Ron Mitchell

Quick summary AI agents — autonomous, multi-step AI tools that can search your systems, take actions, and follow up without constant human prompts — moved from demos into real business pilots in 2024–25. Vendors and cloud providers now offer agent frameworks that connect to CRMs, calendars, email, ticketing and databases. Real use cases already in […]

Quick story No-code and low-code AI agent platforms have moved from novelty to business-ready in the last 12–18 months. Tools from major cloud vendors and startups now let non‑engineers assemble “autonomous” agents that can read your CRM, draft outreach, schedule meetings, pull numbers from your data warehouse, and generate recurring reports — all with simple

Quick summary • Autonomous AI agents — software that can do multi-step tasks across apps with little human supervision — have moved from demos into real business pilots. • Teams are using agents for sales outreach, lead qualification, customer support triage, and automated reporting. These agents combine language models with connectors, retrieval (RAG), and simple

Story summary Over the last year the fastest-moving trend in enterprise AI has been the rise of practical, task-focused AI agents — small, automated assistants that connect to your CRM, ticketing systems, email, and internal reports. Instead of asking a lone chatbot questions, businesses are deploying agents that run workflows: summarize last week’s deals, draft

Quick summary A growing wave of AI agents — autonomous software that can read, decide, and act across systems — is making it easier for businesses to automate routine work. These agents can orchestrate multi-step tasks (pull data, draft an email, update CRM, generate a report), learn from outcomes, and run 24/7 without human supervision.

Quick summary AI has moved beyond “helpful suggestions.” The newest wave of AI agents can now execute multi-step tasks end-to-end: research prospects, draft and send personalized outreach, update CRMs, generate and distribute performance reports, and trigger follow-up actions — all with minimal human hand-holding. Improvements in model reasoning, secure connectors to enterprise systems, and low-code

Big idea (short): Over the last year, major AI and cloud vendors have made it much easier to build low‑code AI agents — autonomous workflows that can read your systems, take action, and produce human-ready outputs. That shift turns “experimental” pilots into practical tools for sales, operations, and reporting. Why this matters for business –

Quick summary AI “agents” — autonomous, task-focused AI assistants built from large language models — are no longer just experiments. Over the past 18–24 months platform providers (think custom GPTs, Copilot builders, low-code agent frameworks) made it easy for teams to stand up agents that handle real work: drafting personalized outreach, summarizing meetings, generating weekly

Quick take: AI agents — autonomous, task-focused AI that can read your data, use tools, and take multi-step actions — are moving from labs into real business use. They’re already saving time on outreach, lead qualification, scheduling, and routine reporting. For business leaders, that means faster decisions, lower operational cost, and more time for high-value

Short summary AI “agents” — autonomous systems that can research, write, execute multi-step tasks, and interact with apps — have crossed an important threshold. They’re no longer just experiments in R&D labs. Businesses are now using them to run repeatable sales tasks (lead research, outreach sequences, CRM updates) and to generate and automate regular reports.