Ron Mitchell

Short summary AI “agents” — software that plans, acts, and uses tools (CRMs, calendars, analytics) on your behalf — moved in 2024 from experimental projects into real, deployable business tools. Open-source frameworks and cloud vendor toolkits made it easier to build agents that can qualify leads, book meetings, generate reports, and trigger downstream automations. Why […]

Quick summary – Over the past year we’ve moved beyond “chat with an LLM” to AI agents — systems that can act autonomously: call APIs, query databases, run workflows, and follow multi-step instructions. – Tooling (agent frameworks like LangChain/AutoGen and more flexible models from major providers) has matured enough that companies are shipping agentic automation

Quick summary A new wave of AI agents — autonomous assistants that read your systems, take actions, and generate reports — is moving from labs into the workplace. These agents can connect to CRM, ERP, calendars, email and document stores to do things like qualify leads, update deal stages, auto‑prepare weekly sales reports, route support

Quick summary – In the last 18–24 months AI “agents” — software that can act across apps, synthesize data, and take multi-step actions — have moved from demos to real business pilots. – Instead of just answering questions, these agents can draft outreach, update CRM records, generate weekly reports, and coordinate tasks across email, calendars

Short summary AI agents — small, goal-driven AI programs that can plan, act, and coordinate tasks — are moving from demos to real business work. Teams are using agents to automate repetitive workflows (like lead follow-up and expense triage), produce routine reports, and stitch together systems without heavy engineering. That means faster cycles, lower operational

Quick summary AI “agents” — autonomous workflows powered by large language models — have gone from niche demos to reliable tools businesses are adopting for real work: qualifying leads, routing customer requests, running multi-step reports, and automating follow-ups. Major platform updates and new orchestration tools have made agents easier to build, connect to CRMs, and

Quick summary Major AI vendors have spent the last year making it easier to build task-specific AI agents — think automated assistants that can read your inbox, pull CRM data, draft outreach, update records, and generate reports. New tools and APIs (from leading providers across the market) let businesses create these agents without rebuilding everything

Short summary AI agents — software that can act autonomously across apps, data, and workflows — have moved from demos to real business use. Companies are now wiring agents into CRMs, ERPs, help desks, and BI tools so the AI can read data, take actions, and generate answers or reports without constant human hand-holding. Why

Quick summary AI agents — the configurable, task-oriented bots built on large language models — are now moving from the lab into everyday business tools. Major vendors (OpenAI’s custom GPTs, Microsoft Copilot in 365, and Google’s agent features) are making it easier for teams to create agents that draft emails, summarize meetings, generate sales outreach,

Quick summary – What’s happening: AI agents — customizable, task-focused AI that can act across apps and systems — are moving from experiments into real business use. Teams can now build or buy agents that qualify leads, pull and explain sales forecasts, automate repetitive workflows, and triage customer requests. – Why it matters for business: