Ron Mitchell

Quick summary AI agents — autonomous software that can chain together tasks, use tools, and act on behalf of users — are moving from experiments into real business use. Companies are now piloting agents to manage parts of the sales cycle (researching leads, drafting outreach, scheduling meetings), automate recurring workflows, and generate up-to-date reports that […]

Summary AI agents — software that uses large language models to perform multi-step tasks autonomously — are no longer just a developer novelty. Over the last 18 months we’ve seen more low‑code agent platforms, tighter integrations with CRMs and data warehouses, and practical use cases that matter to business teams: automated sales outreach, invoice triage,

Quick summary AI agents — software that can act on your behalf, coordinate tasks, and pull data from systems — have moved from experimental demos to practical tools. Major vendors and new no-code platforms now let teams build agents that automate workflows, run reporting, and even manage parts of customer outreach. At the same time,

The story (short): Over the past year the big shift in business AI has been from point tools to autonomous, workplace-ready “AI agents” — connected systems that combine large language models with data access, retrieval (RAG), and workflow automation. Instead of asking an LLM a question and copying the answer, companies are building agents that

Quick summary Big cloud and AI vendors moved from experiments to production in 2024: custom AI agents (think GPTs, Copilot-style copilots, and vendor agent platforms) plus richer connectors and function-calling made it practical to automate real business workflows — not just chat. That means AI can now run parts of sales processes, generate and update

Quick summary AI agents — software that can act on behalf of users to complete tasks, make decisions, and talk to other systems — are no longer a novelty. Over the past year we’ve seen a wave of platforms and integrations that make it easier to plug autonomous agents into everyday business systems (CRM, ticketing,

Story summary The last two years have pushed AI agents — small, purpose-built systems that complete tasks end-to-end — out of labs and into real business use. Major cloud vendors and a vibrant startup ecosystem now make it straightforward to deploy agents that qualify leads, draft proposals, update CRM records, generate executive reports, and even

Quick summary AI agents — software that can act autonomously across tools (schedule meetings, qualify leads, update CRMs, draft proposals, generate reports) — have moved from experiments into business-grade pilots. A new wave of agent platforms pairs retrieval-augmented generation (RAG), real-time data connectors, and orchestration engines so agents can work across your systems with less

Quick summary AI “agents” — systems that can act across apps, fetch data, and complete multi-step tasks — stopped being a niche experiment in 2024 and are now showing up in mainstream products (think Copilot-style features, generative models with plugins/connectors, and platform-level assistants). That means businesses can automate not just single tasks, but whole mini-processes:

Quick summary Major cloud vendors and AI toolmakers have moved AI “agents” from research demos to supported business tools. Today you can use ready-made agent frameworks and low-code platforms to build assistants that do specific jobs — for example, draft sales outreach, triage customer tickets, generate weekly performance reports, or run reconciliations across systems —