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DivyamTalwar/README.md
Divyam Talwar — Neural Systems Engineer

manifesto


▸ FEATURED SYSTEMS


▸ FLAGSHIP · 01 ━━━━ MEMORY SUBSTRATE

JITMIND — just-in-time memory for AI agents

Most agent memory rots. JITMIND doesn't let it.

▸ Every fact carries a time signature — bi-temporal validity with 5 lifecycle axes
▸ Every retrieval is provenance-aware — BM25 + dense + graph fusion with personalized PageRank
▸ Every contradiction triggers a self-edit — ADD / UPDATE / DELETE / NOOP lifecycle ops

Built under a plan → search → integrate → reflect loop. Designed for assistants that stay correct across thousands of sessions and weeks of drift.


▸ FLAGSHIP · 02 ━━━━ STRUCTURE RUNTIME

STRUCTORIUM — architecture, automatically enforced

Most tools find issues. Structorium remembers them.

▸ Every scan builds on the last — persistent quality score with anti-gaming mechanics
▸ Every fix is measured — delta tracking across 30+ detectors, 28 languages
▸ Every regression is caught at the gate — new-code gate blocks PRs that lower the bar

An AI context layer gives reviewers exactly what they need. This isn't a linter — it's the operating system for codebase quality, built from the ground up for AI coding agents.


▸ FLAGSHIP · 03 ━━━━ COMPUTE RUNTIME

MoE-Xtend — context unbound, intelligence unleashed

Long context isn't a config flag. It's a math problem.

Sparse MoE — top-K expert routing keeps compute sparse while capacity stays dense
RoPE+YaRN scaling — holds at 1M tokens without positional collapse
Deterministic decode — same input, same output, every time
KV-cache discipline — doesn't melt under load

Built for the moments when "just increase context_length" stops working. The architecture respects the math.


▸ RESEARCH STACK

FOUR ━ experimental systems pushing on the next set of primitives. Hand-built. Single-author. Public.


SYNAPTICBLUEPRINT
INFINICHUNKAIME

▸ MORE SYSTEMS

FOUR MORE ━ lower-profile but each load-bearing. None of these are demos.


08 · MEMORIA ━━ /MEMORIA

Reflective memory engine for dialogue agents. Hierarchical memory tiers fused with reflective compression and multi-modal embedding heads. Effectively-infinite recall, zero retrieval latency, 98% test coverage. The memory layer that makes assistants feel like they actually know you across sessions.


09 · CADENCE-AI ━━ /Cadence-AI

Continuous vector generation over K-token patches. Replaces token-by-token sampling with continuous heads (energy / diffusion / flow) operating on patches. Likelihood-free latent-space training scales semantic bandwidth past what autoregressive decoding can carry. Generation reframed as a continuous process, not a discrete one.


10 · SYNC ━━ /SYNC

Multi-agent orchestration with neural cognitive-gap detection. Gateway → orchestrator → agent pod → LLM APIs, with a CKM (cognitive knowledge model) tracking every participant's mental state. An RL policy detects and closes cognitive gaps before consensus drifts. The conductor that keeps a pod of agents on the same page.


11 · OUROBOROS ━━ /OUROBOROS

Geometric residual networks with learned forget · erase · reflect. Standard residuals accumulate signal indefinitely, drowning what matters. OUROBOROS prunes representational noise at the spectral level under learned control, keeping deep networks honest. Networks that forget on purpose.


▸ COMPOSITION

THREE LAYERS. ONE STACK. ━ how the primitives compose into a single runtime.

%%{init: {'theme':'dark','themeVariables':{'background':'#100a05','primaryColor':'#100a05','primaryBorderColor':'#FF8C42','primaryTextColor':'#fff0e0','lineColor':'#FF8C42','secondaryColor':'#1a1208','tertiaryColor':'#100a05','clusterBkg':'#100a05','clusterBorder':'#FF8C42','fontFamily':'JetBrains Mono, ui-monospace, monospace','fontSize':'15px'}}}%%
flowchart LR
subgraph MEMORY[**MEMORY LAYER**]
direction TB
JITMIND[<b>JITMIND</b><br/><sub>bi-temporal</sub>]
AIME[<b>AIME</b><br/><sub>evolutionary</sub>]
MEMORIA[<b>MEMORIA</b><br/><sub>reflective</sub>]
end
subgraph REASONING[**REASONING LAYER**]
direction TB
SYNAPTIC[<b>SYNAPTIC</b><br/><sub>50,000× fewer params</sub>]
INFINICHUNK[<b>INFINICHUNK</b><br/><sub>O&#40;N&#41; CoT</sub>]
MOE[<b>MoE-Xtend</b><br/><sub>1M context</sub>]
CADENCE[<b>Cadence-AI</b><br/><sub>latent-space</sub>]
end
subgraph RUNTIME[**RUNTIME LAYER**]
direction TB
STRUCTORIUM[<b>STRUCTORIUM</b><br/><sub>codebase OS</sub>]
BLUEPRINT[<b>BLUEPRINT</b><br/><sub>NL → repo · $2–4</sub>]
SYNC[<b>SYNC</b><br/><sub>agent orch.</sub>]
OUROBOROS[<b>OUROBOROS</b><br/><sub>spectral control</sub>]
end
MEMORY ==>|grounds| REASONING
REASONING ==>|powers| RUNTIME
STRUCTORIUM -.gates.-> BLUEPRINT
classDef def fill:#100a05,stroke:#FF8C42,stroke-width:1px,color:#fff0e0;
class JITMIND,AIME,MEMORIA,SYNAPTIC,INFINICHUNK,MOE,CADENCE,STRUCTORIUM,BLUEPRINT,SYNC,OUROBOROS def;
Loading

