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Telegram Chat Summary & Email Automation
Automated system that analyzes Telegram group chats, generates AI-powered summaries, and sends them via email to stakeholders. It helps teams stay informed without reading hundreds of messages.
Key Features:
• Automatic extraction of Telegram chat messages
• AI-powered summarization using ChatGPT API
• Smart filtering of important discussions and decisions
• Customizable summary formats and recipients
Results:
• Reduced time spent reading chats by 80%
• Key decisions never missed
• Processed 1000+ messages daily into concise summaries
• Automated delivery saves 10+ hours/week
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
Related posts
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.
😊 AI-Powered Appointment Booking Automation with n8n
This project is an AI-powered appointment booking automation system built with n8n. The workflow is designed to let a user interact with a conversational AI assistant, request an appointment, provide personal details, and move through the booking process automatically.
The system uses an AI agent connected with a knowledge base, memory, vector storage, and external tools. It can understand user messages, ask follow-up questions, collect booking information such as name and email, check calendar availability, create a calendar event, and send confirmation messages through Gmail. The workflow also includes document ingestion, text extraction, embeddings, and Supabase Vector Store integration so the assistant can answer based on stored business information.
My work focused on building the full automation flow inside n8n, connecting AI models, configuring memory and knowledge base retrieval, integrating Google Calendar and Gmail actions, and testing the conversational booking process from start to finish. The result is a practical AI assistant system that can reduce manual appointment scheduling work and provide a smoother customer booking experience.
Skills & Tools:
n8n, AI Automation, Workflow Automation, AI Agent, Google Calendar API, Gmail Automation, Supabase Vector Store, HuggingFace Embeddings, Google Gemini, Groq, RAG Workflow, Knowledge Base Integration, Chatbot Automation, Appointment Booking System, CRM/Business Process Automation.
Appointment booking bot that does the task, nothing makes work easier than this
End-to-End Website Data Extraction Automation with n8n
This project is an automated website data extraction workflow built with n8n. The system is designed to fetch a website homepage, extract internal page URLs, loop through selected pages, collect page content, clean and structure the extracted data, and generate a final organized output automatically.
The workflow includes multiple automation steps such as homepage fetching, URL extraction, page-by-page looping, delay handling, individual page requests, content cleaning, data aggregation, JavaScript-based processing, and document updating. This makes the system useful for website audits, content collection, lead research, SEO analysis, documentation generation, and business data extraction tasks.
My work focused on building the full n8n workflow structure, connecting each automation node, adding controlled delays between page requests, processing extracted content with JavaScript, merging results into a clean format, and sending the final output into a document. The result is a practical end-to-end automation system that reduces manual website research and turns web content into organized, reusable data.
Skills & Tools:
n8n, Workflow Automation, Web Scraping, Website Data Extraction, JavaScript, API Requests, HTTP Request Automation, Data Cleaning, Data Aggregation, Document Automation, No-Code Automation, Low-Code Development, Business Process Automation, SEO Data Collection, Content Extraction.
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