okay i think i cooked

bangerr videoo

its testing time

I was digging around on X and found Crosmos. It's a conceptual neighbour to what I'm researching, not as a vector backend but as a persistent context substrate for agents. Its core claim is that agents fail because context is scattered, stateless, and temporally flat. Their answer is a monotonic temporal knowledge graph, hybrid retrieval, contextual memories, soft forgetting, clusters, MCP tools, and editor skills. Their relevance is the architectural pattern, since context should be structured, persistent, queryable, provenance-aware, and exposed to agents (through MCP/skills). This supports my theory, we need a layer between agents and repositories, rather than another standalone agent framework. The most useful design lesson is their rejection of over-splitting. The “atomic” units should not become tiny disconnected fragments. They need to remain self-contained enough for agents to act on, while still being precise enough for retrieval and coverage analysis. Crosmos is broader organizational memory. I intend to stay narrower and sharper with repository structure, changed paths, context packs, branch drift, stale docs, trial artifacts, execution handoff, and evidence-aware coding context. Crosmos validates the market direction for me; my research's differentiation is codebase-native structural context with verifiable and measurable agent-execution outcomes.

People working around context infra and memory should realize, it's not about recall. Anyone can make their own custom RAG pipeline / filesystem setup that's good enough and works for them in a day. You're just adding 3 more steps to it. The main objective of a context infra should be how well are you maintaining the context over long running agents / noisy data / how well you handle contradictions / how well you forget. Yes "forget". Context is not just about storing a record. It's about giving the agent the intelligence it needs. How well you represent the context is how good your infra is. We're building crosmos.dev on the same primitives. Check it out and give your agents persistent context. Building at @localhostIND

we using motion for the launch video

Sometimes all you need to do is provide quality before promising it. Users pay for experience not promises.

The more I look into interference theory, the more it feels like a useful substrate for understanding why noise hurts representation quality. Looking at the geometry of the underlying vector space makes a lot of these effects much easier to reason about. Things that seem unrelated often end up being consequences of interference and signal degradation.

momentum is built when you stop restarting and start improving the same thing

Just shipped our graph package, go make your own on - crosmos.dev and give the context your agents need.

We've had really good experience with @ZeroEntropy_AI while building @crosmoslabs. Really happy they're growing so well. Giving it a shot was worth it

Goated guy

From the way I see it, context management and the ways you can handle it, depends heavily on the use-case of the context, and the environment it is utilized in. And I think that's the reason why there are so many approaches to solve it. Each might solve a problem of it's own scope. But keeping in mind how heavily it is reliant on the environment the context is used in. There will always be multiple ways to handle context.

self launch video built in one day everything is ai dreamlike-creative-direction… for mobile: view horizontally double tap/click and enjoy the music @dreamlikedawar @swapnilsdream