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A/B Testing & Causal Inference — 64,000-Customer Email Campaign Analysis (Hillstrom Dataset)
A full randomized-experiment analysis, built to show the difference between running a statistical test and running one correctly — including catching and fixing my own methodology bug mid-project.
Result: A clear, statistically defensible recommendation (send the Men's email campaign to the full customer base) with honestly quantified conditions under which that recommendation would change.
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What if every new lead could be handled before you even open your inbox? ⚡
This AI-powered workflow turns a new email inquiry into a structured, ready-to-handle lead — automatically.
A new inquiry arrives → AI extracts the important details → Airtable/CRM is updated → the response goes through optional human approval → a personalized email is sent → Notion is updated → the team gets notified in Slack → performance data is collected for reporting.
The goal isn't to remove people from the process. It's to remove the repetitive work around them.
This type of workflow can be customized for B2B companies, SaaS businesses, agencies, real estate, e-commerce, recruitment, consulting, customer support, healthcare, finance, education, and other service businesses.
Already know what you want to automate? → Send me your current workflow and I’ll map out how we can automate it.
Still doing repetitive work manually? → Tell me the task that consumes your team’s time, and I’ll help identify what can be automated.
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I'd use the human approval step to capture corrections, not just a yes/no decision. If a reviewer changes the extracted lead details, does the workflow update Airtable and the reporting record before sending the email?
34 tested API endpoints that AI agents can discover and pay for per request in USDC, with no accounts or API keys. It includes a paid MCP server, marketplace listings generated from real outputs, SSRF-safe fetching, and 19 Apify Actors that offer bulk versions of the endpoints.
agents paying per request in USDC with no API keys is lowkey the future
🚨 CODES, SHADERS & SPOOKY UI: WHY BUILDERS CAN’T MATCH HAND-CODED PRECISION
Most creators blend static assets in Figma or Canva. As a Full-Stack Engineer, I treat code itself as an art form.
For the Rive Halloween Challenge, I brought together raw code, terminal-driven workflows, and GPU shaders into one ultimate dev collage:
• Rive CLI & RML: Writing responsive interactive scenes directly inside VS Code—zero bloat.
• GPU Canvas (WGSL Shaders): Custom fog, flickering lights, and real-time spooky effects powered directly by the GPU.
• Cybersecurity & Clean Architecture: High-performance, pixel-perfect web apps built to convert in 0.05 seconds.
Forget laggy plugins and heavy template builders. True digital experiences are engineered from the ground up.
💬 Quick Question for Creatives & Devs:
Are you team Drag-and-Drop Builders or team 100% Hand-Coded Architecture?
👇 Drop your thoughts below, let's connect and push the boundaries of modern web tech!
The part where you drive fog and flickering lights with WGSL shaders on the GPU feels like the kind of low level control that really cuts latency.