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AI-Powered Facebook Ads Performance Analyzer
Built automated AI analyst for Facebook Ads. System analyzes ad creatives, compares performance against benchmarks, and provides recommendations (Scale/Test/Stop).
Key Features:
• Automated data extraction via Facebook Graph API
• AI performance evaluation
• Funnel analysis: CTR, CPC, Conversation Rate, Cost per Lead
• Benchmark comparison with top performers
• Daily Telegram reports and Google Sheets dashboards
Results:
• Saved 20+ hours/week of manual analysis
• Improved ROAS by 3x faster creative identification
- Automated decisions for 50+ active ads
• Reduced wasted ad spend by 40%
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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AI ads don't have to suck! what do you think of these two?
The process here was:
Creative strategist = concept x brief
Visual Asset manager = produce necessary screen recordings
Video editors = create AI scenes needed x edit together with recordings
4 voted
80%
1 voted
20%
5 votes
Closed
Adding the cat was genius, makes it seem way more natural. What generators are you using? Some of the most realistic looking people I've seen. 😅
For this project, I was completely exhausted, my eyes hurting badly.
But I refused to leave it halfway.
The more I learn, the more I realize businesses don’t actually have an information problem.
They have a retrieval problem.
That’s the problem I stayed up all night thinking about in #n8n. 😪
I’m interested in building systems that actually make things run better with my automation engineering skills.
If you're interested in #AI, #automation, or just want to be part of my journey, hit the follow button and send a DM.
AI is a great copilot, but it’s a terrible captain.
With AI coding assistants, it’s easy to fall into the trap of letting the LLM drive the entire development workflow. You prompt, copy, paste, and pray.
But our value as software engineers has never been about how fast we type syntax. It’s about system design, critical thinking, and code ownership.
Our role is evolving from builders to technical pilots. If you completely delegate the workflow, you lose control of the project.
Here is a quick framework to keep ownership of your features while leveraging AI:
🛠️ The 4-Step Workflow Guide
Design First, Prompt Second: Define your architecture, data flow, and edge cases before touching an LLM. Use AI to implement, not to invent.
Deconstruct: Break features into micro-steps. Guide the AI through isolated, high-context tasks (schema ➡️ logic ➡️ error handling).
Radical Skepticism: Treat AI code like a PR from an intern who is incredibly fast but occasionally hallucinates. Test and review every single line.
Own the "Why": If a bug hits production, "the AI wrote it" is not an option. You are responsible for the code you ship.
📌 To Developers: The future belongs to those who use AI to accelerate execution, but keep their eyes on system architecture and product sense.
📌 To Tech Recruiters: Stop looking for syntax experts. Look for developers with strong debugging frameworks, system-level thinking, and true project ownership.
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