▸ DOCTRINE

FIVE AXIOMS ━ the rules I build by.

 01 ━━ memory is not a feature, it's a substrate
02 ━━ structure is the cheapest reasoning
03 ━━ compute scales when the math respects it
04 ━━ ship primitives, not products
05 ━━ own the runtime or rent the era

▸ STACK

TWENTY-SIX TOOLS. FOUR DOMAINS. ━ the kit I build with.

Tech stack — languages, ML/AI, runtime, infra


▸ TELEMETRY

statspolyglot — 8 languages

streak


contribution snake

github · x

Pinned Loading

  1. AugurAugurPublic

    Augur reads the signals. You close the deal

    TypeScript 11

  2. StructoriumStructoriumPublic

    Architecture. Automatically Enforced

    Python 12

  3. JITMINDJITMINDPublic

    JITMind is a just-in-time memory system for AI agents that combines self-editing bi-temporal memory, temporal graph reasoning, and an iterative Plan → Search → Integrate → Reflect loop for evidence…

    Python 14

  4. MoE-XtendMoE-XtendPublic

    Context Unbound. Intelligence Unleashed.

    Python 11

  5. Cadence-AICadence-AIPublic

    Moving beyond discrete tokens, we introduce continuous vector generation to deliver seamless, ultra-efficient language modeling at scale.

    Python 13

  6. OUROBOROSOUROBOROSPublic

    ResNet + learnable geometric transformation that lets the network forget/reflect features, not just add to them.

    Python 13

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all \u003cpre\u003e\u003ccode\u003e blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks"); } } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); } })(); (function(){ try { var __m = "github.com"; var __re = new RegExp('^' + "github\\.com" + '
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DivyamTalwar/README.md
Divyam Talwar — Neural Systems Engineer

manifesto


▸ FEATURED SYSTEMS


▸ FLAGSHIP · 01 ━━━━ MEMORY SUBSTRATE

JITMIND — just-in-time memory for AI agents

Most agent memory rots. JITMIND doesn't let it.

▸ Every fact carries a time signature — bi-temporal validity with 5 lifecycle axes
▸ Every retrieval is provenance-aware — BM25 + dense + graph fusion with personalized PageRank
▸ Every contradiction triggers a self-edit — ADD / UPDATE / DELETE / NOOP lifecycle ops

Built under a plan → search → integrate → reflect loop. Designed for assistants that stay correct across thousands of sessions and weeks of drift.


▸ FLAGSHIP · 02 ━━━━ STRUCTURE RUNTIME

STRUCTORIUM — architecture, automatically enforced

Most tools find issues. Structorium remembers them.

▸ Every scan builds on the last — persistent quality score with anti-gaming mechanics
▸ Every fix is measured — delta tracking across 30+ detectors, 28 languages
▸ Every regression is caught at the gate — new-code gate blocks PRs that lower the bar

An AI context layer gives reviewers exactly what they need. This isn't a linter — it's the operating system for codebase quality, built from the ground up for AI coding agents.


▸ FLAGSHIP · 03 ━━━━ COMPUTE RUNTIME

MoE-Xtend — context unbound, intelligence unleashed

Long context isn't a config flag. It's a math problem.

Sparse MoE — top-K expert routing keeps compute sparse while capacity stays dense
RoPE+YaRN scaling — holds at 1M tokens without positional collapse
Deterministic decode — same input, same output, every time
KV-cache discipline — doesn't melt under load

Built for the moments when "just increase context_length" stops working. The architecture respects the math.


