Ron Mitchell

Summary — what’s happening now A new wave of autonomous “AI agents” is moving from labs into everyday business use. These agents are software that can perform multi-step tasks on their own — for example, qualify leads, update CRMs, run monthly reports, or follow up on overdue invoices. Vendors and open-source tools now make it […]

Quick summary – Over the past year the focus in AI has moved from raw model accuracy to production-ready agents and orchestration: businesses can now stitch LLMs, retrieval systems, connectors (CRM, ERP), and automation tools into reusable “agents” that act on your data and processes. – That shift makes tasks like automated outreach, recurring report

Quick summary AI agents — autonomous, chainable software assistants that can read data, take actions, and update systems — are moving from experiments into real business use. Companies are using them to research leads, personalize outreach, update CRMs, and generate routine sales and operations reports without manual handoffs. The tools are easier to set up

The story (short summary) AI “agents” — autonomous workflows that use large language models plus plugins, connectors, and tools — have moved from experiments into real business use. Over the past year we’ve seen vendors and developer frameworks make it easier to build, deploy, and monitor agents that do things like manage sales outreach, pull

Summary Over the past year we’ve seen a clear shift: AI agents — autonomous, task-focused AI programs — are moving from demos into real business work. Instead of one-off chat answers, companies are chaining LLM steps, connecting agents to CRMs, email, spreadsheets and internal APIs, and letting them do multi-step tasks like lead triage, sales

Quick summary AI agents — software that can act on your behalf across apps, pull data, and complete tasks — are moving fast from labs into business tools. Recent vendor releases and enterprise pilots show agents can draft outreach, triage leads, generate sales reports, update CRMs, and trigger follow-ups without humans doing every click. Why

Summary A new wave of AI agents — conversational, task-focused systems that can access apps, data, and APIs — is crossing the gap from lab demos into real business use. Over the last year, major cloud and CRM vendors have released secure connector frameworks and low-code tools that let companies safely deploy agents to do

Big idea in one line AI agents — autonomous, goal-driven software that can read your systems, take actions, and return answers — are moving from lab demos into real business work: qualifying leads, running daily reports, and automating routine workflows. What’s happening (short summary) In the past year we’ve seen an explosion of enterprise-focused agent

Short summary Autonomous AI agents — software that can take actions, not just generate text — are crossing a tipping point. What began as developer demos is now becoming practical for everyday business work: automated prospect research, intelligent email follow-ups, CRM clean-up, and real-time sales reporting. Early adopters are replacing repetitive tasks with agent workflows

Summary AI agents — software that combines large language models with tools (email, calendar, CRM, search, docs) — have moved quickly from proofs-of-concept to real business pilots. Companies are now using agents to triage leads, draft highly personalized outreach, book meetings, update CRM records, and run faster what-if forecasts for pipeline scenarios. Why this matters