Day with AI: Full Lead Gen System in a Day. 7 Workflows, CRM, Cold Emails.
7 n8n automations, Notion CRM, company scraping, AI enrichment and cold email pipeline. Plus frontend migration to Netlify. A Wednesday that normally takes a month.

What I worked on today
Wednesday. Two big commits, each would normally be a week-long project.
1. Lead generation pipeline — from zero to system
This one took the most effort. Complete pipeline for generating leads:
- Notion CRM — extended the existing clients database with lead gen fields (lead status, source, scoring, follow-up date)
- 7 n8n workflows — company scraping from firmy.cz and Google Maps, enrichment via ARES and AI website analysis, cold email sending, open tracking, and follow-up sequences
- CLI tool — `lead-manager.ts` for terminal management (stats, list, add, campaign)
- Demo tool — for client presentations
From "I have no lead system" to "I have CRM, scraping, enrichment and automated emails" in a day. Without AI? Two weeks, realistically.
2. FE migration to Netlify + system documentation
Moved frontend hosting from Vercel to Netlify free tier (saves credits). Also wrote workflow rules for Claude Code and updated system documentation — CLAUDE.md, setup guides, architecture.
Small thing next to the lead gen, but important. A system without docs is a system nobody understands in a month. Including yourself.
Time: AI vs without AI
| Task | Without AI | With AI |
|---|
| Lead gen pipeline (CRM + 7 workflows + CLI) | 40h+ (2 weeks) | ~24h |
|---|---|---|
| FE migration to Netlify + workflow rules + docs | 8h+ | 2h |
| Total | 48h+ | ~26h |
2 commits. 3 AI sessions. And a system that would normally take a month to build.
What I learned
- A lead gen pipeline with AI can be built in a day. Notion as CRM, n8n for automation, ARES for enrichment — all free or nearly free. No expensive SaaS needed.
- Netlify free tier for FE hosting is a solid choice when you don't want to pay per deploy on Vercel. Just watch the build minutes.
- System documentation is an investment. Spending an hour writing workflow rules for an AI agent saves hours in every future session.
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