He runs 100s of AI agents ... here’s how

What does it actually look like to work with hundreds of AI agents? In this episode of NEXT with John Koetsier, I chat with Steve Ancheta, founder and CEO of Zig.ai, an AI-native platform for relationship-driven sales. Steve explains why what looks like a single AI agent to a user can actually be a swarm of hundreds of specialized agents working behind the scenes, handling copywriting, follow-ups, CRM updates, next-best actions, orchestration, and more. We also dig into how Steve personally uses AI agents as force multipliers across his work, why he still writes important investor and customer messages himself, and why simply giving an agent access to documents isn’t enough. Steve shares his approach to building an effective agent harness, including two critical pieces many people overlook: governance and grounded truth. We also discuss OpenClaw, NanoClaw, cloud-based agents, agent security, human-in-the-loop workflows, critical thinking, AI productivity, and the shift from reactive agents that wait for instructions to proactive agents that start doing useful work on their own. Topics include: - Why Steve believes many beginners shouldn’t build agents yet - How hundreds of specialized agents can operate as one system - AI agents as force multipliers rather than human replacements - Why human taste and connection become more important as AI improves - How Steve uses agents for planning, operations, scheduling, and analysis - The dangers of AI-generated documents nobody actually reads - Agent governance, guardrails, and permissions - Giving agents a reliable source of truth - Why vector databases alone aren’t a magic solution - Balancing human interaction with AI-assisted work - The move from reactive AI agents to proactive AI agents - Why humans should remain in the loop for external actions Guest: Steve Ancheta Company: Zig.ai 00:00 Why beginners may not be ready for AI agents 00:24 Working with AI agents every day 01:34 Steve Ancheta’s journey into AI 03:00 The early days of agent workflows 04:36 OpenClaw, Hermes, and the agent boom 05:37 The security problem with early AI agents 06:00 Why Steve moved agents to the cloud 07:00 Local agents vs. cloud-based agents 08:00 How quickly agent technology is evolving 09:00 How Zig.ai uses hundreds of AI agents 10:00 Why one “agent” may actually be an entire swarm 11:00 Specialized agents and orchestration 11:30 What Steve personally uses AI agents for 12:00 Why he still writes important emails himself 13:00 AI agents as force multipliers 14:00 Why AI won’t eliminate the human element 15:00 Human connection and taste matter more than ever 15:50 Steve’s favorite uses for AI agents 16:00 The danger of AI-generated documents 17:15 Agents for planning, operations, and forecasting 18:00 Using agents to find problems across a company 18:40 AI as a chief of staff 19:25 Why beginners probably shouldn’t build agents yet 20:00 What an agent harness actually does 21:00 Zig.ai is fundamentally a data company 22:00 Giving AI agents a reliable source of truth 23:00 Governance, guardrails, and agent permissions 24:00 Why vector databases aren’t enough 24:35 How AI agents change the way we work 25:20 Balancing AI time with human interaction 26:00 Why Steve deliberately spends time away from technology 27:00 The next phase: proactive AI agents 28:00 Keeping humans in the loop 29:00 When AI agents start giving us tasks