DEV Community

Cover image for ChatGPT Gets Agentic Powers: What OpenAI’s New Automation Means for Everyone
Ritesh Kumar Sinha
Ritesh Kumar Sinha

Posted on

ChatGPT Gets Agentic Powers: What OpenAI’s New Automation Means for Everyone

Hey Devs 👋,

OpenAI just dropped a groundbreaking update to ChatGPT—and it’s not just conversational anymore. ChatGPT is now agentic, which means it can browse the web, take action, and execute tasks on your behalf.

As a senior software engineer, my first question wasn’t “Wow!”—it was “How does this actually work under the hood, and what can I build with it?”

Let’s break it down.


🔍 TL;DR — What’s New?

ChatGPT can now act like an autonomous agent with real-world access.

Reason & Act: Breaks down complex goals into actionable steps.

Web Access: Searches, clicks, scrapes, and navigates full web pages.

Autonomous Execution (with Guardrails): Executes workflows end-to-end with built-in safety checks.

Permission Controls: Explicitly asks before submitting sensitive data or performing impactful actions.

Currently Rolling Out: Available for ChatGPT Plus, Team, and Enterprise tiers.


⚙️ Under the Hood — The Agentic Loop

This isn’t your typical API call. OpenAI has implemented something akin to the ReAct framework—Reason, Act, Observe, React.

Here’s the loop process:

  1. 🧠 Reason: Given a prompt like “Find top 3 competitors' Q2 earnings,” ChatGPT creates a plan.
  2. 🔧 Act: It opens its toolkit and performs actions like a Google search.
  3. 👁️ Observe: It watches for outputs (e.g., did it get a page? Was it relevant?).
  4. 🔁 Repeat: Based on output, it adjusts and tries again.

All this runs within a sandboxed virtual computer, so your data and machine are protected.


🧪 A Real-World Example (Made Simple)

Prompt:

“Go to LinkedIn and find engineering managers in Bangalore who’ve worked at high-growth startups and have 5+ years of experience. List their names.”

Execution Flow:

  1. ✅ Navigate to LinkedIn
  2. ✅ Search: “Engineering Manager Bangalore”
  3. ✅ Apply filters: “5+ years experience” (UI-dependent)
  4. ✅ Analyze list of results
  5. ✅ Inspect each profile
  6. ✅ Infer whether past companies were high-growth startups
  7. ✅ Extract matched names
  8. ✅ Compile and return the final list

This kind of flow used to require Selenium, Puppeteer, or LangChain. Now? It can be done natively with ChatGPT’s agent.


🛡️ What About Security?

OpenAI has built-in safety layers:

  • Prompts before submitting forms or PII
  • Sandbox execution to isolate environment access
  • User-in-the-loop confirmations

But devs know: the devil is in the edge cases.

✨ Questions to keep in mind:

  • How reliably does it detect PII across edge cases?
  • How does it handle multi-step login flows or JS-heavy pages?
  • Could it be misled by a phishing-style frontend?

These guardrails are solid first steps, but deeper validation will be essential at enterprise scale.


💭 Final Thoughts & Open Questions

This is a foundational move that bridges the gap between LLMs and autonomous agents. It makes “power scripting” accessible to millions of users—and potentially removes the need for command-line scripting in lots of automatable use cases.

But we should ask:

  • What’s your first workflow to automate with this?
  • What new attack vectors could emerge?
  • Does this reduce the need for frameworks like LangChain, or are we just getting started?

Let’s talk. Drop your thoughts or use cases in the comments 👇

Happy coding! 🚀

Top comments (0)