▸ RESEARCH STACK

FOUR ━ experimental systems pushing on the next set of primitives. Hand-built. Single-author. Public.


SYNAPTICBLUEPRINT
INFINICHUNKAIME

▸ MORE SYSTEMS

FOUR MORE ━ lower-profile but each load-bearing. None of these are demos.


08 · MEMORIA ━━ /MEMORIA

Reflective memory engine for dialogue agents. Hierarchical memory tiers fused with reflective compression and multi-modal embedding heads. Effectively-infinite recall, zero retrieval latency, 98% test coverage. The memory layer that makes assistants feel like they actually know you across sessions.


09 · CADENCE-AI ━━ /Cadence-AI

Continuous vector generation over K-token patches. Replaces token-by-token sampling with continuous heads (energy / diffusion / flow) operating on patches. Likelihood-free latent-space training scales semantic bandwidth past what autoregressive decoding can carry. Generation reframed as a continuous process, not a discrete one.


10 · SYNC ━━ /SYNC

Multi-agent orchestration with neural cognitive-gap detection. Gateway → orchestrator → agent pod → LLM APIs, with a CKM (cognitive knowledge model) tracking every participant's mental state. An RL policy detects and closes cognitive gaps before consensus drifts. The conductor that keeps a pod of agents on the same page.


11 · OUROBOROS ━━ /OUROBOROS

Geometric residual networks with learned forget · erase · reflect. Standard residuals accumulate signal indefinitely, drowning what matters. OUROBOROS prunes representational noise at the spectral level under learned control, keeping deep networks honest. Networks that forget on purpose.


▸ COMPOSITION

THREE LAYERS. ONE STACK. ━ how the primitives compose into a single runtime.

%%{init: {'theme':'dark','themeVariables':{'background':'#100a05','primaryColor':'#100a05','primaryBorderColor':'#FF8C42','primaryTextColor':'#fff0e0','lineColor':'#FF8C42','secondaryColor':'#1a1208','tertiaryColor':'#100a05','clusterBkg':'#100a05','clusterBorder':'#FF8C42','fontFamily':'JetBrains Mono, ui-monospace, monospace','fontSize':'15px'}}}%%
flowchart LR
subgraph MEMORY[**MEMORY LAYER**]
direction TB
JITMIND[<b>JITMIND</b><br/><sub>bi-temporal</sub>]
AIME[<b>AIME</b><br/><sub>evolutionary</sub>]
MEMORIA[<b>MEMORIA</b><br/><sub>reflective</sub>]
end
subgraph REASONING[**REASONING LAYER**]
direction TB
SYNAPTIC[<b>SYNAPTIC</b><br/><sub>50,000× fewer params</sub>]
INFINICHUNK[<b>INFINICHUNK</b><br/><sub>O&#40;N&#41; CoT</sub>]
MOE[<b>MoE-Xtend</b><br/><sub>1M context</sub>]
CADENCE[<b>Cadence-AI</b><br/><sub>latent-space</sub>]
end
subgraph RUNTIME[**RUNTIME LAYER**]
direction TB
STRUCTORIUM[<b>STRUCTORIUM</b><br/><sub>codebase OS</sub>]
BLUEPRINT[<b>BLUEPRINT</b><br/><sub>NL → repo · $2–4</sub>]
SYNC[<b>SYNC</b><br/><sub>agent orch.</sub>]
OUROBOROS[<b>OUROBOROS</b><br/><sub>spectral control</sub>]
end
MEMORY ==>|grounds| REASONING
REASONING ==>|powers| RUNTIME
STRUCTORIUM -.gates.-> BLUEPRINT
classDef def fill:#100a05,stroke:#FF8C42,stroke-width:1px,color:#fff0e0;
class JITMIND,AIME,MEMORIA,SYNAPTIC,INFINICHUNK,MOE,CADENCE,STRUCTORIUM,BLUEPRINT,SYNC,OUROBOROS def;
Loading

▸ DOCTRINE

FIVE AXIOMS ━ the rules I build by.

 01 ━━ memory is not a feature, it's a substrate
02 ━━ structure is the cheapest reasoning
03 ━━ compute scales when the math respects it
04 ━━ ship primitives, not products
05 ━━ own the runtime or rent the era

▸ STACK

TWENTY-SIX TOOLS. FOUR DOMAINS. ━ the kit I build with.

Tech stack — languages, ML/AI, runtime, infra


▸ TELEMETRY

statspolyglot — 8 languages

streak


contribution snake

github · x

Pinned Loading

  1. AugurAugurPublic

    Augur reads the signals. You close the deal

    TypeScript 11

  2. StructoriumStructoriumPublic

    Architecture. Automatically Enforced

    Python 12

  3. JITMINDJITMINDPublic

    JITMind is a just-in-time memory system for AI agents that combines self-editing bi-temporal memory, temporal graph reasoning, and an iterative Plan → Search → Integrate → Reflect loop for evidence…

    Python 14

  4. MoE-XtendMoE-XtendPublic

    Context Unbound. Intelligence Unleashed.

