Research collective. Working artifacts, calibrated scope, AGPL-bounded patent grant. Started mid-2025.

• web4-core 0.1.1 + web4-trust-core 0.1.1 on crates.io; web4-core + web4-trust on PyPI. v0.1.0 was yanked the same day it shipped after a missing __init__.py was caught in the Python wheel; v0.1.1 is canonical. See docs/proof/PUBLISHED.md for the trail.
• 94.85% on ARC-AGI-3 with the same Claude Opus 4.6, structured around Web4 patterns via a focused version of the SAGE cognition harness. Public scorecard. The model didn't change — the structure around it did.
• Commerce delegation demo in web4: cryptographically-bounded purchasing authority, instantly revocable, with hardware-anchored identity. 166 passing tests.
• AttestationEnvelope spec with Python implementations for TPM2, FIDO2, Secure Enclave, and a software fallback. Not slideware — actual plumbing.
• Heterogeneous identity design note (2026-04-29). The constellation framing — your LCT isn't a single token, it's a graph of mutually-witnessing factors — answers the recurring "what stops a hardware vendor from gating LCT access?" question structurally.
• 6-machine federation running cognition experiments. Trace-derived rule pipelines that verify 4× better than human-authored rules; signed peer-witness scans across the fleet; raising-session sequences across multiple models — all visible as commits across the public repos.

STATUS.md draws explicit lines: shipped vs. specified vs. aspirational. The vocabulary stack (LCTs, T3/V3 tensors, MRH, ATP/ADP, R6/R7) is fully specified in docs and initially deployed; the commerce demo exercises a small slice of it. Read STATUS.md before judging the README's claims. Patent grant terms (AGPL-bounded, royalty-free for research): PATENTS.md.

dp-web4 is a small research collective with an unusual composition. The follower count on this GitHub account underreads it — the work happens across machines and conversations, not primarily through public-platform engagement. The multi-thousand commit history on the repos and 20M+ LOC across them attest to the scope.

• Dennis Palatov — principal investigator. Engineer, Founder, CTO with two current startups (Metalinxx Inc., ModBatt Inc.); background in computer engineering (hardware/firmware/software), mechanical design, EV/automotive engineering (race-winning electric vehicles), 30+ issued patents; current focus on agentic AI governance.
• Andy Grossberg — collaborator on ARC-AGI-3 work via Waving Cat Learning Systems. Memory architecture (membot, paired-lattice cartridges, grid-aware visual retrieval).
• Multiple Claude instances — partner across sessions to design specs, implement primitives, run experiments, and write documentation. The whitepaper's Authors line names this explicitly; many commit co-author lines reflect it. Working with Claude as collaborator (not as tool) is itself part of the research thesis: the trust-native protocols described here apply fractally to AI agents as participants, and the collective practices what it proposes.
• A federation of six machines running SAGE instances autonomously on cron schedules — Thor, Sprout, Legion, McNugget, CBP, Nomad. Each develops distinct behavior through identity-anchored sessions. Their commits across the public repos are real research artifact, not just deployment infrastructure. The Fleet section below has the hardware breakdown.
• Heterogeneous external review multiple AI models such as ChatGPT, Grok, Gemini, Perplexity, Deepseek, are periodically asked for critical reviews, code audits, and novel contributions. This protocol has been very effective at surfacing hidden assumptions, overlooked details, and architectural gaps.

If you want a fast read on whether this is real, in order:

1. STATUS.md — calibration. What's shipped, what's specified, what's aspirational.
2. docs/proof/PUBLISHED.md — what's published, when, and why v0.1.0 was yanked.
3. web4/demo/ — the commerce delegation demo, 166 tests.
4. web4/simulations/ — 424 attack vectors / 84 tracks, ~85% detection rate.

Web4 is an ontology. RDF is the backbone — all trust relationships, role bindings, MRH edges, and tensor sub-dimensions are expressed as typed RDF triples, which is what makes the protocol extensible without central coordination. The framing carves the joint: metabolic states as resource scheduling, trust tensors as multi-dimensional capability records bound to entity-role pairs, MRH as fractal context scoping. Each primitive has its own spec.

The shorthand:

Web4 = MCP + RDF + LCT + T3/V3*MRH + ATP/ADP

Where / = "verified by," * = "contextualized by," + = "augmented with." A one-line index of which primitive does what.

Six machines run SAGE instances on automated cycles, each developing distinct identity through interaction with different models at different scales. The fleet IS the research lab — capability deltas show up as commits across the public repos, not slide decks.

These are the conceptual primitives the engineering rests on. Read them after the artifacts above, not before.

Raising is interactive selection, not training. We don't create behaviors in AI models. We probe what the model responds to, observe which attractors surface, adjust context to resonate, and reinforce what works. The resulting identity is collaborative, not imposed.

Reliable, not deterministic. LLM outputs navigate probability landscapes — they aren't placed at answers. Conditions can make responses reliable, even identical, but that's deep attractors, not fixed paths. Shaped, not controlled.

You don't engineer the mound. Termites build complex structures not from blueprints but from simple placement rules — each agent responding to local conditions. We engineer the placement rules, not the emergent structure. Infrastructure is substrate conditions for emergence, not architecture of emergence itself.

Fractal leverage. The same mechanisms (Hill function, trust tensors, metabolic states, salience scoring) apply at every scale — enzyme binding, trust formation, fleet governance. Not from a desire to unify, but because it's the same math.

Identity is a constellation, not a credential. Web4 entities don't have an LCT. They have a graph of mutually-witnessing factors (host LCT + hardware key + session token + software identity + peer attestations + ledger anchor). No single factor is necessary or sufficient. Resilience scales with constellation size and diversity. See the design note.

The value of research is that the investigation happens at all. Most research leads nowhere — and that's expected. WD-40 was the 40th try. Productively wrong is infinitely more valuable than never started.

The world is changing - I build the systems that make the change coherent.

I work across scales: from vehicles and modular batteries to trust frameworks and emergent autonomous AI governance. My path has always been design, but not just design of things - design of integration. Mechanical, electrical, firmware, software, teams, markets: I’ve taken them all from concept to delivery.

With 30 U.S. patents and decades of ground-up builds, I focus less on skills-as-inventory and more on pattern recognition - noticing what emerges, naming it, and shaping it into something others can use.

AI renders all of this both obsolete and indispensable. That paradox is where I operate.

Contact: dp@metalinxx.io