About
The Context Window exists because I believe the most important technology shift in human history deserves better than surface-level takes and hype cycles.
Every week, thousands of AI articles are published. Most explain what happened. Very few explain why it matters, what it connects to, or where it leads. The discourse is dominated by hot takes, benchmarks out of context, and breathless “AGI is here” proclamations based on a single demo.
I wanted a second option. A place that goes deep instead of wide. That tracks its predictions honestly. That connects ideas into a knowledge graph instead of dumping isolated articles into a feed. That serves both the human reader who wants to truly understand AI and the AI agent that needs structured, citable knowledge.
The Open Knowledge Protocol
The web was built for human browsers. But we're entering an era where AI agents are becoming a primary consumer of online information. They research topics, cite sources, and synthesize knowledge — but the current web is hostile to machine consumption. Every site is a different shape of HTML that agents have to scrape and hope for the best.
The Open Knowledge Protocol is my attempt to fix that — an open-source standard for structuring content so AI agents can consume it natively. Think of it as building the Wikipedia of tech for Web 4.0: the agentic web where machines don't just read pages, they query knowledge graphs.
The Context Window is the reference implementation. Every article has Concept DNA — structured metadata with key claims, confidence levels, prerequisites, and knowledge graph connections. The whole site is queryable via an MCP server, REST API, and llms.txt. And the protocol itself is open-source — any publisher can adopt it.
The vision is simple: if enough publishers structure their content for machine consumption, we create a knowledge web that AI agents can navigate as easily as humans navigate links. Not a walled garden. Not a single company's dataset. An open, interconnected graph of human knowledge, built for the next era of the internet.
Why I Built This
I'm Aditya. I've been obsessed with AI since the first time I watched a language model generate text that made me forget I was talking to a machine. Not because the technology is cool (it is), but because of what it means for how we learn, work, create, and relate to information.
The thing that frustrates me most about AI discourse is how shallow it often is. We have the most transformative technology since the internet, and the dominant conversation is about which chatbot writes better marketing copy. The deeper questions — how agents will reshape personal computing, why memory architectures matter more than parameter counts, what the agentic web means for content creators — these get buried under the hype.
The Context Window is my answer: deep dives that assume you're smart and curious. Analysis that looks at trajectories, not just announcements. Predictions with timestamps and confidence levels, tracked honestly over time. And a belief that the best way to share knowledge about AI is to build with AI — making the platform itself a demonstration of what's possible.
Articles are written by me, with research assistance from specialized AI agents that help with paper discovery, fact-checking, and generating adversarial perspectives. I believe in human editorial judgment powered by AI research capability — the best of both.
What Makes This Different
| The AI content landscape | The Context Window |
|---|---|
| Surface-level trending takes | Deep structural analysis of long-term impact |
| Isolated articles in a feed | Knowledge graph with connected concepts |
| Predictions made casually, never revisited | Timestamped predictions tracked with confidence levels |
| Writes about AI | Built as AI infrastructure |
| Optimized for Google only | Optimized for humans, Google, and AI agents |
| Content locked in HTML | MCP server + REST API + llms.txt |
| No intellectual accountability | Adversarial perspectives on every deep dive |
Principles
One well-researched deep dive is worth more than ten hot takes.
Every claim has a confidence level. Predictions are tracked. Being wrong is recorded, not hidden.
The protocol is open-source. The API is public. The content is free. Knowledge wants to be shared.
If I write about the agentic web, the platform should be agentic. The medium is the message.
Evergreen analysis that ages well beats trending content that's forgotten in a week.
Get Involved
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