Ron Mitchell

Quick summary AI agents — autonomous, multi-step AI assistants that can read, act, and integrate across systems — stopped being a novelty in 2024 and are becoming practical tools for businesses. Major platform vendors (think Copilot-style features across Microsoft 365 and CRM AI in Salesforce) combined with open agent frameworks mean companies can automate complex […]

AI agents go mainstream — what this means for sales, reporting, and automation Summary Recent advances in AI — especially “agent” style models and easy-to-build custom GPTs — have moved beyond demos into practical business use. Companies can now create AI agents that connect to CRMs, calendars, internal docs, and analytics tools to automate routine

Quick summary AI “agents” — systems that act autonomously across apps and data sources — are rapidly maturing. They can now connect to calendars, CRMs, finance systems, and knowledge bases to complete multi-step tasks: qualify leads, generate weekly reports, file invoices, reserve rooms, and escalate exceptions to people. That shift is making AI less of

Quick summary AI “agents” — autonomous, multi-step AI workflows that can research, decide, and act across systems — have gone from research demos to real production uses. Companies are now using agents to qualify leads, run outreach, generate recurring reports, and automate repetitive back-office work. That makes AI less of a one-off tool and more

Quick summary AI agents — autonomous, multi-step AI workflows that can research, act, and update systems — are no longer just a developer playground. Over the past year we’ve seen them move into real business use: automating lead research and outreach, running recurring financial and performance reports, triaging customer inquiries, and orchestrating cross‑system processes (CRM

Short summary Custom AI agents — purpose-built, autonomous assistants that connect to your apps and data — are moving from tech demos into real business use. Low-code “agent builders” from major vendors and open frameworks make it easier to create agents that qualify leads, summarize meetings, generate reports, or automate routine steps across systems. Why

Quick summary Over the last couple of years we’ve moved past “chatbots” to a new class of AI tools often called AI agents — autonomous, multi-step assistants that can access your systems, run processes, and take actions (for example: pull CRM data, compile a sales report, create and send follow-ups, or update your ERP). These

Summary AI is shifting from single-query chat tools to autonomous, task-focused “agents” that can act on your behalf. These agents combine large models with connectors, memory, and business logic so they can: – Read your systems (CRM, ERP, email) via secure connectors – Perform multi-step tasks (qualify leads, update records, generate reports) – Schedule actions

Quick summary Autonomous AI agents—software that can take multi-step actions (like qualify leads, follow up with prospects, or build recurring reports)—are moving from labs into real business use. Cloud vendors and startups have released agent platforms and templates that let companies automate complex workflows without building everything from scratch. Why this matters for your business

Quick story summary Autonomous AI agents — AI systems that can take multi-step actions (like researching a lead, composing outreach, updating a CRM, and scheduling follow-ups) — have moved rapidly from prototypes to practical tools for businesses. Improved developer frameworks, plug-and-play integrations with CRMs and data warehouses, and more reliable retrieval systems (RAG) mean teams