Ron Mitchell

Quick summary AI “agents” — autonomous, task-oriented AI that can fetch data, take actions across systems, and carry out multi-step workflows — have stopped being just experiments. Over the last 12–18 months we’ve seen major platform features (Copilot-style assistants, function-calling in models, and agent frameworks like LangChain/AutoGen) plus improved retrieval-augmented methods that make agents far […]

Quick summary AI “agents” — autonomous, task-focused AI that can connect to your tools (CRM, calendar, reporting systems) and carry out multi-step work — have moved from experiments to practical deployments. Major AI platforms now let businesses build custom agents that qualify leads, create tailored outreach, update records, and generate recurring reports with little human

Quick summary There’s a clear surge in practical, business-ready AI agents — small, task-focused systems that can act on your behalf: qualify leads, update CRMs, generate weekly sales reports, schedule demos, and trigger follow-up automations. At the same time, generative features in BI tools let teams ask plain-English questions of company data and get narrative

Summary • 2024 accelerated a clear shift: AI agents — autonomous, task-focused AI that can search systems, run workflows, and produce decisions — moved from demos into real business use. Major platforms and open-source tools made it easier to build agents that connect to CRMs, email, calendars, and internal data. • For businesses, that means

AI story in one line AI agents — autonomous, task-focused tools that can read your inbox, update your CRM, run reports, and even take multi-step actions across apps — are maturing fast. Better connectors, retrieval-augmented generation (RAG), and more reliable planning mean agents are shifting from lab demos to real, repeatable business wins. Why this

Quick summary – Over the last year, “AI agents” — autonomous AI programs that complete multi-step tasks — have moved from demos to real business use. Companies are using agents to draft personalized outreach, update CRMs, generate weekly performance reports, and automate repetitive workflows across sales and operations. – The result: fewer manual steps, faster

What’s happening AI agents — autonomous software that can read, act, and follow up across apps — moved fast from demos to practical use in 2023–24. Improvements in model grounding, retrieval-augmented generation, app connectors, and enterprise-grade guardrails mean agents can now handle real workflows: triaging support tickets, filling crm records, running routine audits, and producing

Quick summary AI agents — autonomous, task-oriented AI that can read, write, call APIs, and act across apps — moved from hype to practical use over the last few years. Cloud vendors (Copilot-style assistants), open-source agent frameworks (LangChain, AutoGen), and pre-built connectors mean companies can build agents that do real work: draft outreach, run recurring

Quick summary Companies are moving beyond chatbots and single-task tools to deploy autonomous AI agents — small, goal-oriented systems that can complete multi-step workflows on their own. Examples: agents that qualify leads, book meetings, draft proposals, update your CRM, and produce weekly performance reports without human prompts for each step. Why this matters for business

Summary AI agents—autonomous, task-oriented AI that can read your data, take actions, and talk to other systems—have moved past demos and into real business use. Major cloud vendors and AI platforms now offer low-code agent builders and prebuilt connectors that let teams automate workflows, generate reports, and handle routine sales tasks without heavy engineering. Why