Ron Mitchell

Quick summary – Over the last year companies have shifted from “trying” chatbots and LLM proofs-of-concept to deploying AI agents that do real work: multi-step processes, CRM updates, automated outreach, and natural‑language reporting. – New low-code agent builders, tighter CRM and data‑warehouse integrations, and retrieval-augmented generation (RAG) make these agents more accurate and business-ready. – […]

Quick summary AI agents — small, goal-focused AI programs that can read calendars, pull CRM data, send emails, run queries, and trigger workflows — are no longer just labs-and-hackathons experiments. Over the last year we’ve seen a wave of low-code agent platforms and “Copilot”-style integrations that let teams automate routine sales, ops, and reporting tasks

Quick summary AI agents — autonomous, task-focused AI that can carry out multi-step workflows — have moved from experiments to real business tools. Over the last year major cloud providers and low-code platforms have rolled out agent-building toolkits and analytics integrations. That means teams can now automate not just single tasks (like drafting an email)

Short summary AI “agents” — autonomous systems that can search your data, draft messages, update CRMs, and generate reports with little human prompting — have rapidly moved from experiments into real business use. Major platforms (custom GPTs, Microsoft’s Copilot family, and open-source agent frameworks) now make it easy to build task-focused assistants. That means companies

Quick story Autonomous AI agents — tools that can plan, carry out, and follow up on tasks across apps — moved from research demos to real business pilots in 2023–24. Think lightweight “digital teammates” that gather data, draft reports, run follow-up sequences, and trigger automated workflows. Early adopters are using them to reduce repetitive work,

Quick story summary Over the last 18 months we’ve moved past chat-only AI into a new phase: autonomous AI agents that can do multi-step work across systems — book meetings, draft outreach, update CRMs, generate reports, and follow up without a human typing every command. Major vendors and startups now offer agent platforms and marketplaces,

Summary AI agents — autonomous assistants that can research, draft, follow up, and update systems — are no longer just experiments. Organizations are increasingly embedding agent-style tools into CRMs, reporting pipelines, and customer workflows to automate repetitive tasks like lead qualification, follow-up emails, and routine reporting. The result: faster response times, fewer manual errors, and

Quick summary AI agents — autonomous, multi-step AI assistants that can act across apps and data — are moving from labs into everyday business use. Companies are using them to draft outreach, triage customer requests, automate routine approvals, and generate near-real-time reports. The result: faster decisions, fewer repetitive tasks, and more time for high-value work.

Quick summary Autonomous AI agents—software that can plan and execute multi-step tasks with little human direction—have stopped being just demos. Over the past 12–18 months companies have started putting specialized agents into production for sales research, lead outreach sequences, and automated reporting. These agents can scan public data, enrich CRM records, draft personalized emails, and

What’s happening Autonomous AI agents — software that can research, act across apps, and complete multi-step tasks with little human prompting — moved from demos into real business workflows in 2024. Companies are using them to enrich leads, draft personalized outreach, run and reconcile reports, and trigger follow-up workflows across CRMs, email, and project tools.