Ron Mitchell

What happened (short summary) AI “agents” — autonomous workflows built from large language models plus tool connectors — have moved from experiments into practical business use. Instead of a human typing prompts and copying results, these agents can research accounts, draft personalized outreach, book meetings, update CRMs, and generate real-time reports without constant manual intervention. […]

Short summary Over the past year we’ve seen a clear shift: autonomous AI agents — systems that can plan, act, and coordinate across apps with little human prompting — are moving from lab experiments into real business workflows. These agents can research prospects, draft and send personalized outreach, update your CRM, generate weekly performance reports,

Short summary AI “agents” — software that can perform multi-step tasks, call other tools, and act on behalf of users — moved from lab demos into real business pilots in 2024. Toolkits and integrations from major platforms (tool calling, orchestration libraries, and business copilots) made it faster and cheaper to build agents that handle things

Quick story summary A new wave of AI “agents” — autonomous, task-focused AI that can read documents, run workflows, and interact with systems — is surging across enterprise tools. Major vendors and startups now offer agent platforms you can configure to qualify leads, create reports, escalate exceptions, or handle routine customer questions without coding every

Quick summary – Over the past year businesses have moved from experimenting with chatbots to piloting autonomous AI agents — systems that can access your data, run tasks, and take actions across apps (CRM, ERP, email, BI). – That shift matters because AI agents can cut repetitive work, speed up sales cycles, and deliver AI-powered

Summary AI “agents” — models that can act autonomously across apps, call APIs, and complete multi-step tasks — moved from demos to real business use in 2024. Companies are now using agents to draft personalized outreach, update CRMs, generate weekly sales reports, coordinate calendars, and trigger follow-up workflows without constant human prompting. Why this matters

Summary Over the past year we’ve seen a clear shift: AI “agents” — autonomous assistants that can take actions, run workflows, and talk to systems — are moving from labs and demos into real business use. Major platforms now make it easy to connect agents to CRMs, calendars, ticketing systems, and data warehouses. Early adopters

Short summary AI agents — autonomous, task-focused AI assistants that can run workflows, call APIs, and manage data — have gone from demo-stage curiosity to practical tools companies use for sales, ops, and reporting. Major cloud vendors and startups now offer agent toolchains and plug-ins that make it faster to connect AI to CRMs, calendars,

Quick summary Major enterprise software vendors and startups are embedding AI agents (think: “autonomous helpers” inside CRM, email, and analytics tools). These agents can draft outreach, update records, surface next-best actions, and generate quick reports — often with little manual prompting. The result: routine sales and operations tasks are being automated end-to-end, not just assisted.

Short summary AI “agents” — autonomous workflows powered by large language models — have moved from experiments to real business use. Modern agent frameworks let a model take actions (like pulling CRM data, drafting outreach, or running queries), call tools and APIs, and loop until a task completes. That means you can automate multi-step work