Pillars of an Autonomous Agentic System - by sohit kumar

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Pillars of an Autonomous Agentic System

sohit kumar<br>Jun 24, 2026

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With the rise of agents, every platform needs to be thought through from first principles - where the agent is a first-class citizen and actively does work on the platform.<br>I don’t think we will have fully autonomous systems on day 0.<br>We need to build platforms where humans and agents can work together. Over time, as models keep getting better, more and more work will be done by agents, while humans move toward overseeing them.<br>So how should we think about the journey from a platform where humans and agents work together to a world where most of the work is done by agents?<br>I think there are three foundational pillars for building an autonomous system.<br>Context<br>Enough has been said about context, so I don’t need to over-explain this.<br>But humans and agents need to operate on the same context layer. That will only happen when platforms start capturing more decisions, traces, workflows, and outcomes as part of the system itself.<br>Over time, this becomes the organization’s memory.<br>Governance<br>Agents need to be first-class citizens on the platform, and they need access control similar to humans.<br>What can they access vs. what can they not access?

Which team are they part of?

Who can delegate to them?

What tasks can be delegated to them?

What boundaries and rules do they need to follow?

What reasoning capability can they use?

Which model should they use for a given task?

How much can they spend on reasoning for that task?

As more work moves to agents, governance becomes the control plane for how agents safely operate inside the organization.<br>Self-Learning and Evolution<br>The platform needs to have a constitution and principles for how it evolves.<br>How and when can it add more agents for specific tasks?

How and when can it add new skills?

How can it validate that the platform is behaving correctly?

How should communication between agents happen?

For a system to learn, it should be able to verify whether something is working or not, capture new context it sees while working on a task with humans, and add it back to the context layer so that the next task does not start from zero, but with the needed context.<br>In each layer, we will need human oversight. But the degree of human involvement will vary based on task complexity, risk, and confidence in the system.<br>If we build on these three fundamental principles, we can actively move toward systems where agents do most of the work, with humans stepping in only when needed.<br>We don’t start with autonomous systems. We move toward them.<br>This is what I am building with Prinevo (<br>@helloprinevo<br>) - a software factory where humans and agents collaborate to ship production-ready software.

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