AI Post

Summary AI agents — autonomous, multi-step AI assistants that can research, act, and report — went from developer experiments to practical business tools over the past year. Major platform vendors and low-code vendors made building and connecting agents much easier, and companies are now using them for lead research, automated outreach, ticket triage, and real-time […]

Quick summary Over the past year major vendors (OpenAI, Microsoft, Google and others) pushed AI agents from demos into production-ready features — think custom GPTs, Copilot actions, and agent APIs that can read your systems, take actions, and follow multi-step workflows. These aren’t just chatbots: they can fetch CRM data, draft proposals, run reports, and

Quick summary AI “agents” — autonomous workflows built from large language models plus tools (CRMs, calendars, databases, email) — are no longer just lab experiments. More companies are using agents to run repetitive sales tasks, generate on-demand reports, and automate follow-ups. That means faster responses to customers, fewer manual reports, and more time for your

Short summary 2024 brought a big shift: AI agents — purpose-built assistants that combine large language models with tools, data connectors, and simple workflows — moved from research demos into real business use. Major cloud vendors and a wave of low-code platforms made it easier to build agents that can read your CRM, pull from

Quick summary AI agents — software that can act autonomously across apps and data — are moving from experiments into everyday business use. Modern agents can read your CRM, draft personalized outreach, update records, trigger follow-up tasks, and create live reports without constant human direction. Combined with secure data connectors and retrieval-augmented generation (RAG —

Quick summary AI agents — autonomous, task-focused AI that can read systems, take multi-step actions, and learn from outcomes — are moving from labs into the day-to-day of sales, operations, and reporting. Instead of a person copy-pasting between screens, these agents can qualify leads, generate tailored proposals, update CRMs, and assemble executive reports automatically. Why

Quick summary Big software vendors and startups are no longer just talking about “AI agents” as experiments. Over the past year we’ve seen AI agents rolled into productivity suites, CRMs, and reporting tools so they can complete end-to-end tasks — for example: qualify leads, summarize meetings, generate and distribute sales reports, and trigger downstream automations.

Summary AI agents — autonomous software that can plan, act, and follow up on tasks using LLMs, retrieval systems, and automation — are moving from lab experiments into real business workflows. Frameworks and tools like LangChain, AutoGen, and commercial offerings (e.g., Copilot-style agents) make it faster to build agents that handle things like customer follow-ups,

Quick summary AI “agents” — autonomous assistants that connect to your systems, take actions, and run multi-step workflows — have moved from labs into real business use. Instead of only answering questions, agents now book meetings, create and send personalized sales outreach, assemble monthly reports, and trigger approvals across CRM, ERP, and ticketing systems. Why

Quick summary AI agents — autonomous, multi-step AI programs that can access apps, APIs, and data — moved fast from demos into real business use in 2024. Major cloud providers and startups released agent platforms and frameworks that make it easier to build assistants that research prospects, draft outreach, update CRMs, and generate BI-ready reports