Episode
[Redacted] an NC Tweener Times Podcast: The AI Workflow Graveyard: CRMs, Agents, and... Tamagotchis?
- Podcast
- NC Tweener Talks
- Published
- May 20, 2026
- Duration seconds
- 2321
- Processing state
not_requested- Canonical source
- https://share.transistor.fm/s/63b1ef1d
Actions
POST https://stenobird.com/v1/public/podcasts/nc-tweener-talks-7053588/episodes/redacted-an-nc-tweener-times-podcast-the-ai-workflow-graveyard-crms-agents-and-tamagotchis/transcription-requests
Idempotently request low-priority transcript generation for this episode.GET https://stenobird.com/podcast/nc-tweener-talks-7053588/redacted-an-nc-tweener-times-podcast-the-ai-workflow-graveyard-crms-agents-and-tamagotchis.md
Read the agent-friendly Markdown representation of this episode resource.
Summary
In episode 2 of Redacted, David and Taylor get into the messy middle of building with AI inside a real business. After compressing Offline from a 34-person team to a much smaller operating crew, AI stopped being a fun experiment and became a necessity. This episode is about what that actually looks like: rebuilding lead-gen workflows, trying to make HubSpot reflect reality, keeping AI agents alive like Tamagotchis, and testing whether Claude Code can help generate a real shareholder update from scattered company data. What They Cover Why David and Taylor are sharing their AI experiments publicly How Offline compressed from 34 full-time employees to a much smaller team while still serving hundreds of restaurants and thousands of subscribers Why CRM cleanup is way harder than it sounds The difference between n8n workflows and locally built AI agent systems Taylor’s attempt to build a multi-agent flow for HubSpot cleanup The “AI existential crisis” that happens when a system kind of works, but not enough David’s shareholder update experiment using Claude Code How AI pulled context from financials, GitHub commits, payroll, board notes, and prior updates Why the best AI workflows are often context problems, not prompt problems The takeaway: AI can do a lot more than send one email, but only if you teach it where the business actually lives. Timestamps 00:00 — Welcome back to Redacted 00:36 — “Why should people even listen to us?” 02:07 — How Offline compressed from 34 employees to a tiny team 03:58 — The original AI lead-gen and CRM automation experiments 06:27 — Translating complicated human workflows into AI systems 07:00 — AI-powered inbound lead classification and HubSpot automation 08:09 — Using RSS feeds and AI to discover restaurant leads 08:52 — Where CRM automation…