Everyone talks about AI agents. But few actually show useful workflows. In today's episode, Harish Mukhami actually builds an AI employee:
He builds an AI CS agent in just 62 minutes.
📌 Watch here: https://xmrrwallet.com/cmx.plnkd.in/eKbay8tu
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Harish is the former CPO at LeafLink (valued at $760M) and Head of Product at Siri.
Now, he is the CEO and founder of GibsonAI, which built the scalable database behind our AI agent.
Here were my favorite takeaways:
1: Building an AI employee just took 62 minutes. Harish demonstrated creating a fully functional customer success agent using ChatGPT O3 Mini, Gibson AI, Cursor, and Crew AI. The system analyzes data, identifies churn risks, sends emails, and creates Jira tickets—all production-ready.
2: Follow a three-stage evolution for maximum adoption success. Start with dashboards for insights, move to AI recommendations with human approval, then progress to full automation. This builds organizational confidence while gradually removing humans from routine tasks.
3: Architecture planning upfront prevents weeks of technical debt later. Use reasoning models like O3 Mini to define data models and business logic before coding. This ensures clean integration with existing tools rather than building isolated prototypes.
4: Production infrastructure is becoming accessible to non-technical teams. AI-powered databases auto-provision environments, generate APIs, and handle scaling without DevOps knowledge. Gibson deployed production-grade infrastructure in <3 mins.
5: MCP protocols eliminate the need to context-switch between tools. Model Context Protocol connects databases to code editors, letting you manage everything through natural language. Complex workflows across multiple tools become simple prompts.
6: Multi-agent frameworks make sophisticated automation accessible to PMs. Crew AI abstracts complexity that normally requires engineering expertise. Define specialized agents and orchestrate them like managing a human team with clear handoffs.
7: Any information worker role can now be automated. The same framework applies to SDRs, recruiters, and executive assistants. If your job involves data analysis and action-taking, it's automatable.
8: The PM skillset is evolving faster than most teams realize. Product managers who can architect agent workflows and design human-AI handoffs will have exponential impact. Natural language is becoming the primary interface for building software.
9: Development timelines have compressed from quarters to hours. The combination of reasoning models, AI infrastructure, and agent frameworks represents the biggest productivity shift since cloud computing for resource-constrained product teams.
