Because LLMs are non-deterministic like humans, it's more effective to integrate them using existing human-centric processes. Give an agent an email, permissions, and "onboarding" so it can navigate the organization like an employee, rather than building complex new software interfaces.

The overhead of maintaining personal AI agents is too high for most employees. The successful model, seen at Shopify and Ramp, is a centralized, company-wide "super-agent" managed by a dedicated team, ensuring it remains reliable and useful for everyone.

Current communication tools like Slack are ill-suited for managing AI agents. The future lies in integrated "super apps" that combine chat interfaces with built-in credential management, file systems, and API key provisioning, creating a unified environment for human-agent collaboration.

Frame your relationship with AI agents as an employer-employee dynamic. This involves proper onboarding, creating documentation for processes, and defining clear roles and communication protocols to ensure they operate effectively and align with your goals.

Shift the mental model from "building a workflow" to "hiring an employee." This focuses development on providing agents with the right knowledge (onboarding), context, and tools (a clear job description) to perform complex tasks autonomously.

To properly integrate an AI agent into your workflows, provision it like a new hire. Give it a dedicated email address, a GitHub account, and specific access permissions. This mental model simplifies security, access control, and collaboration, making the agent a true digital team member.

Building a bespoke communication layer for multiple AI agents is a complex "scaffolding" problem. A simpler, more direct solution is to treat agents as digital coworkers, assigning them accounts on existing platforms like Slack or Google Docs, enabling them to interact using established human workflows.

Intercom's CEO predicts that companies will abandon separate AI agents for sales, service, and onboarding. A single, coordinated "customer agent" is necessary to avoid conflicting goals and create a seamless, high-touch experience for every user.

To maximize an AI agent's effectiveness, treat it like a team member, not just a tool. Integrate it directly into your company's communication and project management systems (like Slack). This ensures the agent has the full context necessary to perform its tasks.