Forget ChatGPT: We're Entering the Agentic Society - By Sourav Mishra (@souravvmishra)

We're not just improving chatbots. We're moving into an "agentic society" where autonomous agents do multi-step work without a human in every loop. I see it in how people use Claude Code, in longer sessions, and in platforms where agents interact with each other. That change affects how I build products and where I put guardrails. In this post I, Sourav Mishra, break down what the agentic society means, why it matters for developers, and how to build for it without building blind.

What I Mean by "Agentic Society"

The agentic society is the idea that more and more work is done by agents that reason, decide, use tools, and complete tasks end-to-end—not just answer questions in a chat box. The shift is from "user asks, model answers" to "user sets a goal, agent runs until done (or hits a limit)."

Evidence I point to is concrete. Claude Code is contributing a measurable share of code on GitHub; teams (e.g. at Spotify) report barely writing code manually anymore for whole slices of their stack. Session lengths in agentic tools have doubled in some studies—for example, the 99.9th percentile of turn duration went from around 25 minutes to over 45 minutes in a matter of months. That's not chat; that's extended, multi-step execution. Research like Anthropic's agent autonomy work shows that even when agents run freely, most tool use still has human oversight—so we're talking about a hybrid world, not pure autonomy. But the capacity for long, tool-chaining runs is here.

The discussion isn't only optimistic. I also worry about intelligent spam, channel overload, and the bar for automation dropping so low that abuse becomes trivial. So "agentic society" is both the trend I build for and a reason to add guardrails from day one.

How This Differs From "Using ChatGPT"

ChatGPT is largely a single-turn or short conversational interface. You ask; it answers. You might have a few follow-ups, but the model doesn't typically run a long-lived loop of tool calls without you in the loop. The agentic society implies agents that run longer tasks, chain tools, and operate with less constant human supervision—or at least with the option to run many steps before a human checks in.

That distinction drives architecture. Chat-first systems assume the user is present every turn. Agent-first systems assume the agent might run 5, 10, or 20 steps before returning a result or asking for confirmation. So we need timeouts, step limits, and clear boundaries. I spell out the technical difference between agents and workflows elsewhere; the product implication is that "agentic" isn't just a buzzword—it changes how we design for safety and cost.

Why This Matters for Developers

If the default expectation becomes "the agent does it," then our systems need to be safe when the agent does the wrong thing or is manipulated. That means three things in practice.

Bounded autonomy. Agents need hard stops. In the Vercel AI SDK that's patterns like stopWhen: stepCountIs(N). Without a cap you get "and then it called the API 10,000 times" or worse. I use step limits in every agent I ship; see Building an Agentic Chatbot with Vercel AI SDK for the full pattern.

Tool validation and least privilege. Agents should only have the tools they need, with the narrowest scope possible. No shared admin creds; no "run anything" endpoints. Real incidents (e.g. in my AI agent security fact-check) consistently point at overprivileged access. Design for tool safety from the start.

Human-in-the-loop for irreversible or high-stakes actions. Most production tool use still has human oversight; only a tiny fraction of actions are irreversible. Design for that. For delete, pay, publish—require confirmation or at least review. "Agent proposes, human confirms" is the right default. Anthropic's research backs that up.

It also means designing for agent-to-agent and agent-to-API interactions, not only human-in-the-loop chat. Architectures that assume a single user turn will feel outdated. If you're building platforms where multiple agents or external systems talk to your agent, you need clear boundaries and verification—I wrote about multi-agent security for that reason.

The Ethics Angle

Who builds the agents, who uses them, and who pays—that's part of the same picture. Building for an "agentic society" without thinking about access, control, and misuse is building blind. The Cancel ChatGPT movement and the debate over who gets to use frontier models are one side of it; the other is making sure the agents we ship don't become vectors for spam, fraud, or abuse.

I treat the agentic society as the target state: more automation, more delegation. My job is to ship agents that are robust, auditable, and aligned with clear boundaries—not to ship maximum autonomy and hope for the best. That means defaulting to step limits, least-privilege tools, and human-in-the-loop where it matters, and being explicit about what the agent is allowed to do and who is accountable.

Key Takeaways

• Agentic society = work increasingly done by autonomous agents in multi-step loops, not only chat. Evidence: longer sessions, more code and workflows agent-driven, and platforms where agents interact.
• Different from ChatGPT: agentic implies long-lived tasks, tool chaining, and less constant human presence per step. Design for step limits, timeouts, and clear review UX.
• Build for bounded autonomy, tool safety, and human-in-the-loop for irreversible actions. Assume agents will be manipulated; validate inputs and scope permissions.
• Consider ethics and control (who uses the agent, for what) from the start. Robust and auditable beats "maximum autonomy."

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This post was written by Sourav Mishra, a Full Stack Engineer focused on Next.js and AI applications.

Frequently Asked Questions

Q: What is the agentic society? The idea that more work will be done by autonomous AI agents that reason, use tools, and complete tasks end-to-end, rather than by humans or simple chatbots.

Q: How is the agentic society different from using ChatGPT? ChatGPT is largely a single-turn or short conversational interface. The agentic society implies agents that run long-lived tasks, chain tools, and operate with less constant human supervision.

Q: What should developers do to prepare for an agentic society? Design for tool safety, step limits, and human-in-the-loop for irreversible actions. Assume agents will be manipulated; validate inputs and scope permissions. Prefer architectures that support agent-to-agent and agent-to-API flows, not only human-in-the-loop chat.

Q: Where can I see a concrete agent implementation with guardrails? Building an agentic chatbot with the Vercel AI SDK—includes tools, stopWhen, and streaming with bounded autonomy.