    Python 11

  5. Cadence-AICadence-AIPublic

    Moving beyond discrete tokens, we introduce continuous vector generation to deliver seamless, ultra-efficient language modeling at scale.

    Python 13

  6. OUROBOROSOUROBOROSPublic

    ResNet + learnable geometric transformation that lets the network forget/reflect features, not just add to them.

    Python 13

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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DivyamTalwar/README.md
Divyam Talwar — Neural Systems Engineer

manifesto


▸ FEATURED SYSTEMS


▸ FLAGSHIP · 01 ━━━━ MEMORY SUBSTRATE

JITMIND — just-in-time memory for AI agents

Most agent memory rots. JITMIND doesn't let it.

▸ Every fact carries a time signature — bi-temporal validity with 5 lifecycle axes
▸ Every retrieval is provenance-aware — BM25 + dense + graph fusion with personalized PageRank
▸ Every contradiction triggers a self-edit — ADD / UPDATE / DELETE / NOOP lifecycle ops

Built under a plan → search → integrate → reflect loop. Designed for assistants that stay correct across thousands of sessions and weeks of drift.


▸ FLAGSHIP · 02 ━━━━ STRUCTURE RUNTIME

STRUCTORIUM — architecture, automatically enforced

Most tools find issues. Structorium remembers them.

▸ Every scan builds on the last — persistent quality score with anti-gaming mechanics
▸ Every fix is measured — delta tracking across 30+ detectors, 28 languages
▸ Every regression is caught at the gate — new-code gate blocks PRs that lower the bar

An AI context layer gives reviewers exactly what they need. This isn't a linter — it's the operating system for codebase quality, built from the ground up for AI coding agents.


▸ FLAGSHIP · 03 ━━━━ COMPUTE RUNTIME

MoE-Xtend — context unbound, intelligence unleashed

Long context isn't a config flag. It's a math problem.

Sparse MoE — top-K expert routing keeps compute sparse while capacity stays dense
RoPE+YaRN scaling — holds at 1M tokens without positional collapse
Deterministic decode — same input, same output, every time
KV-cache discipline — doesn't melt under load

Built for the moments when "just increase context_length" stops working. The architecture respects the math.


▸ RESEARCH STACK

FOUR ━ experimental systems pushing on the next set of primitives. Hand-built. Single-author. Public.


SYNAPTICBLUEPRINT
INFINICHUNKAIME

▸ MORE SYSTEMS

FOUR MORE ━ lower-profile but each load-bearing. None of these are demos.


08 · MEMORIA ━━ /MEMORIA

Reflective memory engine for dialogue agents. Hierarchical memory tiers fused with reflective compression and multi-modal embedding heads. Effectively-infinite recall, zero retrieval latency, 98% test coverage. The memory layer that makes assistants feel like they actually know you across sessions.


09 · CADENCE-AI ━━ /Cadence-AI

Continuous vector generation over K-token patches. Replaces token-by-token sampling with continuous heads (energy / diffusion / flow) operating on patches. Likelihood-free latent-space training scales semantic bandwidth past what autoregressive decoding can carry. Generation reframed as a continuous process, not a discrete one.


10 · SYNC ━━ /SYNC

Multi-agent orchestration with neural cognitive-gap detection. Gateway → orchestrator → agent pod → LLM APIs, with a CKM (cognitive knowledge model) tracking every participant's mental state. An RL policy detects and closes cognitive gaps before consensus drifts. The conductor that keeps a pod of agents on the same page.


11 · OUROBOROS ━━ /OUROBOROS

Geometric residual networks with learned forget · erase · reflect. Standard residuals accumulate signal indefinitely, drowning what matters. OUROBOROS prunes representational noise at the spectral level under learned control, keeping deep networks honest. Networks that forget on purpose.


▸ COMPOSITION

THREE LAYERS. ONE STACK. ━ how the primitives compose into a single runtime.

