Ron Mitchell

Short summary AI “agents” — AI systems that act autonomously to complete tasks across apps and data — are moving from research demos into real business use. Tools and frameworks (think agent-enabled versions of Copilots, LangChain-based agents, and generative models with tool access) now let AI fetch documents, update CRMs, draft outreach, and generate recurring […]

Quick summary AI “agents” — autonomous assistants that can read your data, take actions, and follow multi-step workflows — are rapidly moving out of experiments and into mainstream business tools. Major vendors and open-source frameworks now offer agent toolkits and connectors that let these assistants interact with CRMs, calendars, BI dashboards, and internal knowledge bases.

Short summary AI agents — software that acts on your behalf across apps and data — have moved from experiment to enterprise-ready. Recent advances in connectors, retrieval-augmented models, and secure sandboxing mean agents can now complete repeatable business tasks: qualify leads, draft and send follow-ups, build sales reports, and update CRMs — often with minimal

Short summary AI “agents” — autonomous or semi-autonomous AI programs that can fetch data, take actions, and follow multi-step workflows — have moved from experiments to practical tools for businesses. Advances in foundation models, retrieval-augmented generation (RAG), and better integrations with CRMs and ERPs mean these agents can now do reliable tasks like lead qualification,

What happened (short summary) AI “agents” — autonomous, task-focused assistants that can access tools and company data — moved from research demos to real-world pilots across 2023–2024. Vendors and open-source frameworks made it easier to build agents that do things end-to-end: triage leads, generate and distribute reports, update CRM records, schedule follow-ups, and escalate exceptions

The story in plain terms – Over the past year we’ve seen AI agents — autonomous LLM-driven workflows that can read your CRM, draft outreach, book meetings, and update records — move out of R&D labs and into real sales teams. – These agents connect to tools (email, calendars, CRM, knowledge bases) and run multi-step

Summary — What’s happening AI agents—autonomous software that can read, act, and learn across your tools—have moved from prototypes to everyday business use. Instead of one-off chat responses, modern agents can pull data from your CRM, send follow-ups, update records, prepare weekly reports, and even trigger downstream processes automatically. They’re being embedded into sales stacks,

Quick summary Autonomous AI agents — task-focused bots that research, act, and report with limited human supervision — moved from tech demos into real enterprise use in 2024–2025. Companies are deploying agents for lead qualification, routine customer responses, automated reporting, and workflow handoffs. The result: faster response times, fewer manual errors, and more bandwidth for

Quick summary – Autonomous AI agents are getting practical fast. These are AI-driven workflows that can read your CRM, draft outreach, pull data, and take actions across apps with minimal human prompts. – For businesses that sell, operate, or report regularly, agents can automate repetitive tasks (lead qualification, follow-up emails, weekly reporting) and surface insights

Quick story Major AI vendors and enterprise platforms have moved beyond demos: in 2024 we saw a wave of “agent” and low‑code automation features baked into business apps and reporting tools. Vendors are shipping ways to chain tasks, call systems, and run multi‑step workflows (think: qualify a lead, enrich the record, create a follow-up task,