What Jobs Are Morally Acceptable to Automate?

On the October 10th episode, Brian and Andy held down the fort for a focused, hands-on session exploring Google’s new Gemini Enterprise, Amazon’s QuickSuite, and the practical steps for building AI projects using PRDs inside Lovable Cloud. The show mixed news about big tech’s enterprise AI push with real demos showing how no-code tools can turn an idea into a working product in days.

Key Points Discussed

Google Gemini Enterprise Launch:

Announced at Google’s “Gemini for Work” event.

Pitched as an AI-powered conversational platform connecting directly to company data across Google Workspace, Microsoft 365, Salesforce, and SAP.

Features include pre-built AI agents, no-code workbench tools, and enterprise-level connectors.

The hosts noted it signals Google’s move to be the AI “infrastructure layer” for enterprises, keeping companies inside its ecosystem.

Amazon QuickSuite Reveal:

A new agentic AI platform designed for research, visualization, and task automation across AWS data stores.

Works with Redshift, S3, and major third-party apps to centralize AI-driven insights.

The hosts compared it to Microsoft’s Copilot and predicted all major players would soon offer full AI “suites” as integrated work ecosystems.

Industry Trend:

Andy and Brian agreed that employees in every field should start experimenting with AI tools now.

They discussed how organizations will eventually expect staff to work alongside AI agents as daily collaborators, referencing Ethan Mollick’s “co-intelligence” model.

Moral Boundaries Study:

The pair reviewed a new paper analyzing which jobs Americans think are “morally permissible” to automate.

Most repugnant to replace with AI: clergy, childcare workers, therapists, police, funeral attendants, and actors.

Least repugnant: data entry, janitors, marketing strategists, and cashiers.

The hosts debated empathy, performance, and why humans may still prefer real creativity and live performance over AI replacements.

PRD (Project Requirements Document) Deep Dive:

Andy demonstrated how ChatGPT-5 helped him write a full PRD for a “Life Chronicle” app — a long-term personal history collector for voice and memories, built in Lovable.

The model generated questions, structured architecture, data schema, and even QA criteria, showing how AI now acts as a “junior product manager.”

Brian showed his own PRD-to-build example with Hiya AI, a sales personalization app that automatically generates multi-step, research-driven email sequences from imported leads.

Built entirely in Lovable Cloud, Hiya AI integrates with Clay, Supabase, and semantic search, embedding knowledge documents for highly tailored email creation.

Lessons Learned:

Brian emphasized that good PRDs save time, money, and credits — poorly planned builds lead to wasted tokens and rework.

Lovable Cloud’s speed and affordability make it ideal for early builders: his app cost under $25 and 10 hours to reach MVP.

Andy noted that even complex architectures are now possible without deep coding, thanks to AI-assisted PRDs and Lovable’s integrated Supabase + vector database handling.

Takeaway:

Both hosts agreed that anyone curious about app building should start now — tools like Lovable make it achievable for non-developers, and early experience will pay off as enterprise AI ecosystems mature.