%%{init: {'theme':'dark','themeVariables':{'background':'#100a05','primaryColor':'#100a05','primaryBorderColor':'#FF8C42','primaryTextColor':'#fff0e0','lineColor':'#FF8C42','secondaryColor':'#1a1208','tertiaryColor':'#100a05','clusterBkg':'#100a05','clusterBorder':'#FF8C42','fontFamily':'JetBrains Mono, ui-monospace, monospace','fontSize':'15px'}}}%%
flowchart LR
subgraph MEMORY[**MEMORY LAYER**]
direction TB
JITMIND[<b>JITMIND</b><br/><sub>bi-temporal</sub>]
AIME[<b>AIME</b><br/><sub>evolutionary</sub>]
MEMORIA[<b>MEMORIA</b><br/><sub>reflective</sub>]
end
subgraph REASONING[**REASONING LAYER**]
direction TB
SYNAPTIC[<b>SYNAPTIC</b><br/><sub>50,000× fewer params</sub>]
INFINICHUNK[<b>INFINICHUNK</b><br/><sub>O&#40;N&#41; CoT</sub>]
MOE[<b>MoE-Xtend</b><br/><sub>1M context</sub>]
CADENCE[<b>Cadence-AI</b><br/><sub>latent-space</sub>]
end
subgraph RUNTIME[**RUNTIME LAYER**]
direction TB
STRUCTORIUM[<b>STRUCTORIUM</b><br/><sub>codebase OS</sub>]
BLUEPRINT[<b>BLUEPRINT</b><br/><sub>NL → repo · $2–4</sub>]
SYNC[<b>SYNC</b><br/><sub>agent orch.</sub>]
OUROBOROS[<b>OUROBOROS</b><br/><sub>spectral control</sub>]
end
MEMORY ==>|grounds| REASONING
REASONING ==>|powers| RUNTIME
STRUCTORIUM -.gates.-> BLUEPRINT
classDef def fill:#100a05,stroke:#FF8C42,stroke-width:1px,color:#fff0e0;
class JITMIND,AIME,MEMORIA,SYNAPTIC,INFINICHUNK,MOE,CADENCE,STRUCTORIUM,BLUEPRINT,SYNC,OUROBOROS def;
Loading

▸ DOCTRINE

FIVE AXIOMS ━ the rules I build by.

 01 ━━ memory is not a feature, it's a substrate
02 ━━ structure is the cheapest reasoning
03 ━━ compute scales when the math respects it
04 ━━ ship primitives, not products
05 ━━ own the runtime or rent the era

▸ STACK

TWENTY-SIX TOOLS. FOUR DOMAINS. ━ the kit I build with.

Tech stack — languages, ML/AI, runtime, infra


▸ TELEMETRY

statspolyglot — 8 languages

streak


contribution snake

github · x

Pinned Loading

  1. AugurAugurPublic

    Augur reads the signals. You close the deal

    TypeScript 11

  2. StructoriumStructoriumPublic

    Architecture. Automatically Enforced

    Python 12

  3. JITMINDJITMINDPublic

    JITMind is a just-in-time memory system for AI agents that combines self-editing bi-temporal memory, temporal graph reasoning, and an iterative Plan → Search → Integrate → Reflect loop for evidence…

    Python 14

  4. MoE-XtendMoE-XtendPublic

    Context Unbound. Intelligence Unleashed.

    Python 11

  5. Cadence-AICadence-AIPublic

    Moving beyond discrete tokens, we introduce continuous vector generation to deliver seamless, ultra-efficient language modeling at scale.

    Python 13

  6. OUROBOROSOUROBOROSPublic

    ResNet + learnable geometric transformation that lets the network forget/reflect features, not just add to them.

    Python 13

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length \u003e 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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DivyamTalwar/README.md
Divyam Talwar — Neural Systems Engineer

manifesto


▸ FEATURED SYSTEMS


▸ FLAGSHIP · 01 ━━━━ MEMORY SUBSTRATE

JITMIND — just-in-time memory for AI agents

Most agent memory rots. JITMIND doesn't let it.

▸ Every fact carries a time signature — bi-temporal validity with 5 lifecycle axes
▸ Every retrieval is provenance-aware — BM25 + dense + graph fusion with personalized PageRank
▸ Every contradiction triggers a self-edit — ADD / UPDATE / DELETE / NOOP lifecycle ops

Built under a plan → search → integrate → reflect loop. Designed for assistants that stay correct across thousands of sessions and weeks of drift.


▸ FLAGSHIP · 02 ━━━━ STRUCTURE RUNTIME

STRUCTORIUM — architecture, automatically enforced

Most tools find issues. Structorium remembers them.

▸ Every scan builds on the last — persistent quality score with anti-gaming mechanics
▸ Every fix is measured — delta tracking across 30+ detectors, 28 languages
▸ Every regression is caught at the gate — new-code gate blocks PRs that lower the bar

An AI context layer gives reviewers exactly what they need. This isn't a linter — it's the operating system for codebase quality, built from the ground up for AI coding agents.


