Ron Mitchell

Quick summary AI “agents” — autonomous, workflow-driving systems that combine large language models with data connectors, apps, and simple decision logic — moved rapidly from prototypes into real business tools in 2023–24. Low-code agent builders, pre-built CRM connectors, and tighter integration with reporting platforms mean teams can now deploy agents for routine sales tasks, lead […]

Quick story: AI agents — software that can act on your behalf, chain tasks, and use company data — moved from experiments into real business use in 2024. Startups and major vendors released agent frameworks and low-code orchestration tools that let teams build autonomous workflows for customer outreach, data checks, and regular reporting. The result:

Short summary AI “agents” — autonomous workflows that can read your systems, take actions, and follow up — are moving from labs into real business use. Companies are using them to qualify leads, auto-schedule meetings, draft personalized outreach, and generate near-real-time sales and operations reports. The result: less manual work, faster responses to customers, and

Quick summary A new wave of practical AI agents — autonomous helpers built on large language models — is making it easier for companies to automate sales tasks, generate faster reports, and streamline repetitive operations. Vendors have added agent frameworks, better integrations with CRMs, and safer retrieval-augmented workflows, so these tools are no longer just

The story in one line Autonomous AI agents — small, task-focused AI programs that can act, fetch data, and make decisions — are moving out of labs and into real business workflows. More platforms, low-code builders, and data connectors mean companies can automate work like lead qualification, meeting follow-ups, and routine reporting faster than before.

Short summary AI agents — software that can plan, act, and connect to other apps on your behalf — are no longer just research demos. Businesses are using agents to do end-to-end work: triage customer requests, run sales outreach, compile and explain weekly performance reports, and automate repetitive approval flows. The result is faster cycles,

Summary AI agents—software that can act autonomously to complete tasks—have moved from lab demos to real business use. Today’s agents can qualify leads, schedule meetings, draft and deliver reports, monitor KPIs, and orchestrate multi-step workflows across apps. They’re faster than manual processes and can run 24/7, which makes them especially useful for sales, operations, and

Quick summary AI “agents” — models that can act across apps, fetch data, and complete multi-step tasks — have moved from labs into real business use. Modern agent platforms (think tools that connect AI to CRMs, email, calendars, and databases) let companies automate complex workflows: qualifying leads, drafting proposals, updating orders, and assembling reports with

Short summary AI agents — AI systems that act on your behalf to complete tasks end-to-end — have moved from demos into real business use. Vendors and toolmakers now offer agent frameworks, connectors, and low-code integrations that let these systems read your CRM, generate proposals, update tickets, and create regular reports without constant human hand-holding.

Short summary AI “agents” — AI systems that chain tasks, call tools, and act on your data — are finally out of the lab and entering everyday business tools. Major platforms and startups now let these agents connect to CRMs, calendars, document stores, and APIs to do multi-step work: qualify leads, draft and send follow-ups,