
Agents are no longer a concept or a theory—they’ve become infrastructure. And in just the last 60 days, the game has fundamentally changed:
Zapier launched Model Context Protocol (MCP)
OpenAI gave ChatGPT browser and file access
NVIDIA released Nemotron, an LLM tuned for task execution
These aren’t just new features. They’re signs we’ve entered Agentic AI 2.0—a world where software doesn’t just respond to input, it takes action.
And for early-stage founders, this shift presents a rare, time-sensitive window of opportunity.
Zapier’s Model Context Protocol (MCP)
Allows agents to connect to 8,000+ apps without building custom APIs
Browser automation built-in
Backed by Microsoft, indicating serious enterprise momentum
OpenAI’s New Autonomy Features
ChatGPT can now operate your browser and desktop like a junior operations assistant
Think Robotic Desktop Automation—but smarter, contextual, and more adaptable
NVIDIA’s Agent-Optimized LLM: Nemotron
Purpose-built for executing workflows—not just holding conversations
A clear signal that major players are betting on autonomy at the infrastructure level
Agentic AI is turning the traditional software model on its head. Here’s what that unlocks:
Forget UI-first thinking — Build automated workflows, not dashboards
Agents-as-SaaS — A new interaction layer between users and legacy software
Plug-and-play interoperability — With MCP, agents can integrate with existing systems in hours, not weeks
The biggest opportunity?
AI-native tools that quietly handle repetitive work in the background—without ever needing a visible interface.
We’re seeing a surge in demand (and white space) in areas like:
Agent-native SaaS for niche industries
Invisible automation layers powering internal ops
Agent governance: trust scoring, audit trails, approval logic
If you can replace a human-in-the-loop task—especially in trust-sensitive areas like invoicing, QA, or triage—you’re still early to the market. But you won’t be alone for long.
We’re currently partnering with a handful of early-stage founders to help them design agent-native MVPs.
If you want to:
Stress test your AI idea
Get feedback on your use case
Map out your MVP + tech stack
Book a strategy call with our team
You’ll leave with:
A clarified use case
MVP scope and milestones
A recommended stack and agent orchestration plan
Let’s build.