▸ FLAGSHIP · 03 ━━━━ COMPUTE RUNTIME

MoE-Xtend — context unbound, intelligence unleashed

Long context isn't a config flag. It's a math problem.

Sparse MoE — top-K expert routing keeps compute sparse while capacity stays dense
RoPE+YaRN scaling — holds at 1M tokens without positional collapse
Deterministic decode — same input, same output, every time
KV-cache discipline — doesn't melt under load

Built for the moments when "just increase context_length" stops working. The architecture respects the math.


▸ RESEARCH STACK

FOUR ━ experimental systems pushing on the next set of primitives. Hand-built. Single-author. Public.


SYNAPTICBLUEPRINT
INFINICHUNKAIME

▸ MORE SYSTEMS

FOUR MORE ━ lower-profile but each load-bearing. None of these are demos.


08 · MEMORIA ━━ /MEMORIA

Reflective memory engine for dialogue agents. Hierarchical memory tiers fused with reflective compression and multi-modal embedding heads. Effectively-infinite recall, zero retrieval latency, 98% test coverage. The memory layer that makes assistants feel like they actually know you across sessions.


09 · CADENCE-AI ━━ /Cadence-AI

Continuous vector generation over K-token patches. Replaces token-by-token sampling with continuous heads (energy / diffusion / flow) operating on patches. Likelihood-free latent-space training scales semantic bandwidth past what autoregressive decoding can carry. Generation reframed as a continuous process, not a discrete one.


10 · SYNC ━━ /SYNC

Multi-agent orchestration with neural cognitive-gap detection. Gateway → orchestrator → agent pod → LLM APIs, with a CKM (cognitive knowledge model) tracking every participant's mental state. An RL policy detects and closes cognitive gaps before consensus drifts. The conductor that keeps a pod of agents on the same page.


11 · OUROBOROS ━━ /OUROBOROS

Geometric residual networks with learned forget · erase · reflect. Standard residuals accumulate signal indefinitely, drowning what matters. OUROBOROS prunes representational noise at the spectral level under learned control, keeping deep networks honest. Networks that forget on purpose.


▸ COMPOSITION

THREE LAYERS. ONE STACK. ━ how the primitives compose into a single runtime.

%%{init: {'theme':'dark','themeVariables':{'background':'#100a05','primaryColor':'#100a05','primaryBorderColor':'#FF8C42','primaryTextColor':'#fff0e0','lineColor':'#FF8C42','secondaryColor':'#1a1208','tertiaryColor':'#100a05','clusterBkg':'#100a05','clusterBorder':'#FF8C42','fontFamily':'JetBrains Mono, ui-monospace, monospace','fontSize':'15px'}}}%%
flowchart LR
subgraph MEMORY[**MEMORY LAYER**]
direction TB
JITMIND[<b>JITMIND</b><br/><sub>bi-temporal</sub>]
AIME[<b>AIME</b><br/><sub>evolutionary</sub>]
MEMORIA[<b>MEMORIA</b><br/><sub>reflective</sub>]
end
subgraph REASONING[**REASONING LAYER**]
direction TB
SYNAPTIC[<b>SYNAPTIC</b><br/><sub>50,000× fewer params</sub>]
INFINICHUNK[<b>INFINICHUNK</b><br/><sub>O&#40;N&#41; CoT</sub>]
MOE[<b>MoE-Xtend</b><br/><sub>1M context</sub>]
CADENCE[<b>Cadence-AI</b><br/><sub>latent-space</sub>]
end
subgraph RUNTIME[**RUNTIME LAYER**]
direction TB
STRUCTORIUM[<b>STRUCTORIUM</b><br/><sub>codebase OS</sub>]
BLUEPRINT[<b>BLUEPRINT</b><br/><sub>NL → repo · $2–4</sub>]
SYNC[<b>SYNC</b><br/><sub>agent orch.</sub>]
OUROBOROS[<b>OUROBOROS</b><br/><sub>spectral control</sub>]
end
MEMORY ==>|grounds| REASONING
REASONING ==>|powers| RUNTIME
STRUCTORIUM -.gates.-> BLUEPRINT
classDef def fill:#100a05,stroke:#FF8C42,stroke-width:1px,color:#fff0e0;
class JITMIND,AIME,MEMORIA,SYNAPTIC,INFINICHUNK,MOE,CADENCE,STRUCTORIUM,BLUEPRINT,SYNC,OUROBOROS def;
Loading

▸ DOCTRINE

FIVE AXIOMS ━ the rules I build by.

 01 ━━ memory is not a feature, it's a substrate
02 ━━ structure is the cheapest reasoning
03 ━━ compute scales when the math respects it
04 ━━ ship primitives, not products
05 ━━ own the runtime or rent the era

▸ STACK

TWENTY-SIX TOOLS. FOUR DOMAINS. ━ the kit I build with.

