Ron Mitchell

Quick summary Over the last 12–18 months, AI agents — not just chatbots — have moved from proof-of-concept to practical, multi-step tools that can access company data, run processes across apps, and complete tasks without constant human prompting. These agents combine large language models with retrieval (RAG), cloud connectors, and low-code automation to do things […]

Quick summary AI agents — autonomous systems that can read, act, and follow up across tools (email, CRM, calendars, databases) — are no longer just demos. Over the past year we’ve seen low-code agent platforms, better API/tool integrations, and stronger controls that let companies safely deploy agents for real work: lead qualification, customer follow-up, recurring

Quick summary AI agents — autonomous software that can read data, take actions, and talk to systems — are moving from labs into everyday business use. Instead of just answering questions, modern agents can qualify leads, triage support tickets, generate reports from your CRM and BI tools, and trigger follow-up actions automatically. Why this matters

AI agents are moving from experiments to real business workflows — here’s how to start Quick summary AI “agents” — autonomous, LLM-driven assistants that connect to apps, fetch data, and complete multi-step tasks — are no longer just demos. Companies are using them to draft personalized sales outreach, automate routine reporting, triage support tickets, and

Short summary AI agents — autonomous software that can read data, call APIs, and take actions — are no longer just lab experiments. Over the last year we’ve seen an influx of low‑code agent builders, better connectors to CRMs and ERPs, and safer enterprise controls that make agent-driven workflows practical for mid‑market and enterprise teams.

Quick summary Low-code AI agent builders and better ways to connect agents to company data (think CRMs, knowledge bases and cloud storage) are making practical, trustworthy business AI far easier to deploy. These “agents” — automated assistants that read, reason, and act on your data — are shifting from lab projects to real operational tools

Summary Big cloud vendors and AI startups are moving past single-prompt chatbots and pushing “AI agents” and customizable copilots that can act across apps, pull from your data, and complete multi-step tasks. In plain terms: these tools don’t just answer questions — they can read your CRM, run queries, update records, generate reports, and trigger

Hook AI agents — not just chatbots, but goal-driven assistants that act across apps — are moving from experiments into real business use. That shift matters for every leader who wants faster decisions, cheaper operations, and better sales outcomes. What’s happening – Major platforms and vendors have embedded generative features and agent workflows into CRM,

Big AI platforms (OpenAI, Microsoft, Google and others) are making it easy to build AI agents: autonomous, task-focused AI that can run sales outreach, generate routine reports, or trigger workflows across tools. These agents can read your CRM, draft personalized emails, pull weekly KPIs, and even take action — all with far less engineering than

Summary – What’s happening: AI agents — autonomous, task-focused AI that can read your systems, take actions, and follow up — are moving from demos into real business use. Companies are deploying agents to qualify leads, update CRMs, draft proposals, and produce routine reports without constant human supervision. – Why it matters for your business: