We now live in a world where we can send emails, set reminders, book flight tickets, and do a lot more through simple text prompts. With AI chatbot genies trained to believe ‘Your prompt is my command’, all you have to do is type out your wish. And voila! The agent will get it done for you automatically! It’s true, now AI chatbots like ChatGPT with Scheduled Tasks and Operator, and Claude with its Computer Use feature, can do task automation without the need for separate AI agents. Does this mean we no longer need dedicated AI agent building tools? Does this mark the downfall of agentic AI platforms like LangGraph, AutoGen, and CrewAI? Let’s find out.
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AI Agentic Tasks Across Platforms: ChatGPT, Claude, and Beyond
AI-powered chatbots and virtual assistants are now developing agentic features, making our lives a lot easier. Thanks to these developments, we no longer require task-specific agents for simple tasks like scheduling, setting reminders, receiving updates, creating content, etc. Let’s get to know the agentic features offered on different AI platforms and what they can do.
ChatGPT’s Operator and Task Scheduling Features
ChatGPT has recently introduced two new features – Scheduled Tasks and Operator taking a great step towards agentic AI. These tools can automatically send you updates, search the web, make bookings, and a lot more. Let me explain.
- Task Scheduling: This enables ChatGPT to automate recurring or future tasks by trigger pre-set actions at a specified time. For instance, it can remind you about an upcoming event or meeting, or send you news bulletins every morning, once you set it up with a single prompt.
- Operator Feature: This new feature enables ChatGPT to execute everyday tasks by making specific API calls and interacting with third-party tools directly. This lets users book flights, send emails, generate reports, make appointments, and more, by just telling ChatGPT what to do.
Know More: OpenAI Operator – ChatGPT Like Moment for AI Agents
Agentic Features on Other Platforms
Apart from ChatGPT, a few other platforms have also developed task automation and agentic features. Let’s have a look at some of them.
1. Claude 3.5
The Computer Use feature on Claude 3.5 gives it the ability to access and manage computer files, locally. Users can give the AI chatbot access to their personal systems, and it can autonomously type on screen, create files, run scripts, and execute workflows, based on input prompts. This makes it more of an agentic virtual assistant for both personal and business use.
Learn More: Exploring the Latest Features of Claude 3.5 and What We Can Do With Them
2. Google AI Studio and Gemini Chatbot
Google AI Studio and its Gemini chatbot focus on integrating task automation within Google Workspace. Gemini can pull data from Google Sheets, automate emails, and even manage calendar events and send reminders. Moreover, its advanced multi-modal capabilities further enhance its agentic potential.
3. Copilot Tools
Copilot tools such as GitHub Copilot and Microsoft Copilot automate specific tasks within their domains and ecosystems. These AI assistants excel in domain-specific expertise such as code generation and document editing.
4. Meta AI Chatbot
Meta’s chatbot, Meta AI, is gradually incorporating agentic features, including task scheduling and social media management. While still evolving, Meta’s focus on integrating its chatbot with platforms like Instagram and Facebook is surely a step towards social media automation.
All of these features transform tools like ChatGPT, Claude, and MetaAI from passive conversational AI chatbots into active, goal-oriented AI agents. Moreover, they embed agentic AI into our everyday life without requiring separate agents, reducing our dependency on agent-building tools.
Also Read: 5 Real-Life Use Cases of AI Agents for Day-to-Day Work
Would We Still Need Agent Building Platforms?
Well, the answer is yes… for now. While AI chatbots have now gotten into task automation, it’s just a small step. There’s a lot more that we can do with agents built on platforms such as LangGraph, AutoGen, or CrewAI.
We still need agent-building tools and platforms for:
- Complex, Enterprise-grade Workflows: Full-fledged agent building platforms have the technological framework to build agents that can automate complex tasks and workflows. This cannot be done by AI chatbots, as of now.
- Integration with Current Systems: Enterprises mostly need agents that integrate with their company databases, CRMs, or ERPs. Platforms like LangGraph and CrewAI provide the flexibility to build custom agents that can integrate with existing systems.
- Training on Custom Data: Organizations often require the agents to be trained on proprietary datasets, tailored to their unique workflows. Agent-building platforms provide a more secure and functional space for building and training agents on custom data.
- Specialized AI Agents: Tools like AutoGen, LangGraph, and CrewAI enable the development of deeply specialized agents (e.g., legal advisors, medical assistants) tailored to specific industries. The tasks performed by these agents are not simple enough to be performed by chatbots.
- Multi-agent Orchestration: Most enterprise workflows require more than one agent to work together in order to get the task done. Such multi-agent frameworks and systems can only be built on full-fledged platforms like Microsoft Orchestrator.
- Benefits of Open Source Platforms: Open-source agent building platforms such as Rasa, AutoGPT, and LangGraph offer unmatched flexibility and control. They allow developers to customize agents, build on existing frameworks, and adapt solutions to meet unique organizational needs. Open-source platforms also encourage innovation and provide cost-effective alternatives to proprietary chatbots like ChatGPT.
The Future of Agentic AI
With the integration of agentic features on AI chatbots, here are some key trends we believe would shape the future of Agentic AI.
- Unified Conversational and Agentic Platforms: AI chatbots will increasingly combine conversational abilities with autonomous task execution in the times to come. This would reduce the need for separate tools and platforms for agent building. It may also eliminate the need for separate agents for different tasks.
- Competition and Consolidation: We now have too many platforms offering similar services (e.g., Smallagents, LangGraph, AutoGen). In the future, some of these will fade away or be bought by bigger companies, resulting in having just a handful of AI agent building tools.
- Reduced Complexity: While no-code tools simplify agent-building, designing effective workflows and maintaining control still requires expertise. Going forward, agent building will be further simplified, making it more accessible to everybody, even for creating complex agents.
- Privacy and Security: As AI agents gain more autonomy and deeper integration into our systems, the risks of misuse or breaches would increase. There will have to be strict protocols in place to control how much access is given to these agents into personal files and secure data.
Also Read: Top 10 AI Agent Trends and Predictions for 2025
Conclusion
ChatGPT’s Operator and Task Scheduling features mark a significant step toward making agentic AI accessible to all. Similar agentic features in Claude and other AI platforms are also potentially reducing the need for standalone agent-building tools.
While they challenge traditional agent-building platforms in certain areas, tools like AutoGen, CrewAI, and LangGraph remain indispensable for complex and enterprise-grade automation. The future lies in a hybrid ecosystem where general-purpose chatbots and specialized agentic platforms coexist, offering users the best of both worlds.
Frequently Asked Questions
Q1. What are ChatGPT’s Operator and Scheduled Task features?
A. ChatGPT’s Operator feature allows the AI to execute real-world tasks by making API calls and interacting with third-party tools directly. The Scheduled Task feature enables users to automate recurring tasks, like reminders or sending updates, by setting up specific triggers for future execution.
Q2. How do AI chatbots like ChatGPT and Claude compare to agent-building platforms?
A. AI chatbots are great for automating simple tasks through conversational prompts. However, agent-building platforms like LangGraph, AutoGen, and CrewAI specialize in creating complex, industry-specific agents with multi-agent orchestration and system integrations, which AI chatbots currently cannot match.
Q3. Can AI chatbots completely replace agent-building platforms?
A. No, AI chatbots are making strides in task automation, but they primarily focus on basic tasks. Agent-building platforms remain crucial for enterprise workflows, custom data training, and creating specialized agents tailored to specific industries.
Q4. What are some no-code tools for building AI agents?
A. No-code tools like AutoGen, CrewAI, LangGraph, and Microsoft Azure AI Studio enable users to build agents with drag-and-drop interfaces and customizable templates. While chatbots automate simple tasks, these platforms excel in creating scalable and enterprise-grade solutions.
Q5. What are the key benefits of open-source agent-building platforms?
A. Open-source platforms like Rasa, LangGraph, and AutoGPT offer unmatched flexibility, allowing developers to modify frameworks, integrate custom datasets, and innovate without vendor lock-in. They also provide cost-effective solutions for businesses looking to scale.
Q6. What does the future of agentic AI look like with the rise of chatbot platforms?
A. The future will likely see hybrid models where general-purpose chatbots handle everyday tasks, while specialized agent-building platforms address complex workflows. As chatbots integrate agentic features, the need for standalone tools may decrease. However, enterprise-grade platforms will remain essential for advanced automation.
Sabreena Basheer is an architect-turned-writer who's passionate about documenting anything that interests her. She's currently exploring the world of AI and Data Science as a Content Manager at Analytics Vidhya.
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