need 15 million plays.
Mid: 2 ads, $5 eCPM = $5 per 1,000 plays. You need 3 million plays.
High: 3 ads, $10 eCPM = $15 per 1,000 plays. You need 1 million plays.
One developer reported about €1.20 per 1,000 CrazyGames plays across eight older games. That's the low case, so I plan around the middle at best.
Is 3 million plays realistic?
CrazyGames reported 320 million play sessions a month this October. Poki says it has 100 million players a month. The players exist. Retention and session length decide which line you land on.
That's the bigger reason I'm here. I have Unity games in progress that were meant for the App Store. On the App Store, I'd only find out if people come back after paying for players.
So the new plan is web first, App Store later:
Launch on CrazyGames and Poki, where test players are free.
Tune retention and session length on real data.
If a game becomes a hit on the web, take it to the app stores.
Both portals' exclusivity rules cover only the web, so the app stores stay open.
I'm also skipping CrazyGames' exclusivity bonus. It pays 50% more for two months if your game stays off other web portals, and I want to test on Poki too.
Getting a Claude Code build accepted took six fixes, including a static build, relative paths, no Google Fonts and cutting the size from 20.5 MB to 12.4 MB. One known bug is still live: on landscape phones the start button sits below the fold.
I'll post the real numbers as they come in. Play it here:
https://crazygames.com/game/bolt-pit
CrowdVision AI – Real-Time Crowd Monitoring & Intelligence System
An AI-powered computer vision platform that detects and counts people in real time, monitors crowd density and occupancy, tracks entry and exit movements, and provides actionable crowd intelligence through a live monitoring dashboard.
Overview
CrowdVision AI is an intelligent crowd monitoring and safety analytics platform designed to help organisations monitor public spaces, understand crowd behaviour, and identify potentially unsafe crowd conditions.
The system uses computer vision and machine learning inference to analyse camera feeds and video streams, detect people, estimate occupancy, classify crowd density, and monitor movement across designated zones.
The Problem:
Monitoring crowded environments manually can be difficult, time-consuming, and inefficient. Security personnel may struggle to maintain accurate occupancy counts, monitor multiple zones, and identify unusual crowd conditions quickly.
CrowdVision AI was developed to explore how computer vision and real-time analytics could improve crowd visibility and monitoring.
My Solution:
I developed a computer vision system integrating a pretrained YOLO object-detection model with OpenCV for video processing.
The platform includes:
Real-time people detection and counting.
Crowd occupancy estimation.
Crowd-density classification.
Entry and exit line counting.
Zone-based monitoring.
Incident and anomaly monitoring workflows.
Camera health and tamper monitoring.
Evidence management and reporting.
Telegram alert notifications.
Remote edge camera processing.
Live monitoring dashboard.
Technical Implementation:
Machine Learning & Computer Vision
Python
YOLO / Ultralytics
OpenCV
NumPy
Pandas
Backend:
Python
FastAPI
REST API
Frontend:
React
Vite
JavaScript
Other Technologies
Git
GitHub
Telegram Bot API
JSON/CSV data storage
My Role
Founder & Full-Stack Machine Learning Developer
For entry/exit line counting, I'd test someone pausing on the boundary and stepping back without entering. Do you require a track to move fully between two zones before recording an entry, so small position changes don't become extra visits?