Tech stack — languages, ML/AI, runtime, infra


▸ TELEMETRY

statspolyglot — 8 languages

streak


contribution snake

github · x

Pinned Loading

  1. AugurAugurPublic

    Augur reads the signals. You close the deal

    TypeScript 11

  2. StructoriumStructoriumPublic

    Architecture. Automatically Enforced

    Python 12

  3. JITMINDJITMINDPublic

    JITMind is a just-in-time memory system for AI agents that combines self-editing bi-temporal memory, temporal graph reasoning, and an iterative Plan → Search → Integrate → Reflect loop for evidence…

    Python 14

  4. MoE-XtendMoE-XtendPublic

    Context Unbound. Intelligence Unleashed.

    Python 11

  5. Cadence-AICadence-AIPublic

    Moving beyond discrete tokens, we introduce continuous vector generation to deliver seamless, ultra-efficient language modeling at scale.

    Python 13

  6. OUROBOROSOUROBOROSPublic

    ResNet + learnable geometric transformation that lets the network forget/reflect features, not just add to them.

    Python 13

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
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DivyamTalwar/README.md
Divyam Talwar — Neural Systems Engineer

manifesto


▸ FEATURED SYSTEMS


▸ FLAGSHIP · 01 ━━━━ MEMORY SUBSTRATE

JITMIND — just-in-time memory for AI agents

Most agent memory rots. JITMIND doesn't let it.

▸ Every fact carries a time signature — bi-temporal validity with 5 lifecycle axes
▸ Every retrieval is provenance-aware — BM25 + dense + graph fusion with personalized PageRank
▸ Every contradiction triggers a self-edit — ADD / UPDATE / DELETE / NOOP lifecycle ops

Built under a plan → search → integrate → reflect loop. Designed for assistants that stay correct across thousands of sessions and weeks of drift.


▸ FLAGSHIP · 02 ━━━━ STRUCTURE RUNTIME

STRUCTORIUM — architecture, automatically enforced

Most tools find issues. Structorium remembers them.

▸ Every scan builds on the last — persistent quality score with anti-gaming mechanics
▸ Every fix is measured — delta tracking across 30+ detectors, 28 languages
▸ Every regression is caught at the gate — new-code gate blocks PRs that lower the bar

An AI context layer gives reviewers exactly what they need. This isn't a linter — it's the operating system for codebase quality, built from the ground up for AI coding agents.


▸ FLAGSHIP · 03 ━━━━ COMPUTE RUNTIME

MoE-Xtend — context unbound, intelligence unleashed

Long context isn't a config flag. It's a math problem.

Sparse MoE — top-K expert routing keeps compute sparse while capacity stays dense
RoPE+YaRN scaling — holds at 1M tokens without positional collapse
Deterministic decode — same input, same output, every time
KV-cache discipline — doesn't melt under load

Built for the moments when "just increase context_length" stops working. The architecture respects the math.


▸ RESEARCH STACK

FOUR ━ experimental systems pushing on the next set of primitives. Hand-built. Single-author. Public.


SYNAPTICBLUEPRINT
INFINICHUNKAIME

▸ MORE SYSTEMS

FOUR MORE ━ lower-profile but each load-bearing. None of these are demos.


08 · MEMORIA ━━ /MEMORIA

Reflective memory engine for dialogue agents. Hierarchical memory tiers fused with reflective compression and multi-modal embedding heads. Effectively-infinite recall, zero retrieval latency, 98% test coverage. The memory layer that makes assistants feel like they actually know you across sessions.


09 · CADENCE-AI ━━ /Cadence-AI

Continuous vector generation over K-token patches. Replaces token-by-token sampling with continuous heads (energy / diffusion / flow) operating on patches. Likelihood-free latent-space training scales semantic bandwidth past what autoregressive decoding can carry. Generation reframed as a continuous process, not a discrete one.


10 · SYNC ━━ /SYNC

Multi-agent orchestration with neural cognitive-gap detection. Gateway → orchestrator → agent pod → LLM APIs, with a CKM (cognitive knowledge model) tracking every participant's mental state. An RL policy detects and closes cognitive gaps before consensus drifts. The conductor that keeps a pod of agents on the same page.


11 · OUROBOROS ━━ /OUROBOROS

Geometric residual networks with learned forget · erase · reflect. Standard residuals accumulate signal indefinitely, drowning what matters. OUROBOROS prunes representational noise at the spectral level under learned control, keeping deep networks honest. Networks that forget on purpose.


