Ron Mitchell

What’s happening AI “agents” — autonomous, task-oriented AI that can access your data, take actions, and run multi-step workflows — have moved from demos into real business use. Instead of one-off chat responses, companies are building agents to handle end-to-end tasks like prospecting, scheduling, expense triage, and automated reporting. Vendors (think custom GPTs, Copilot-style integrations, […]

Quick summary AI agents are autonomous software that combine large language models, tool APIs, and business data to complete end-to-end tasks — from qualifying leads and generating customized proposals to producing automated sales and operations reports. Over the last year these agents moved out of research labs and into low-code platforms and enterprise copilots, making

Hook: AI agents — autonomous, goal‑oriented software that can read, act, and learn — moved from research demos into real business tools this year. If you haven’t evaluated them yet, you should. What happened (short summary) – Large AI vendors and open‑source toolkits have made it easy to build “agents” that can connect to your

Quick summary – The big AI platforms (notably OpenAI) have pushed “custom GPTs” and agent frameworks into the mainstream. These let companies build tailored AI agents — little virtual assistants that can access your data, follow workflows, and act with minimal human direction. – Businesses are already using them for sales support, lead qualification, customer

Short summary There’s a growing wave of AI agents — autonomous, task-focused AI that can read your systems, take actions, and run multi-step workflows without constant human prompts. Companies are already piloting agents for sales outreach, customer triage, automated reporting, and order processing. These agents combine language models with connectors to CRM, ticketing, BI, and

Story summary – In 2024 the biggest shift wasn’t a single new model — it was the rise of AI agents: autonomous, tool-enabled AI that can take multi-step actions (book meetings, pull reports, draft emails, trigger workflows) instead of just answering questions. – These agents are becoming easier to build and integrate thanks to cloud

Quick summary AI agents — autonomous, task-oriented AI assistants that can read files, query systems, and take actions across apps — have moved from demos to real business pilots. Companies are using them to draft outreach, qualify leads, automate reporting, and triage customer inquiries. The result: faster workflows, fewer manual handoffs, and clearer, AI-powered reporting

Quick summary AI “agents” — autonomous workflows that combine language models, tools, and company data to perform tasks — moved from demos to real business use in 2024–25. Vendors and startups now offer agent orchestration, built-in observability, and safety features so companies can run agents for sales outreach, customer support triage, order processing, and automated

Short summary AI “agents” — small, goal-directed systems built on large language models — moved from experiments to real business use in 2024. Tools and frameworks such as LangChain, Auto-GPT patterns and integrations into CRMs and reporting stacks let companies automate end-to-end tasks: lead enrichment, multi-step prospecting, automated reporting, and recurring process execution. Why this

Quick summary AI agents — autonomous software that can read, decide, and act across apps — are moving from labs into real business workflows. Instead of just generating text, modern agents can pull CRM records, qualify leads, run outreach sequences, update pipelines, generate executive reports, and trigger follow-up tasks without constant human supervision. Why this