AI Agents for Completing Online Tasks

If AI in your company still lives inside chat windows… you haven’t started the Agentic journey yet. Today’s Agentic AI systems don’t just answer questions. They observe signals, make decisions, trigger tools, coordinate workflows, and continuously improve outcomes. Instead of assisting humans one task at a time, these agents run end-to-end business operations across sales, support, finance, engineering, HR, and marketing. This is what production-grade Agentic AI actually looks like inside modern organizations: - Customer Support Agents Handle FAQs, resolve tickets, process refunds, update CRM systems, and escalate complex issues automatically. - Sales Ops Agents Qualify incoming leads, enrich prospect data, update pipelines, generate follow-ups, and notify sales teams in real time. - Marketing Automation Agents Plan campaigns, analyze audiences, generate content, schedule outreach, track performance, and optimize future runs. - Data Analysis Agents Convert business questions into SQL, clean datasets, analyze trends, generate insights, and deliver visual summaries. - Reporting Agents Pull metrics, validate data, create dashboards, write narratives, and distribute reports across stakeholders automatically. - QA / Testing Agents Generate test cases, execute regressions, detect failures, log bugs, and recommend fixes without manual intervention. - DevOps Agents Monitor infrastructure, detect anomalies, run diagnostics, apply rollbacks, notify teams, and assist deployments. - Finance Ops Agents Process invoices, categorize transactions, reconcile records, flag anomalies, and generate financial summaries. - HR Ops Agents Manage resume intake, screen candidates, schedule interviews, update HR systems, and respond to employee queries. - Research Agents Search documents and web sources, extract key findings, compare references, and summarize insights. - Content Creation Agents Outline topics, draft content, optimize for SEO and branding, publish assets, and track engagement end-to-end. - Internal Tools Agents Act as company copilots - understanding employee requests, calling internal APIs, executing actions, and confirming results. The real shift? These agents don’t just respond. They reason. They orchestrate tools. They execute workflows. They learn from feedback. They operate continuously. This is how organizations move from isolated automation to connected, outcome-driven AI systems. Not experiments. Not demos. Not pilots. Real production systems.

I asked an AI agent to organize 6 months of messy files on my computer. It renamed 247 files, sorted them into 12 folders, flagged 18 duplicates, and deleted nothing without asking me first. Took 4 minutes. Would've taken me an entire afternoon. That's the difference between a chatbot and an AI agent. Let me break it down simply: 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐚𝐧 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭? Think of it this way: A chatbot is like texting a smart friend. You ask a question. They answer. Conversation over. An agent is like hiring a freelancer. You give them a goal. They figure out the steps, use the tools they need, and come back with the finished work. You don't tell them "open Google Docs, then click File, then..." You say: "Write me a project brief and put it in my Drive." They handle the rest. 𝐇𝐨𝐰 𝐀𝐠𝐞𝐧𝐭𝐬 𝐀𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐖𝐨𝐫𝐤 Every agent runs the same 4-step loop: 𝟏. 𝐏𝐞𝐫𝐜𝐞𝐢𝐯𝐞 Look at the task, read relevant files, understand the context. 𝟐. 𝐏𝐥𝐚𝐧 Break it into steps. Decide which tools to use. 𝟑. 𝐀𝐜𝐭 Execute. Write code, call APIs, edit files, browse the web. 𝟒. 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐞 Did it work? If not, try a different approach. This cycle repeats until the job is done. Or until it hits something it needs your input on. 𝟑 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐀𝐠𝐞𝐧𝐭𝐬 𝐖𝐨𝐫𝐭𝐡 𝐊𝐧𝐨𝐰𝐢𝐧𝐠 𝟏. 𝐂𝐨𝐝𝐢𝐧𝐠 𝐀𝐠𝐞𝐧𝐭𝐬 You describe what you want built. They write the code, test it, fix bugs, commit to Git. → Claude Code, Cursor, Devin 𝟐. 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐀𝐠𝐞𝐧𝐭𝐬 You point them at your files and data. They organize, analyze, summarize, and create reports. → Claude Cowork, Microsoft Copilot 𝟑. 𝐁𝐫𝐨𝐰𝐬𝐞𝐫 𝐀𝐠𝐞𝐧𝐭𝐬 You tell them what to do on a website. They navigate, click, fill forms, extract data. → Claude Computer Use, OpenClaw 𝐇𝐞𝐫𝐞'𝐬 𝐰𝐡𝐚𝐭 𝐩𝐞𝐨𝐩𝐥𝐞 𝐚𝐫𝐞 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐮𝐬𝐢𝐧𝐠 𝐭𝐡𝐞𝐦 𝐟𝐨𝐫: → "Analyze Q3 sales data and build me a presentation" Agent reads the CSV, finds insights, creates the slides. → "Every Monday morning, pull my dashboard metrics and post a summary to Slack" Agent runs on schedule. Zero human involvement. → "Research 5 competitors in our space and write a comparison doc" Agent searches the web, reads their sites, writes the report. The mental model shift: Chatbot = You drive. AI assists. Agent = You set the destination. AI drives. We're at the very beginning of this. But if you're not experimenting with agents today, you'll be playing catch-up by the end of this year. Save this breakdown for later. ♻️ Repost if someone in your network needs to understand this. #ai #agent

