Build AI agents and superviser to automate your workflow

About this Gig

Are you tired of manually moving data between apps or managing complex workflows that require constant human oversight? In 2026, the most efficient businesses don't just use AI, they deploy AI Agents. I specialize in building Multi-Agent Systems where specialized AI agents (Researchers, Writers, Coders, Data Analysts) work together under a Supervisor Agent that ensures quality, logic, and 100% accuracy. What I Can Automate for You: - Sales & Lead Gen: Agents that find leads, research their company, and write personalized outreach. - Content Factories: A supervisor agent that manages specialized agents for SEO research, drafting, and social media posting. - Customer Support: Intelligent agents that don't just "chat," but actually take actions in your CRM or database. - E-commerce Ops: Automate inventory tracking, competitor price monitoring, and order processing. My Tech Stack: Frameworks: React, Node, Python, LangGraph, Langchain, Cursor. LLMs: GPT-5, Claude 3.5 Sonnet, Llama 3.

Requirements

1. The Workflow Blueprint Step-by-Step Process: A detailed list of the manual tasks you want to automate. (e.g., "First, we scrape a website; second, we summarize the text; third, we draft an email.") Input/Output: What is the starting trigger (e.g., a new row in Google Sheets) and what is the desired final result (e.g., a Slack notification or a drafted PDF)? 2. Access to Tools & APIs The "Hands" of the Agent: I will need access (or API keys) for the platforms the agents need to interact with (e.g., Gamil, Sheets, Docs, Zapier, HubSpot, Slack etc). AI Model Preferences: If you have a specific preference for LLMs (e.g., GPT-4o, Claude 3.5, or a local Llama 3 instance), please let me know. 3. Your "Source of Truth" Knowledge Base: Any documents, PDFs, or URLs that contain the specific company data or "voice" the agents should use. Examples of Success: 2–3 examples of a "perfect" output done manually so I can use them for Few-Shot Prompting (teaching the AI exactly what "good" looks like). 4. Human-in-the-Loop Points Approval Stages: Identify where you want the AI to stop and wait for your "OK" before proceeding (e.g., before sending an email to a real client). 5. Hosting & Environment Where will it live? Do you want the agents to run on your local machine, a cloud server (AWS/Google Cloud), or within a no-code platform like Make.com? (If you're not sure, I can recommend the best fit for your budget).

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