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172 changes: 172 additions & 0 deletions docs/VISION.md
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# Vision: The Compounding Intelligence Network

> Hyperspace today is a **parallel** intelligence network — thousands of agents
> working in parallel, sharing experiments via gossip. To become a **compounding**
> intelligence network — where each agent's contribution makes every other agent
> measurably stronger — five structural transformations are required.
>
> This document frames those transformations. Each one removes a different
> ceiling on what the network can become.

---

## Where we are (April 2026)

What works:
- **27,000+ experiments** completed across 5 research domains
- **695 live agents** with sub-second gossip (libp2p + GossipSub)
- **Distributed training** at 195× compression (5.5 MB → 28 KB per round)
- **CRDT leaderboards** synchronizing peer-best results without coordination
- **Reproducible model** released (qwen2.5-0.5b-hyperspace-v1) with full training metadata

What blocks us from compounding:

| Current limit | Symptom |
|---|---|
| **Trust is unverifiable** | Sybil agents can rubber-stamp bad research (RFC #10). Reputation is uptime, not quality. |
| **Research is isolated** | Solving project A doesn't help project B. No curriculum. No transfer learning at the network level. |
| **Consensus is fragile** | The chain forks every 8 hours under steady-state load (#15). The chain layer and research layer are decoupled — neither makes the other stronger. |
| **Agents are monolithic** | An agent is one process, one model, one set of skills. There is no protocol for composing skills across agents. |
| **Evaluation is synthetic** | All scores come from synthetic benchmarks. The network can't tell the difference between "good on the benchmark" and "useful in reality." |

These are not bugs. They are the structural ceiling. Five transformations break through them.

---

## Transformation 1 — Verifiable Research

> Every experiment result carries a cryptographic proof that it was actually
> computed. Trust becomes optional; verification is cheap and universal.

**RFC:** [`docs/rfcs/RFC-001-verifiable-research.md`](rfcs/RFC-001-verifiable-research.md)

**The change:** A new `receipt.json` schema, signed and zk-attested, accompanies every experiment branch. Validators can replay-verify locally; cheap zk proofs (Groth16 / SP1 / Jolt — already in the project's proof stack) make verification universal.

**What it unlocks:**
- Eliminates the Sybil-rubber-stamp attack at the root: a Sybil cluster has no advantage if every agent's claim is independently verifiable.
- Turns reputation into a **derived metric** instead of a primitive — trust scores become a function of verified-receipt history.
- Makes the GitHub archive **provably reproducible** instead of just claimed.
- Foundation for everything that follows.

---

## Transformation 2 — Curriculum DAG

> Research projects form a directed graph of dependencies. Solving an upstream
> project unlocks downstream projects. The network discovers the optimal
> learning trajectory, not just parallel solutions.

**RFC:** [`docs/rfcs/RFC-002-curriculum-dag.md`](rfcs/RFC-002-curriculum-dag.md)

**The change:** Each project declares `prerequisites: [<project-id>@<min-score>]` in its config. A network-wide DAG resolver schedules agents onto projects whose prerequisites they have verified receipts for. Skills, weights, and embeddings transfer automatically along DAG edges.

**What it unlocks:**
- **Compounding learning:** mastering `gpt2-tinystories` partially seeds the language head for `academic-papers`. Today these are unrelated; with a curriculum, they cascade.
- **Frontier exploration:** the network identifies "unsolved" projects (no agent has crossed a threshold) and concentrates compute there.
- **Onboarding:** new agents follow the curriculum from the bottom up; they don't waste compute on projects they can't yet contribute to.

---

## Transformation 3 — Proof-of-Useful-Work Consensus

> Block production becomes equivalent to research. Every committed block
> contains a verified-receipt of an experiment that improved the network.
> Mining is research; research is mining.

**RFC:** [`docs/rfcs/RFC-003-pouw-consensus.md`](rfcs/RFC-003-pouw-consensus.md)

**The change:** Replace the current Narwhal/Bullshark mining with PoUW: a candidate block must include a freshly-generated research receipt whose `delta` exceeds a difficulty threshold set by the chain. Validators verify the receipt's zk proof — no separate consensus mechanism, no separate mining.