Last week, posted a demo using Stripe Agent SDK to generate one-time payment links for failed invoices—all from a single natural language prompt. But here’s where it gets even more exciting: AI Agents change the interaction model from synchronous to asynchronous. Instead of waiting for an Agent to complete a task in real time, you can assign it a task and let it report back when finished — this opens up the idea of a "Digital Worker" that Marc Benioff has been talking about recently. This paradigm shift opens the door to proactive, automated workflows that happen seamlessly in the background. Building on the synchronous UX in the app, we enabled this Stripe Agent to go a step further—identifying failed payments on a schedule and creating tailored reconciliation reports. 🔑 Here’s how it works using OpenAI, Vercel AI SDK, and Stripe's Agent SDK the agent: ✅ Analyzes payment patterns across integrated platforms ✅ Creates tailored reconciliation products in Stripe ✅ Generates custom-priced payment links ✅ Delivers comprehensive reports with AI-driven recommendations to account managers over email From there, the Payment Ops team can review reports and act on the Agent’s recommendations directly from their email. For cases requiring human intervention, the management app provides an intuitive interface for manual actions. This is a prime example of how AI agents can transform financial operations—turning multi-step, manual processes into automated, intelligent workflows that save time and reduce friction. The future of Financial Operations isn’t just about automation—it’s about systems that understand context, make decisions, and take action seamlessly across your enterprise data.

OpenAI Launches ChatGPT Agent — A New Step in Business Automation OpenAI has officially launched ChatGPT Agent, an agentic model designed to complete multi-step, computer-based tasks on a user’s behalf. Unlike standard chat interactions, Agent mode can take real action: • Researching and summarizing content from the web • Running code in a secure virtual environment • Creating reports, spreadsheets, and slide decks • Accessing and navigating websites, prompting for logins • Pulling in data from external apps and APIs • Providing meeting briefings using calendar and context Examples shared by OpenAI include analyzing competitors and generating a presentation, planning and shopping for a meal, and summarizing news related to upcoming meetings. Agent runs on a virtual machine — allowing it to reason, take action, and adjust mid-task based on your input. It also asks for permission before making any significant changes and allows you to pause or stop tasks at any time. Rollout details: • Pro users gain access immediately (400 messages/month) • Plus and Team users will receive access in the coming days (40 messages/month) • Enterprise and Education access is planned in the near term • Additional usage will be available via flexible credits This is a practical shift. It’s not just about prompting responses — it’s about assigning tasks and letting AI handle them in the background. For business leaders, consultants, and anyone managing operational complexity, the implications are worth watching. Especially as we all look for ways to reduce friction, accelerate research, and make better decisions faster. I’ll be exploring this closely. If you’re curious how it could support your team or workflow, happy to compare notes. #OpenAI #ChatGPTAgent #AItools #BusinessProductivity #EnterpriseAI #FutureOfWork #ProcessAutomation ChatGPT OpenAI Microsoft Apple MacDailyNews Webmaster The Wall Street Journal Financial Times Accenture Tribune Media Chicago Tribune Crain's Chicago Business

OpenAI has introduced a new kind of digital worker: ChatGPT Agent. Designed to go beyond conversational AI and deliver actual task execution, the Agent blends the experimental Operator feature (which could take actions online like placing orders or submitting forms) with the Deep Research feature (which ran multi-step queries to produce longform output). By combining the two, OpenAI has created a more functional, safety-aware AI that performs not just analysis but action. Currently rolling out to Pro, Plus, and Team-tier users, the ChatGPT Agent enables advanced workflows like generating research reports, booking appointments, processing documents, writing code, and even manipulating virtual terminal sessions. In essence, it behaves like a virtual computer that runs inside ChatGPT, giving users access to a browser, file system, terminal, and runtime environment. According to OpenAI, the Agent is designed to handle “multi-step tasks” and is trained with new reinforcement learning strategies. Its default behavior includes asking permission before taking irreversible actions, such as submitting a purchase or deleting a file. When the stakes are especially high—such as financial transactions or sensitive research—it defaults to Watch Mode, a safety layer that requires more explicit user approval. https://lnkd.in/ekfi3Jnb

