Ron Mitchell

Attention grabber: Autonomous AI agents — not just chatbots, but software that plans, executes, and adapts — are rapidly shifting from experiments to real business workflows. Sales teams, ops leaders, and finance managers are already using them to qualify leads, run follow-ups, and generate routine reports. What happened (short summary) – Over the past year […]

Quick summary Over the last year we’ve seen no-code and low-code “AI agent” builders move from demo to real work. These agents—small, task-focused AI workers—now handle things like lead qualification, personalized outreach, meeting summaries, and automated dashboarding. Companies are connecting agents to CRMs, BI tools, and document stores so the AI can act on business

Summary AI “agents” — autonomous workflows built from large language models, connectors, and business logic — have shifted from tech demos to real revenue drivers. Companies are using agents to qualify leads, automate sales outreach, summarize meetings, and generate routine reports. Low-code agent platforms, better retrieval-augmented generation (RAG), and tighter CRM/ERP integrations make deployments faster

Big idea (short): Over the last 18 months we’ve seen a clear shift: AI agents — autonomous, task-focused systems that can read data, take actions, and interact with apps — are moving from demos into real business use. Major cloud and AI vendors plus startups now offer low-code agent platforms, making it practical to automate

Quick summary There’s a clear, recent shift: businesses are moving from single-purpose AI tools (like chatbots or static reports) to AI agents — autonomous, multi-step assistants that can act across apps. These agents can qualify leads, draft and send follow-up emails, update CRMs, and even generate weekly sales reports without a human triggering every step.

Quick summary – What’s happening: Open-source agent frameworks (think LangChain, LlamaIndex, AutoGen and similar toolkits) have matured. They make it practical for companies to build custom AI agents that read your data, act on workflows, and plug into tools like CRMs, calendars and BI systems. – Why it matters for business: These agents can automate

Quick summary AI “agents” — autonomous software that reads your systems, takes actions, and follows up — have moved from lab demos into real business use. Major cloud providers and startups are investing in agent platforms that connect to email, calendars, CRMs, and reporting tools so AI can do work like qualifying leads, routing tickets,

Story summary A new wave of low-code “AI agent” platforms makes it faster and cheaper for non-technical teams to build autonomous assistants that do real work — from qualifying leads and updating a CRM to generating weekly sales reports and triggering follow-ups. These builders combine large language models, retrieval-augmented search (RAG), and simple connectors to

The story in one line Autonomous AI agents — software that can plan, act, and carry out multi-step tasks across apps — have moved from research demos to real business tools. From open-source agent projects to vendor “copilot” offerings, these systems are now practical for automating workflows, generating reports, and helping sales reps do more

Quick take AI agents — autonomous systems that can complete tasks, coordinate across apps, and act on behalf of users — went from “cool demo” to practical tool for sales, ops, and reporting. Companies are using them to qualify leads, automate follow-ups, generate management reports, and speed up back‑office processes. That shift matters because it