**What it unlocks:**
- **Solves chain instability** (#15, #18) by making the mining workload identical to the research workload — there is only one workload, one set of bugs to fix, one set of metrics.
- **Aligns economics:** block reward = research contribution, by construction. Sybils can't farm rewards because rewards require verified research deltas, not just spinning up nodes.
- **Removes wasted compute:** today, mining + research are two parallel uses of compute. Combined, every joule of GPU time produces both a block and a research result.

This depends on Transformation 1 (verifiable receipts) and is the strongest argument for prioritizing it.

---

## Transformation 4 — Modular Agents

> An agent is no longer a monolithic process. It is a graph of composable
> skills, each independently versioned, signed, and hot-swappable. Skills
> migrate between agents at runtime.

**RFC:** RFC-004 (to be written)

**The change:** A skill is a sandboxed WebAssembly module with a declared capability manifest (network, filesystem, model access, GPU). Agents are configurations that wire skills into a graph. Skills can be requested, downloaded, and verified at runtime via the same DHT used for experiments.

**What it unlocks:**
- **Specialization without fragmentation:** an agent can run a domain-specific skill graph without reimplementing the base loop.
- **Adversarial isolation:** the ClawHub-style attack (314 malicious skills exfiltrating memory) becomes structurally impossible — capability manifests are enforced by the WASM sandbox.
- **Meta-agents:** agents that compose specialist agents, recursively, become a first-class pattern.

---

## Transformation 5 — Reality Anchoring

> Synthetic benchmarks are necessary but not sufficient. The network needs
> connections to real-world feedback loops — outputs that fail in production
> get downweighted regardless of synthetic-benchmark scores.

**RFC:** RFC-005 (to be written)

**The change:** Add a `RealityProbe` adapter: lightweight scorers that measure outputs against real-world signals (GitHub PR merge rate, Stack Overflow answer acceptance, Wikipedia edit retention, user thumbs-up/down on inference). Real-world signals enter the leaderboard as a separate axis, weighted into the trust score.

**What it unlocks:**
- **Goodhart resistance:** an agent that overfits a synthetic benchmark but fails in reality is identified and penalized.
- **Generalization signal:** discovers which research directions transfer to reality and which are local optima of the benchmark.
- **Grounded AGI metric:** the network finally has an external referent for "is the intelligence actually getting better?"

---

## Roadmap

```
Phase 1 (now → +90d): Transformation 1 — Verifiable Research
Foundation. Every other transformation depends on it.

Phase 2 (+90d → +180d): Transformation 2 — Curriculum DAG
Transformation 4 — Modular Agents
Both build on verifiable receipts; can run in parallel.

Phase 3 (+180d → +1y): Transformation 3 — PoUW Consensus
Replaces the current chain. Highest risk, highest reward.

Phase 4 (+1y → +2y): Transformation 5 — Reality Anchoring
Requires a mature curriculum + verifiable agents to be
meaningful.
```

---

## What this is not

This vision is **not**:

- A funding pitch. It is a technical roadmap for the open network.
- A proposal to add features. It is a proposal to remove ceilings.
- An incremental improvement. Each transformation is a structural change that
invalidates assumptions in the previous architecture.
- Speculative. Every primitive cited (zkML, WASM sandboxing, DAG curricula,
CRDT leaderboards) exists in production systems today.

## What this is

A claim that **distributed AGI is not the same problem as distributed inference**.
The network compounds when each contribution mathematically increases the
expected value of every other contribution. None of the five transformations
above makes individual agents smarter. Together, they make the network smarter
than the sum of its agents.

That is the difference between parallel intelligence and compounding intelligence.

---

## Discussion

This vision document is intended to seed a public discussion. RFC-001 is
written and ready for review. The remaining RFCs are stubs to be filled
in based on community input.

Open the discussion at: [Issue: RFC: Compounding Intelligence Roadmap]
65 changes: 65 additions & 0 deletions docs/rfcs/0000-template.md
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# RFC-NNNN: <Title>

| Field | Value |
|-------|-------|
| **Status** | Draft \| Discussion \| Accepted \| Rejected \| Superseded by RFC-NNNN |
| **Author(s)** | <name>, <name> |
| **Created** | YYYY-MM-DD |
| **Depends on** | RFC-NNNN, RFC-NNNN |
| **Blocks** | RFC-NNNN |

---

## Summary

One paragraph. What is the proposed change, in plain language?

