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B2B wholesalers and manufacturers waste thousands of hours manually transcribing PDF purchase orders into their ERP systems. It's slow, expensive, and highly prone to human error. I built this Autonomous PDF Order Agent to completely eliminate...
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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Uhh. Can you help me pick, A or B? 🙏
I'm drafting client's landing page using 2 of the most advanced AI models: Anthropic (Fable) and OpenAI (Sol).
Both delivered a banger result from a single prompt (I'll put it in the comments).
Can you tell which model delivered which output? 😏
31 voted
56%
24 voted
44%
55 votes
Closed
I think both are AI generated UI
correct if I'm worng.
Your app works locally… but crashes after deployment? 😩
One of the most common mistakes I see is forgetting that local and production environments are different.
Before deploying, always check:
✅ Environment variables are correctly configured
✅ Production database credentials are set
✅ API URLs point to the right environment
✅ CORS settings allow your frontend
✅ Build errors are resolved
✅ Authentication works in production
My rule: Never assume that because it works on localhost, it's ready for production.
What’s the most frustrating deployment error you've faced? 👇
devtipsDesktop Apps DevelopmentWeb DesignWeb DevelopmentCursorNode.jsPythonnextjsfullstackwebdevelopment
Talon Audit — a privacy-first website exposure and remediation platform
I built Talon Audit to solve a problem most website tools handle badly: they detect issues, but rarely help teams understand what matters, what to fix first, or whether the fix actually worked.
Talon analyses public-facing websites across four connected domains:
Exposure — browser protections, cookies, scripts, TLS, and visible configuration risks
Integrity — broken resources, routes, errors, forms, and reliability regressions
Experience — accessibility, mobile usability, speed, and interaction friction
Conversion — messaging, trust signals, pricing paths, forms, and calls to action
The product follows a complete improvement workflow:
Detect → Explain → Fix → Verify → Monitor
Every finding is structured around evidence, severity, confidence, impact, remediation guidance, and a verification method.
I led the project from strategy to launch, including:
product positioning and methodology
UX/UI and design system
full-stack implementation
AI-assisted analysis and remediation workflows
privacy and security boundaries
pricing, demo experience, and launch
Talon performs passive, low-impact analysis only. It does not exploit systems or claim to replace authorised penetration testing.
Built through a terminal-first AI-native workflow using Codex 5.5 and Claude Fable.
Live product: talonaudit.com
Role: Product Strategy, Product Design, Full-Stack Development, AI Development
Structuring findings around evidence, severity, and verification methods makes remediation so much clearer. How are you handling false positives during passive analysis?