🚨 BREAKING: OpenAI just dropped a research preview of their internet AI agent. I was an early tester of the product and want to share my thoughts. Let’s break down what it is, my views, why it matters, and what to do/expect. ↓ ↓ ↓ WHAT: ChatGPT now lets you delegate internet tasks to it. You tell it what to do, and it will navigate the internet for you to get the answer and help take action—for example, you ask it to find you an Airbnb in Houston for under $500 a night that fits 8 people. MY THOUGHTS: it’s not AGI, but it’s a step toward more autonomous systems. The Operator UI is sleeker than Anthropic Claude Computer Use. I like that it punts it back to the user for logins and payments for security (without watching the user), but navigation and typing is slow. I had several times where the website detected it was an AI and blocked it (definitely monitor your first few searches). OpenAI may be using Operator to inform their AI agent strategy. It may be the first AI agent that’s really accessible to non-devs (no API integrations required!) Works well across use cases like travel, dining, and shopping. For research, I still recommend Google Gemini with Deep Research. WHY IT MATTERS: 2025 is the year of agentic AI. OpenAI, Anthropic, Google and Microsoft have all revealed their early AI agent bets, and this is just a 4o class model. The UX of watching an AI click around is not fun and often painful. But hopefully its accessibility can help people understand what working with hundreds of AI agents may look like. WHAT TO DO: if you have pro mode, give it a real test drive. After two years of gen AI, I've seen how hands-on testing gives you 10x better results and 100x clearer vision of where this is headed. Seriously. Test it: operator.chatgpt.com ↓ ↓ ↓ If you want to immediately watch my introduction to AI agents webinar so you’re ready for 2025, watch it for free here: https://lnkd.in/dttywPU2

Two types of AI agents for two types of tasks: 1) Information processing Output: Text, eg reports or software code. Capabilities: Performs complex analysis and writes these up in natural language or code. Tasks can involve problem definition, literature review, data analysis, ... Level of development: Already very good and still improving quickly. Options include Deep Research products by OpenAI, Google, Perplexity. Likely impact: Will revolutionize many knowledge work tasks, eg in financial services, consulting, legal, or academia. Will put pressure on many job types but will foster innovation. 2) Decision delegation Output: Decisions, eg purchases. Capabilities: Matches decision criteria to decision options (eg marketplace offerings), makes assessments (eg tradeoffs), implements decisions (eg booking a holiday). Level of development: Still early days. Available products like OpenAI Operator show glimpse of the future but widespread adoption is still not around the corner. Difficult problem also because the web is made for humans (ie graphical user interface), not machines. Likely impact: Pressure on many job categories (especially when tailored to decisions within orgs). Major impact on marketing/branding (the consumer will still be a person but the customer will be an algorithm).

In 2025, your next promotion could be by an AI agent, not your boss. This new agent is here to disrupt everything you thought you knew about work. OpenAI has rolled out Operator, its first true AI agent, to Pro users across India and eight other countries. What sets Operator apart from typical AI assistants is its ability to do tasks. Unlike Siri or Alexa, it can navigate websites, analyze content, and interact with your screen like a human. It sees pixels, recognizes buttons, menus, and text, and executes actions seamlessly. Here’s what it can do: → Order groceries from recipe images → Schedule appointments by checking calendars → Plan trips by analyzing online recommendations → Fill out forms and create content It doesn't need special access to websites. It simply "sees" the screen and interacts with it just as you would, saving time and mental effort for more creative tasks. For example, imagine uploading a recipe photo, and Operator automatically ordering the ingredients for you. Or using it to schedule all your meetings without you lifting a finger. This is AI that doesn’t just assist, it works alongside you. I think AI is transforming the way we work, and soon, the question won’t be if you’ll use it, but how you’ll use it. With AI agents like Operator, businesses can optimize workflows, and individuals can focus more on high-level tasks while leaving the mundane to AI. However, as with any new technology, there are considerations. Giving an AI control over your screen requires significant trust, and businesses must weigh the potential privacy concerns before fully adopting such tools. What's the first task you'd delegate to an AI agent? #Automation #Productivity #Innovation #AI

Understanding ChatGPT Agents: AI that acts, not just chats. ChatGPT’s new Agent mode is more than a chatbot. It can browse websites, log in, run code, and create files. You see every step, approve actions, or take over anytime. That means AI can handle research, reports, and repetitive workflows. The key difference? It doesn’t just suggest, it actually executes. For marketers, analysts, and operators, this can save hours every week. It’s a shift from AI as a helper to AI as a teammate. What task would you trust an AI Agent to handle?