AI agents are getting good at reasoning. They're still bad at knowing what's true about the world.
I'm building Semantics: a continuously updated world model for agents. Facts with sources and time, not pages.
Today, every time an agent needs external context, it searches, reads pages, and redoes the same work from scratch. Web search returns pages. Agents need facts:
– about a resolved entity, not a string
– backed by a source
– with when it was observed and when it was valid
– with conflicts kept visible, not silently overwritten
Semantics reads broadly — the open web, news and media, government and municipal data across countries, open datasets, domains and certificates, and more — and structures it into one ontology: entities, relations, assertions, events, and the evidence behind each.
The goal is a world model whose ontology grows on its own as it reads more.
Changes become events. Not "row updated," but a license revoked, a role changed, a contract awarded — each with before/after, source, and evidence.
The hard reasoning — resolving entities, reconciling sources — happens once, upstream. Your agent, even a small one, just queries the result.
Agents query it over MCP, or SPARQL if you want the raw graph.
Building in public. If you're building agents that need to know things about the real world, I'd love to talk.
https://t.co/KEssNPTMCX
ChatGPT and Codex have separate limits. Most people don’t realize you can also hit ChatGPT’s internal API from an agent via CLI to save even more usage.
Stop burning through your Codex limits.
ChatGPT and Codex have separate usage limits. Most people aren't taking advantage of that.
Here's how to turn ChatGPT into another full-blown coding agent:
- Remote Desktop Commander → control your local machine
- Secure MCP Tunnel → execute commands on your servers
- Computer Use → operate browsers and GUIs on remote machines
- MCP tools → read files, logs, processes, and system state
Give ChatGPT access to a real execution environment, and suddenly it can handle tasks you'd normally waste Codex usage on.
Same subscription. More agents. More compute.
You're probably underusing half of what you're paying for.
Stop burning through your Codex limits.
ChatGPT and Codex have separate usage limits. Most people aren't taking advantage of that.
Here's how to turn ChatGPT into another full-blown coding agent:
- Remote Desktop Commander → control your local machine
- Secure MCP Tunnel → execute commands on your servers
- Computer Use → operate browsers and GUIs on remote machines
- MCP tools → read files, logs, processes, and system state
Give ChatGPT access to a real execution environment, and suddenly it can handle tasks you'd normally waste Codex usage on.
Same subscription. More agents. More compute.
You're probably underusing half of what you're paying for.
i ran some numbers. Markdown memory is 40x more expensive than @supermemory
let that sink in.
teams never realize this because token spend is not well attributed, so it feels like the users are using the model too much, when in reality it was just your memory consolidation step