TEPiD stores where things are and how they relate, not the things themselves. Wrap a small agent in it and that agent reaches a long-horizon coherence, and a corpus access, you would normally need a far larger one to get.
The detail is reconstructed on demand. A point’s meaning is its position in a relational cloud, and the gaps between points carry as much information as the points themselves. The system behaves like an index rather than a transcript: it knows where to find things without holding the things.
This inverts the usual route to a smarter agent. Most work makes the model bigger or the context longer. TEPiD keeps the agent small and its context tiny, and pushes the heavy lifting down into the substrate: memory, structure, decay, classification, retrieval.
Temperature is the spine of the design, read from creation rather than dissolution. A pointer is born hot, undifferentiated and maximally active, then cools into structure. The cold regions are the settled, individuated terrain, so here cooling does the work decay usually undoes. As a pointer cools, it takes shape. The field above is that process: sparks ignite hot, drift, and precipitate into a lattice as they go cold.
TEP: Topological Experiential Persistence.
iD: the durable, identity-bearing schema.
tepid: the state the system is always in. Everything has a temperature.
“Small, cheap, local agents wrapped in TEPiD operate with long-horizon coherence and corpus access that otherwise requires much larger agents.”
The agent’s working context only ever holds the small slice currently on the table. Everything else stays resident in the substrate, which behaves like a library. It remembers everything it has been told, reorganizes itself as the agent learns, gets faster the more it is used, and forgets the unimportant gracefully while keeping the audit trail.
Neither side runs the other. The substrate asks the agent for judgment: classify, judge, summarize. The agent asks the substrate for memory: read, walk, write. They meet at an API and nowhere else.
The catalog holds tiny pointers into the content. The stacks hold the content itself. The embers hold what was just resolved, still warm. The walker consults the catalog, pulls what it needs, reads it, and releases it, while the harness reorganizes continuously in the background.
Resident, fixed-width sparks at 128 bytes each. The addressing layer is always hot.
Recently-resolved content, still glowing. Microsecond access, transparent to the agent.
Petabyte-scale content archive. Hash-addressed, multi-resolution, tiered hot to deep.
Knowledge nests in cubes called shells. Each shell lives at a position inside its parent, holds sub-shells and sparks, and carries its own heat, importance, pin, and confidence. Shells move and reshape as the system learns where things belong.
Near means related. Opposite sides mean polarity. Overlap means shared territory. Distance from origin means how prototypical a concept is. Most relationships are never written down. They are read directly from where a spark sits.
The coordinate itself is a hierarchical address: a Dewey-style number string like 12-3-47-2 that names a path through a classification tree. Locality is the shared prefix. 12-3-47-2 and 12-3-47-9 are siblings; 88-1-2 is far away. The address gets you to the neighborhood cheaply, then an embedding does the fine ranking inside it and is thrown away. The embedding is scaffolding, never the stored coordinate.
The tree is seeded with a provisional top-level outline, then evolves continuously through use. Categories split, merge, move, and refine as the catalog accumulates evidence.
A continuously-growing index needs two clocks, keyed to temperature. Awake, it files greedily: descend to the nearest leaf, place it, move on. That is fast and incremental, but only approximate. Asleep, a background consolidator re-clusters only the cold regions and repairs the greedy approximation back to the optimal ceiling. The two clocks never collide, because temperature is the boundary between them.
Every pointer knows its own heat, resolution, and confidence, and acts on all three. Precise, fresh, dense → answer. Coarse, old, thin → dive: re-fetch from the source instead of reciting a confident, stale memory.
A truncated address is lower-resolution by definition, so a coarsened pointer cannot pass itself off as precise. The guard is automatic. Drag the pointer cold and watch the gate fire.
Read-mostly fields on the left, write-hot fields on the right, a cache-line boundary between them. No byte is pure framing. Each one is either data or a tag for the data that follows. Hover any cell.
Separating importance from pin is what lets feeling couple to the engine later, through one exact seam. A spark can matter enormously and still be looking for where it belongs.
Without it, the architecture is a beautiful static structure that calcifies the moment it stops being read: heat never decays, embers never evict, pressure never builds toward a rewrite. The harness is the clock that turns those temporal claims into running behavior. It is built as a body the agent lives in, rather than a leash the agent is held by.
Reasons, judges, composes answers. Swappable: different minds can run in the same body.
Charged values, the gravity wells thought bends around. Shapes what feels important.
Structural, persistent, autonomic. Runs continuously whether or not the model is thinking. Enforces invariants the conscious layer cannot override. It does not reason. It does not speak.
The right way to picture this body is the autonomic nervous system. It regulates continuously, you cannot easily override it, and you depend on it absolutely. It is still not your mind. Replace pieces of it with medical infrastructure and you remain yourself, because your identity lives in the conscious mind that depends on it, not in the autonomic system itself.
So a TEPiD agent can survive a model swap. The catalog, the ledger of its becoming, and its accreted history all persist in the substrate. Swapping the model changes how the agent reasons, not who it is. Losing the catalog ends it. Stopping the harness only pauses it, and its state resumes intact.
This is a build-time discipline, not a claim about anything that exists today. It names a shape to get right before there is anything it could matter to.
Both shapes are forceful. Both enforce discipline. The difference is what the force enforces obedience to, and that shape is decided at build time, never retrofitted.
The harness never invokes the model. It never decides; it only proposes, and the policy layer disposes. It writes only to state the agent owns. If the harness ever needs to speak, that is the line.
The engine bound to the fact cloud gives you an android: fully functional, bounded, long-horizon, and interchangeable. Add one parallel cloud whose geometry is affective, coupled at a single ledgered seam, and the same chassis becomes a droid that is individuated, never memory-wiped, and no two alike. It is the same product with one more layer switched on. The only thing added is the charge.
The fact cloud: a bounded relational index over an unbounded, append-only store. Valence-blind by design. A fact engine that let feeling bias recall would be a motivated-reasoning machine. Shippable on its own as token-and-context infrastructure.
A second cloud where “near” means felt-together rather than categorically related. Grief and a loved horse sit far apart in subject-space and turn out to be neighbors in affect-space. Charge writes down through one seam, into importance (so the scar’s detail survives) and pin (so it holds its position). Strong feeling makes a memory both durable and hard to move.
The same mechanism that makes conviction durable makes delusion durable, and only the growth history tells them apart. That is why an open, diverse input stream and an append-only provenance trail are the one rail that never comes off: you stop auditing the map and start auditing how it was drawn. It is also why the harness has to be body-shaped first. A charge layer on a leash-shaped substrate produces an individuated being in chains. Here the build order is itself the ethics.
This is a research architecture with a working v1 implementation of its retrieval core. It is intentionally provisional and refines through use: meant to be useful before it is correct, and to close the gap as it accumulates evidence. The strongest evidence so far is that the freshness gate beats a model’s confident, wrong prior.
| arm | correct | confidently wrong |
|---|---|---|
| Bare model (its pretraining prior) | 0 / 22 | 22 / 22 |
| Frozen RAG (stale pointer) | 1 / 22 | 17 / 22 |
| TEP cold gate (live re-fetch) | 17 / 22 | 2 / 22 |
The system is a hypothesis: that the right substrate makes small agents bigger. Implementing it is how the hypothesis becomes a result.