Ron Mitchell

The story in one line AI agents — LLM-powered assistants that can take multiple steps, call tools, and learn from data — have moved from experiments into real business pilots. Major vendors now support agent-style features and more companies are using them for sales outreach, automated reporting, and routine operations. Why this matters for business […]

Big picture story Over the past year, AI agents — autonomous software that can read data, make decisions, and take actions across systems — have moved beyond demos and developer playgrounds into real enterprise use. Companies are piloting agents for sales outreach, customer triage, claims processing, and automated reporting. The difference today is that vendors

Quick summary – AI agents — autonomous software that can research, draft messages, update systems, and trigger workflows — are no longer just experiments. Businesses are deploying them to qualify leads, automate routine sales tasks, and generate near-real-time reports. – The result: faster response times, fewer manual handoffs, and more accurate, actionable reporting for decision-makers.

Quick summary AI agents — purpose-built, conversational programs that can act on your systems — are moving fast from experiments to real business use. Platforms now let teams build low-code agents that connect to CRMs, calendars, databases, and analytics. That means multi-step tasks (lead triage, order changes, weekly reporting) can be automated end-to-end, not just

Story summary AI agents — small, goal-focused AI programs that can read data, take actions, and interact with apps — are no longer just proof-of-concept experiments. Businesses are increasingly using them to qualify leads, automate follow-ups, update CRMs, and generate executive reports. That shift matters because it turns AI from a cost center into a

Quick summary AI agents — autonomous, task-focused systems that can draft emails, pull reports, book meetings, or trigger workflows — moved from labs into real business teams over the last year. Companies are using agents for sales outreach, customer triage, expense automation, and real-time reporting. At the same time, regulators and internal risk teams are

What’s happening AI agents — autonomous workflows that combine large language models with tools, data connectors, and decision rules — have moved from experimental demos to practical business use. Improved developer frameworks (e.g., agent toolkits and function-calling APIs), better data connectors, and built-in observability/guardrails mean companies can now deploy agents for sales, operations, and reporting

Quick summary AI agents — software that can plan, act, and follow up on tasks with minimal human direction — are moving from demos into day‑to‑day use. Improvements in large language models, retrieval‑augmented generation (RAG), vector databases, and orchestration frameworks mean agents can now access company data, run workflows, and produce reliable outputs like sales

Quick summary AI “agents” — autonomous workflows built on large language models that can read, act, and follow multi-step instructions — have moved from labs into real business use. Tools and frameworks like LangChain-style agents, Auto-GPT concepts, and enterprise copilots + plugin ecosystems are making it practical to automate tasks that once needed human intervention:

Why AI agents are the next big productivity lever for sales and operations Quick summary AI agents — purpose-built, semi-autonomous AI “workers” that can research, act on systems, and produce reports — are moving from demos into real business use. Major cloud and AI vendors now offer low-code agent frameworks and integrations that let companies