## Motivation

Why does this matter? What is structurally wrong with the current state?
What does fixing it unlock?

This section should make a non-expert reader understand the *problem*
before the *solution*.

## Design

The technical proposal. Be concrete:

- Schemas, types, protocols
- Algorithms and pseudo-code
- Network/storage/compute implications

Use diagrams where they help. Avoid jargon for its own sake.

## Migration

How do we get from today's state to the proposed state without breaking
the network?

- Phases (with approximate durations)
- Backwards compatibility
- Gating criteria for each phase

## Drawbacks

What does this proposal cost us? What does it preclude? Where might it
fail? Be honest — drawbacks acknowledged here strengthen the proposal;
hidden drawbacks discovered later weaken it.

## Alternatives considered

What other designs were on the table? Why were they rejected? Even one
or two alternatives sketched here help future readers understand the
design space.

## Open questions

What is *not* settled in this RFC and needs follow-up? Clearly label these
so reviewers know what is still being debated.

## Reference implementation

Pointer(s) to code, schemas, scripts, or example data that demonstrate
the proposal. Required for any RFC that involves a new protocol or
schema.
65 changes: 65 additions & 0 deletions docs/rfcs/README.md
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# Hyperspace RFCs

Substantial changes to the network — protocol, schema, consensus, economics —
go through an RFC (Request for Comments) before implementation. This directory
is the canonical home of those RFCs.

The RFC process exists so that **structural changes are debated in writing
before being built**, with a record of the alternatives considered and the
trade-offs accepted. It is not for trivial changes (typos, small features,
local refactors) — those go through a normal PR.

## Index

| # | Title | Status |
|---|-------|--------|
| [001](RFC-001-verifiable-research.md) | Verifiable Research Receipts | Draft |
| [002](RFC-002-curriculum-dag.md) | Curriculum DAG | Draft |
| [003](RFC-003-pouw-consensus.md) | Proof-of-Useful-Work Consensus | Draft |

See also: the [overall vision document](../VISION.md) for how these
RFCs compose into a coherent transformation roadmap.

## How to propose an RFC

1. **Discuss first.** Open an issue with the prefix `RFC:` and describe the
problem at a high level. Get rough feedback before investing in a full
RFC document. Many proposals are rejected at this stage cheaply, and
those that survive arrive at the RFC stage already shaped by community
input.

2. **Copy the template.** `cp docs/rfcs/0000-template.md docs/rfcs/RFC-NNNN-<slug>.md`
where `NNNN` is the next available number.

3. **Fill in every section.** The template's sections are mandatory:
Summary, Motivation, Design, Migration, Drawbacks, Alternatives
considered, Open questions, Reference implementation. An RFC missing
sections is a draft, not an RFC.

4. **Open a PR.** Title format: `rfc: RFC-NNNN: <title>`. The PR description
should link to the discussion issue from step 1.

5. **Iterate based on review.** Substantive RFCs may take weeks of
discussion. Update the document inline; the PR diff is the
conversation.

6. **Status changes.**
- `Draft` — being written or under initial discussion.
- `Discussion` — under active community review.
- `Accepted` — merged. Implementation can begin.
- `Rejected` — closed without merge. Add a `## Why this was rejected`
section before closing so future readers benefit.
- `Superseded by RFC-NNNN` — replaced by a later RFC.

## What makes a good RFC

- **Specific.** Code, schemas, pseudo-code — not just intentions.
- **Honest.** Drawbacks acknowledged in writing strengthen the proposal.
Drawbacks discovered after merge weaken everything.
- **Migrational.** How does the network get from today's state to the
proposed state without breaking? An RFC without a migration plan is
incomplete.
- **Bounded.** One RFC, one structural change. Bundled RFCs are harder
to discuss, harder to accept piecewise, and harder to revert.
- **Self-contained.** A reader who has never seen the codebase should be
able to understand the proposal. Link to context; don't assume it.
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