Ron Mitchell

What’s happening now AI has moved beyond single-response chatbots to autonomous “AI agents” that can plan, act, and follow up across multiple systems. These agents can do multi-step work — like qualify a lead, schedule a demo, update CRM fields, and generate a sales summary — without a human retyping every step. Organizations from startups […]

AI story (short) AI “agents” — systems that combine large language models with connectors, tools, and workflow logic — are moving from demos into real business use. Instead of a person copy-pasting between apps, an agent can read your CRM, pull finance data, draft a customer email, update records, and produce a one‑page report. Vendors

Quick take AI agents — autonomous, task-focused AI that can schedule, triage leads, draft outreach, and generate reports — are no longer just proofs-of-concept. Major vendors have embedded agent-style assistants into productivity suites and CRMs, and businesses are starting pilots that push routine work from humans to AI. That shift matters because it turns slow,

Big picture (the story) Over the last 12–18 months we’ve moved from “AI assistants” as chat toys to production-ready AI agents that can act on behalf of teams: pull CRM data, qualify leads, schedule follow-ups, generate pipeline reports, and trigger other systems. Major cloud vendors and many startups have shipped agent-building tools and connectors that

Big picture: Over the past year we’ve hit a tipping point — autonomous AI agents are no longer just demos. Companies are deploying agents that qualify leads, schedule meetings, prepare executive reports, and stitch together workflows across CRM, calendar, and data warehouses. These agents can take repetitive tasks off your team’s plate and produce near-real-time

Short summary AI agents — software that can plan, act, and use tools on your behalf — are no longer just research demos. Businesses are now using agents to handle tasks like qualifying leads, automating routine customer support, generating weekly reports, and orchestrating multi-step workflows across systems. These agents combine language models, API access (to

Quick summary AI agents — autonomous assistants that can read your systems, take actions, and talk to apps — are finally practical for day-to-day work. Over the last 18 months, major platforms added safer tool use, connectors, and better ways to integrate large language models with company data. That means AI agents can do useful

The story (short) – Over the past year, AI “agents” — autonomous workflows that read your data, take actions, and generate human-ready outputs — moved out of labs and into real business systems. – Vendors and startups now offer agent frameworks with CRM, calendar, email, and data‑warehouse connectors so these agents can qualify leads, update

Quick summary Autonomous AI agents — small, goal-directed AI programs that can read, act, and connect to systems — are no longer just demos. Over the past year we’ve seen major cloud and AI vendors release agent frameworks and integrations that make it practical for businesses to automate multi-step tasks: lead qualification, CRM updates, proposal

Short summary AI “agents” — models that can plan, use tools, and complete multi-step tasks — are rapidly moving out of labs and into everyday business workflows. Instead of single-answer chatbots, these agents can update CRMs, generate and send personalized sales outreach, assemble monthly performance reports, and trigger downstream tasks across systems. That means automation