Ron Mitchell

Summary — the story in plain language AI agents — software that can plan, act, and follow up on tasks using large language models — have crossed a practical threshold. What used to be experimental (AutoGPT demos and research projects) is now showing up in everyday business tools: agents that draft personalized outreach, generate weekly […]

Quick summary This year, big enterprise platforms (Microsoft, Google, Salesforce and others) pushed AI agents and “Copilot”-style assistants deeper into CRM, collaboration, and reporting tools. Those agents can draft outreach, update records, run analytics, and even trigger workflows — often with simple chat prompts. For businesses, the result is faster day-to-day work and new automation

What’s happening AI agents — software that can think, act, and carry out multi-step tasks with little human prompting — are moving out of labs and into everyday business workflows. From vendor tools and platform-driven copilots to open-source agent frameworks, companies are using agents to qualify leads, triage support tickets, generate sales insights, and assemble

Quick summary AI “agents” — autonomous or semi-autonomous AI assistants that perform multi-step tasks — are moving from experiments into real business use. Think Copilot-style assistants that summarize meetings and update your CRM, AI services that run end-to-end sales outreach, or automated reporting agents that pull data, generate narratives, and push insights to dashboards. Major

Story summary AI agents — autonomous, tool-using AI that can read systems, take actions, and follow multi-step instructions — are no longer just research demos. Over the past year companies have started deploying them to handle real sales and operations tasks: prospect research, personalized outreach, meeting follow-ups, CRM updates, and automated reporting. These agents combine

Big idea (short summary) AI agents — autonomous, task-focused AI that can act across apps — have moved from experiments into real business tools. Products from major vendors and the rise of open-source agent frameworks are letting companies build agents that do things like generate weekly reports, enrich leads, run personalized outreach, and orchestrate cross-system

Short take: AI agents — autonomous, task-focused AI that can act across apps, draft messages, and generate reports — are leaving pilots and showing real ROI in sales, operations, and reporting. Major cloud vendors and a wave of tools make it easier to build agents that qualify leads, update CRMs, summarize meetings, and produce automated

The story (short version) A new wave of “AI agents” — AI systems that can plan, act, and connect to apps and data — is moving from labs into real business use. These agents combine large language models with tool access (APIs, CRMs, calendars, databases) and orchestration frameworks so they can take multi-step actions: pull

Summary AI agents — autonomous, multi-step AI assistants that can read, decide, act, and report — are no longer a novelty. A growing set of low-code agent builders, enterprise copilots, and AI-powered reporting tools now let companies automate complex workflows: from prospect outreach and contract review to help-desk triage and executive dashboards. That shift matters

The story (short) Enterprise AI is shifting from prototypes to practical, production-ready “AI agents” — systems that can complete multi-step tasks (qualify leads, create reports, book meetings, update CRM records) with little human supervision. Over the past year we’ve seen cloud vendors and startups push agent platforms that connect models to company data, apps, and