Ron Mitchell

The story (short) – In the past year, AI “agents” — LLM-powered assistants that can act across apps, run workflows, and make decisions — moved from prototypes to real business tools. Major platforms and startups now offer agent frameworks and CRM integrations that can autonomously qualify leads, draft personalized outreach, update records, and generate reports. […]

Summary – What’s happening: Autonomous AI agents — software that can plan, act, and follow up across tools (email, CRM, calendars, dashboards) — are no longer just demos. Companies are deploying them to handle repeated, multistep tasks like lead qualification, proposal follow-ups, scheduling, and routine reporting. – Why it’s different: Instead of a human clicking

Short summary AI “agents” — autonomous, goal-directed AI that can run tasks, pull data, and interact with apps — have moved quickly from research demos into real business pilots. Companies are using agents to handle things like customer follow-ups, routine order processing, and automated reporting. The upside: faster workflows, fewer repetitive errors, and better use

Quick summary Autonomous AI agents — software that can connect to your systems, take multi-step actions, and follow goals with minimal human prompts — have moved from lab demos to real business pilots. Platform vendors and startups now offer low-code agent builders and pre-built connectors for CRMs, ticketing systems, and reporting tools. Companies testing agents

Hook: AI agents — small, customizable AI assistants that can access your data and act on your behalf — are moving from demos into real business use. The story in a nutshell – Over the past year, tools and patterns for building custom AI agents (often called “GPTs,” “autonomous agents,” or “AI assistants”) have matured.

Quick summary – A new wave of low-code AI agent tools is making it much easier for businesses to build autonomous assistants that work across CRMs, email, calendars, and databases. – These agents can monitor deals, draft outreach, update records, run daily forecasts, and even trigger workflows when exceptions occur — replacing many manual tasks

Quick summary Major cloud vendors and startups are shipping practical “AI agents” — autonomous assistants that connect to apps, pull data, and take actions (schedule, send messages, build reports). These agents aren’t just chatbots: they can use connectors, call APIs, and chain tasks to complete multi-step workflows across systems. Why this matters for businesses –

Quick pick: Custom AI agents (think low-code “GPTs” and vendor copilots) are moving fast from demos into real workflows — and companies are already using them to automate outreach, generate reports, and run routine processes. Why this matters to your business – What changed: Major AI platforms and enterprise vendors now let teams build specialized

Quick summary AI agents — small, goal-directed systems built on large language models — moved from experiments into real business tools in 2024. Low-code “agent builders” (custom GPTs, LangChain-style frameworks) plus retrieval-augmented generation (RAG) and vector databases now let companies safely connect LLMs to CRMs, files, BI tools, and automation platforms. Big vendors (Microsoft, Salesforce

Quick summary AI agents — small, task-focused AI “workers” that connect to your tools and take action — have moved from labs to real business use. Today’s agents can read CRM records, draft personalized outreach, update opportunity stages, and generate near-real-time sales reports. They don’t replace people; they handle repetitive work so your teams focus