Ron Mitchell

Quick summary AI “agents” — software that can research, decide, and act across systems — are no longer just experiments. Across industries, companies are using agents to run end-to-end workflows: qualify leads, draft and send personalized outreach, update CRMs, and generate management reports automatically. The result is faster sales cycles, fewer manual errors, and real-time […]

Short summary AI platforms now make it easy for businesses to build custom AI agents that can read your CRM, query your ERP, schedule actions, and produce ready-to-share reports. Instead of one-off prompts, these agents can run workflows autonomously — draft follow-ups, flag opportunities, generate weekly sales dashboards, and push alerts when numbers deviate. Why

A short story Autonomous AI agents — systems that combine large language models with connectors, tools, and simple decision rules — are no longer just lab experiments. Over the past year organizations have moved from one-off demos to production agents that: – Triage customer tickets and draft responses – Pull and prepare weekly sales and

What’s happening AI agents — software that can plan and execute multi-step tasks on its own — are moving from experiments into everyday business use. Today’s agents can search for leads, draft personalized outreach, update CRMs, generate weekly dashboards, and even follow up on routine customer questions without constant human prompts. Companies are using them

Short summary Major software vendors and startups are embedding autonomous AI agents into everyday apps — from CRMs that draft and send outreach, to helpdesks that triage tickets, to finance tools that reconcile transactions and generate variance reports. These agents don’t just assist; they can act on your behalf, chain tasks together, and surface insights

Story summary AI agents — persistent, task-focused AI that can act across apps and systems — have moved from lab demos to real business use. Instead of one-off chat answers, these agents run recurring workflows: qualify leads in your CRM, follow up with customers, generate weekly sales reports, or triage support tickets automatically. Improvements in

Short summary AI agents — purpose-built AI “assistants” that run tasks, connect systems, and act on your behalf — moved from experiments to practical business tools in 2024. Platforms like custom GPTs, Copilot Studio, and agent frameworks made it far easier to create agents that qualify leads, update CRMs, generate management reports, and automate repetitive

Summary AI “agents” — systems that autonomously complete multi-step tasks by connecting to tools, data, and APIs — have stopped being a research novelty and are now showing up in real business workflows. Modern agents combine large language models with retrieval-augmented knowledge, secure integrations to CRMs and ERPs, and orchestration layers that let them act

Story summary • Over the past year, “agentic” AI — autonomous assistants that take actions across apps and systems — has shifted from lab demos to real business pilots. Vendors and cloud providers now offer enterprise-grade agent platforms that connect to CRMs, email, databases, and analytics tools. • These agents can do tasks end-to-end: qualify

Summary AI “agents” — software that plans, uses apps, and acts on your behalf — have matured quickly. What used to be experimental scripts is now commercial platforms that can read your CRM, generate reports, qualify leads, book meetings, and trigger downstream processes. That shift means automation that used to require heavy custom engineering is