Quick news. We're doing our first virtual event, and the rule is simple: every person on stage has to show their actual work. The actual projects they're selling. The actual outreach they're using to land clients. The actual numbers behind it. No theory. No tutorials. Just what's working in 2026, taught by the people doing it. Waitlist's open. Get on it before tickets go live: -> What's working in AI in 2026 (real projects, real revenue) PS: Annual members of AIS+ get in for free. We will be announcing discounts for monthly members. If you’ve been thinking about joining AIS+, it’s a good time.

I used Claude Code + Firecrawl MCP to scrape job listings from Indeed.ca for a specific role and export the results into a structured CSV file. What surprised me the most:I expected it to scrape Indeed only. Instead, the Firecrawl MCP intelligently expanded the search and started pulling related job data from other websites like Glassdoor as well. It was interesting to see the agent dynamically choose additional relevant sources without me explicitly telling it to. One immediate use case I see:This could become a powerful lead generation and market research system for recruiters, agencies, or B2B businesses. Imagine automatically tracking hiring trends, identifying companies actively hiring, and using that data for outreach or market intelligence.

I've spent over 400 hours inside Claude, and I'm breaking down exactly what separates someone stuck on level 1 from someone running five parallel sessions while they sleep, with the cheat codes to jump between each stage. Hope you enjoy!

Hi everyone, sharing a quick update on my progress with the #AIS Challenge. So far, the system is working well. I successfully automated the full workflow: • AI researches and writes the newsletter • Images and visuals are generated automatically • The final HTML newsletter is emailed directly to recipients The interesting part is realizing that the quality of the output now depends heavily on the instructions given to the agent. I still need to refine the prompts and workflows so future newsletters consistently include all the elements I want, like infographics, layouts, visual hierarchy, and formatting standards. But from an automation perspective, it’s working end-to-end. Now I’m thinking about deployment and scalability. For those building AI automation systems: What are you using for the frontend and deployment layer? Vercel? Railway? Render? Something else? Curious to hear how others are approaching production-ready AI workflows.

Hi, everyone! I’m sharing the results from Day 1 of the #AISChallenge. One thing I learned that really stuck with me is how to connect the APIs, and one improvement I made to the project was changing the colors of the newsletter and adding the logo to the infographic. However, I have a question: how can I make sure the text in the infographics looks good? Thanks for your feedback.