Ron Mitchell

Quick summary AI “agents” — autonomous workflows powered by large language models that can read systems, take actions, and talk back in plain English — are no longer just a lab curiosity. Major platforms and toolkits now let companies hook agents into CRMs, ERPs, help desks and BI tools so they can: – Draft and […]

Quick recap AI “agents” — software that can act on your behalf (think: read CRM data, draft emails, schedule follow-ups, and generate reports) — have moved past experiments and into real business workstreams. Companies are now using agents to automate routine sales tasks, produce faster customer reports, and keep data-driven follow-ups consistent across teams. Why

Quick summary AI agents — task‑focused, customizable AI assistants — are rapidly moving from demos into real business use. Major vendors now offer low‑code tools and marketplaces where teams can build agents that connect to CRMs, calendars, databases, and BI tools. Instead of one‑off chatbots, these agents can run multi‑step workflows, pull authoritative data, and

What’s happening AI “agents” — autonomous, goal-oriented software that can search data, run processes, and take actions — have moved from research demos into real business tools. No-code and low-code platforms now let teams build agents that connect to CRMs, data warehouses, and apps. That means businesses can automate multi-step tasks (like qualifying leads, generating

Summary AI agents — systems that can carry out multi-step tasks with minimal human prompts — have moved quickly from research labs into real business workflows. Vendors and startups are now packaging agents that can qualify leads, draft personalized outreach, prepare sales proposals, and generate weekly performance reports automatically. Why this matters for business –

Summary AI agents — software that can carry out multi-step tasks on your behalf — are moving quickly from tech experiments to real business tools. Companies are using agents to qualify leads, update CRMs, generate weekly sales reports, schedule demos, and even run routine customer follow-ups. The result: less repetitive work, faster response times, and

Quick summary AI agents — autonomous, task-focused AI that can read systems, take actions, and follow up — are moving from labs into everyday business use. Companies are using agents to automate routine sales follow-ups, triage customer requests, enrich CRM records, and generate management-ready reports. The big shift: these agents don’t just answer questions —

Quick summary AI agents — autonomous or semi-autonomous systems that can read your data, take actions, and produce reports — are rapidly shifting from experiments to everyday business tools. Instead of one-off chatbots, modern agents connect to CRMs, ERPs, email, and BI tools to qualify leads, automate follow-ups, reconcile invoices, and generate weekly sales and

Big idea — short summary AI “agents” — autonomous systems that can plan, act, and follow up on tasks — have moved past experiments and into real business use. Teams now use agents to research leads, draft personalized outreach, automate repeat workflows, and produce up-to-date reports without constant human orchestration. Why this matters for business

Quick summary Over the last year, “AI agents” — custom, task-focused AI assistants you can train and connect to your systems — moved from experimental projects to enterprise-ready tools. Platforms like OpenAI’s GPTs and low-code agent builders from major cloud providers make it faster to create agents that do things like triage leads, draft outreach,