Ron Mitchell

Quick summary Autonomous AI agents—software that can plan, act, and follow up on tasks without constant human prompting—are moving from experiments into real business use. Companies are using agents to automate routine sales outreach, generate timely reports, triage customer issues, and coordinate multi-step workflows across systems. That shift is driven by better language models, cheaper […]

Story summary AI agents — autonomous software that can read, reason, and act across apps — are moving from lab demos into real business use. Companies are now using agents to qualify leads, run follow-up emails, compile weekly reports, and trigger workflows across CRM and finance systems. Advances in large language models, retrieval-augmented generation (RAG),

Story summary In the past year major vendors made it much easier for businesses to build custom AI assistants and agents. Low-code platforms and “assistant builders” from providers like OpenAI, Microsoft and Anthropic let teams create task-specific agents that connect to company data, run workflows, and answer questions in plain language — without hiring a

Short summary AI “agents” — autonomous software that can carry out tasks end-to-end (think: enrich leads, draft outreach, schedule meetings, build weekly reports) — are no longer just research demos. Over the last year businesses of all sizes have started running agents in production to automate repetitive sales and operations workflows, speed up reporting, and

Short summary AI “agents” — software that acts on your behalf using language models, data, and integrations — moved this year from tech demos into real business use. Companies are now connecting agents to CRMs, calendars, email, and internal docs so the agents can draft outreach, update pipeline stages, run routine reporting, and nudge reps

Quick summary AI agents — software that can act autonomously by combining language models, data retrieval, and automation tools — are moving from demos into real business use. Companies are using agents to qualify leads, update CRMs, generate weekly performance reports, and run routine customer follow-ups without manual input. That means faster work, fewer human

Summary Autonomous AI agents — software that can plan, act, and carry out tasks across apps — are no longer just experiments. Over the past year we’ve seen major vendors (Copilot-style assistants, multimodal models) and dozens of startups deliver agent-building tools and orchestration platforms that let businesses automate complex workflows: prospect research, proposal drafting, customer

Story summary AI agents — software that can take multi-step actions, talk to systems, and run tasks with little human prompting — moved from demos to day-to-day business use in 2023–24. Tooling like LangChain-style agent frameworks, no-code automation platforms adding AI, and enterprise assistants from major cloud vendors made it easier to connect agents to

Big story in plain terms This year, enterprise-grade AI agents moved from demos into real business tools. Vendors and startups are shipping agents that can securely connect to calendars, CRMs, ERPs and databases, carry out multi-step tasks (like scheduling, quoting, or closing simple support tickets), and produce automated reports that pull from live systems. In

Story pick (quick context) Over the past year, a new wave of “agentic” AI tools has moved from demos into real business use. These AI agents can read and write across multiple apps — sending outreach, updating CRM records, running queries, and producing reports — without a human clicking each step. Big vendors and startups