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Over the past few weeks, I’ve been bombarded by AI recruitment systems that must have pulled my details from LinkedIn. LinkedIn scraping ain't easy so I tried to work out what's going on.
The answer is Exa’s AI Powered People Search. They’ve scraped LinkedIn to create a database of around a billion profiles and released tools for it on their MCP.
Setting this up was simple. I already use Exa’s MCP for my local models.
Now, I can extract full staff lists, analyse work histories, or search for people by job title and location, all through a chat interface.
Exa is taking a risk though. LinkedIn won’t be happy, and while the data is current now, maintaining a dataset this large seems like a challenge.
Still, it’s a clear example of how quickly things move with MCP. Exa releases a tool and within days, recruiters are using it.
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Built this AI agent to find, organize, and manage leads through Gmail, helping automate lead handling and outreach.
n8n is absolute gold for orchestrating lead pipelines like this! Connecting Gmail parsing with LLM qualification saves teams dozens of hours weekly. As someone who builds custom agentic lead automation workflows, seeing clean visual architectures like this is super satisfying. Top-tier build, Talha!.
So I Recently rebranded my upcoming AI Agent Harness from "Crank" to "Pixie" which is the name of my cat. Do you think it was the right decision?
Which one do you prefer? Crank or Pixie?!
Check it out here: pixie.ecnivs.com
#FreelancerLife #AIHarness #FrontendDesign #AIAgent #ArtificialIntelligence #WebDevelopment #Design #TasteTest
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Pixie gets my vote too. Naming it after your cat makes it memorable, and it feels a lot friendlier for a tool people trust with their code. Nice rebrand.
AI-Powered Lead Follow-Up & Management for Miale
I automated lead follow-up and management for Miale to reduce the manual work involved in reviewing enquiries, categorizing leads, responding to prospects, and keeping the team informed.
The problem:
When leads come in, manually reviewing each response, deciding how to handle it, sending emails, and notifying the team can take time, and makes it easier for follow-ups to slip through the cracks.
The solution:
I built an AI-powered workflow in Make that automatically processes new lead submissions.
Here’s how it works:
Google Form → Google Sheets → AI Classification → Router → Email + Slack → Lead Tracking
When a prospect submits the form, AI analyzes their collaboration interest and categorizes the lead as Collaboration Lead, Needs Follow-up, or Not Interested.
The workflow then automatically:
- Routes the lead based on their response.
- Sends a relevant email to the prospect.
- Notifies the team in Slack when a new lead needs attention.
- Updates the lead record for easier tracking.
Tools used:
Make · Make AI Toolkit · Google Forms · Google Sheets · Gmail · Slack
The workflow can also be adapted for client enquiries, sales leads, service requests, bookings, applications, and other repetitive lead-management processes.
The goal isn't simply to automate tasks. It's to build a system that helps businesses respond faster, stay organized, and reduce manual follow-up work.
