Ron Mitchell

Why this story matters – Over the past year, AI “agents” — systems that act on your behalf across apps and data — have moved from flashy demos to real business pilots. – Vendors and startups are building agents that can read CRM records, draft and send outreach, update pipelines, generate executive reports, and trigger […]

Quick summary AI “agents” — software that acts autonomously to complete tasks, orchestrate tools, and make decisions — went from research demos to real business pilots in 2023–24. Tools and frameworks (Auto-GPT, LangChain, vendor copilots) make it easier to automate multi-step work: routing customer issues, generating recurring reports, running prospect outreach, and syncing data across

AI story (short): Over the past year we’ve seen a clear shift: autonomous AI agents — systems that can act on behalf of users across apps and processes — are moving out of labs and into daily operations. Companies are using them to draft personalized sales outreach, triage customer requests, update CRMs, and generate recurring

Autonomous AI agents — short summary – What this trend is: AI agents are software that combine large language models with tools, APIs, and automation so they can perform multi-step tasks with little human prompting. Think: an agent that reads CRM data, drafts outreach, schedules meetings, and updates records — all on its own. –

Quick summary OpenAI’s move to make custom GPTs and assistant APIs easy to build and deploy has pushed AI agents from experiments into real business projects. Companies are now creating tailored agents that draft sales outreach, generate automated reports, triage customer tickets, and connect live to CRM and internal knowledge — without years of engineering

Quick summary – Over the past year, low‑code agent platforms and better connectors have made autonomous AI agents practical for everyday business tasks. – Companies are piloting agents that qualify leads, update CRMs, generate weekly performance reports, and triage customer requests — not to replace people, but to remove repetitive, time‑consuming work. – The result:

What’s happening AI agents — autonomous assistants that can read data, take actions across systems, and talk to people — are moving fast from experiments into real business workflows. Companies are now using agents to qualify leads, populate CRMs, generate and distribute reports, and automate routine approvals. The result: faster decisions, fewer manual errors, and

Quick summary AI “agents” — systems that combine large language models with tools, data access, and automation — moved from proof-of-concept to real business use in 2024. Companies are no longer just using chatbots for information; they’re building agents that research leads, enrich CRM records, draft proposals, automate follow-ups, and produce recurring reports. Why this

Short summary AI “agents” — autonomous, multi-step software assistants that can read, decide, act, and report — have moved from proofs-of-concept into real business deployments. Over the last year vendors and open-source tools made it easier to build agents that connect to CRMs, calendars, email, and databases. That means companies can automate whole workflows (e.g.,

Quick summary – The big story today: AI agents — autonomous, task-focused AI that can read systems, take actions, and follow up — are finally maturing into reliable business tools. Improved models, better retrieval (RAG + vector stores), and agent frameworks mean companies are no longer just experimenting — they’re putting agents into real workflows