Quick summary AI agents — autonomous systems that combine generative models with connectors and business rules — are moving out of limited experiments and into real company workflows. Major vendors have rolled out copilots and tool-enabled models, and open frameworks make it easier for teams to build agents that research, triage, schedule, update CRMs, and […]

Quick summary AI “agents” — autonomous or semi-autonomous AI tools that can read, act, and orchestrate across apps — have moved from experiments to real business tools. In the past year we’ve seen major platforms and startups add agent frameworks, low-code builders, and prebuilt integrations that make it practical to automate workflows that used to

Quick summary AI agents — small, goal-oriented AI systems that can act across apps and data — are moving from prototypes into real business use. Advances in retrieval-augmented generation (RAG), secure connectors to CRMs and cloud storage, and better orchestration frameworks mean these agents can now complete multi-step tasks: qualify leads, update records, compile reports,

What’s happening Major cloud vendors and startups are rolling out no-code / low-code tools that let companies build AI agents — software that can read your systems, take actions, and carry out multi-step tasks (think: generate a sales forecast, pull CRM data, and email a follow-up). These agents combine large language models, retrieval systems, and

Story summary AI agents — autonomous tools that can speak, act on apps, and fetch answers from your data — are no longer just a curiosity. Over the last 12–18 months we’ve seen more companies move from pilot projects to production use of AI agents for tasks like lead qualification, meeting scheduling, automated reporting, and

Quick summary AI “agents” are software that can carry out multi-step tasks for you — they read data, call apps (CRM, calendar, ticketing), and take actions with minimal human prompts. Over the past year we’ve seen faster, cheaper models, better connectors, and mature orchestration tools that make these agents reliable enough for real business use.

Hook: In 2024 we moved from “chatbots” to true AI agents — customizable assistants that connect to your apps, act on data, and run tasks end-to-end. That shift is now changing how sales and operations work. The story, in plain terms – Big AI platforms (think custom GPTs, agent frameworks like LangChain and AutoGPT, and

The story in one sentence Autonomous AI agents — software that can use tools, follow multi-step workflows, and act on your behalf — have moved from research demos to production-ready options across enterprise platforms and open-source frameworks. Why this matters for business – These agents don’t just generate text; they can run searches, call APIs,

AI agents — software that can act, decide, and carry out tasks across apps — are moving from experiments to real business use. Companies are using them to qualify leads, automate routine reporting, handle first-line customer requests, and run repeatable process steps without constant human intervention. Why it matters for your business – Faster cycles:

Quick summary Over the past year major AI platforms have pushed “agent” features — autonomous, multi-step AI assistants that can read internal data, call APIs, and take actions across tools. In plain terms: instead of asking an AI a single question, you can give it a goal (e.g., “find qualified leads, draft outreach, and schedule