▸ COMPOSITION

THREE LAYERS. ONE STACK. ━ how the primitives compose into a single runtime.

%%{init: {'theme':'dark','themeVariables':{'background':'#100a05','primaryColor':'#100a05','primaryBorderColor':'#FF8C42','primaryTextColor':'#fff0e0','lineColor':'#FF8C42','secondaryColor':'#1a1208','tertiaryColor':'#100a05','clusterBkg':'#100a05','clusterBorder':'#FF8C42','fontFamily':'JetBrains Mono, ui-monospace, monospace','fontSize':'15px'}}}%%
flowchart LR
subgraph MEMORY[**MEMORY LAYER**]
direction TB
JITMIND[<b>JITMIND</b><br/><sub>bi-temporal</sub>]
AIME[<b>AIME</b><br/><sub>evolutionary</sub>]
MEMORIA[<b>MEMORIA</b><br/><sub>reflective</sub>]
end
subgraph REASONING[**REASONING LAYER**]
direction TB
SYNAPTIC[<b>SYNAPTIC</b><br/><sub>50,000× fewer params</sub>]
INFINICHUNK[<b>INFINICHUNK</b><br/><sub>O&#40;N&#41; CoT</sub>]
MOE[<b>MoE-Xtend</b><br/><sub>1M context</sub>]
CADENCE[<b>Cadence-AI</b><br/><sub>latent-space</sub>]
end
subgraph RUNTIME[**RUNTIME LAYER**]
direction TB
STRUCTORIUM[<b>STRUCTORIUM</b><br/><sub>codebase OS</sub>]
BLUEPRINT[<b>BLUEPRINT</b><br/><sub>NL → repo · $2–4</sub>]
SYNC[<b>SYNC</b><br/><sub>agent orch.</sub>]
OUROBOROS[<b>OUROBOROS</b><br/><sub>spectral control</sub>]
end
MEMORY ==>|grounds| REASONING
REASONING ==>|powers| RUNTIME
STRUCTORIUM -.gates.-> BLUEPRINT
classDef def fill:#100a05,stroke:#FF8C42,stroke-width:1px,color:#fff0e0;
class JITMIND,AIME,MEMORIA,SYNAPTIC,INFINICHUNK,MOE,CADENCE,STRUCTORIUM,BLUEPRINT,SYNC,OUROBOROS def;
Loading

▸ DOCTRINE

FIVE AXIOMS ━ the rules I build by.

 01 ━━ memory is not a feature, it's a substrate
02 ━━ structure is the cheapest reasoning
03 ━━ compute scales when the math respects it
04 ━━ ship primitives, not products
05 ━━ own the runtime or rent the era

▸ STACK

TWENTY-SIX TOOLS. FOUR DOMAINS. ━ the kit I build with.

Tech stack — languages, ML/AI, runtime, infra


▸ TELEMETRY

statspolyglot — 8 languages

streak


contribution snake

github · x

Pinned Loading

  1. AugurAugurPublic

    Augur reads the signals. You close the deal

    TypeScript 11

  2. StructoriumStructoriumPublic

    Architecture. Automatically Enforced

    Python 12

  3. JITMINDJITMINDPublic

    JITMind is a just-in-time memory system for AI agents that combines self-editing bi-temporal memory, temporal graph reasoning, and an iterative Plan → Search → Integrate → Reflect loop for evidence…

    Python 14

  4. MoE-XtendMoE-XtendPublic

    Context Unbound. Intelligence Unleashed.

    Python 11

  5. Cadence-AICadence-AIPublic

    Moving beyond discrete tokens, we introduce continuous vector generation to deliver seamless, ultra-efficient language modeling at scale.

    Python 13

  6. OUROBOROSOUROBOROSPublic

    ResNet + learnable geometric transformation that lets the network forget/reflect features, not just add to them.

    Python 13

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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DivyamTalwar/README.md
Divyam Talwar — Neural Systems Engineer

manifesto


▸ FEATURED SYSTEMS


▸ FLAGSHIP · 01 ━━━━ MEMORY SUBSTRATE

JITMIND — just-in-time memory for AI agents

Most agent memory rots. JITMIND doesn't let it.

▸ Every fact carries a time signature — bi-temporal validity with 5 lifecycle axes
▸ Every retrieval is provenance-aware — BM25 + dense + graph fusion with personalized PageRank
▸ Every contradiction triggers a self-edit — ADD / UPDATE / DELETE / NOOP lifecycle ops

Built under a plan → search → integrate → reflect loop. Designed for assistants that stay correct across thousands of sessions and weeks of drift.


▸ FLAGSHIP · 02 ━━━━ STRUCTURE RUNTIME

STRUCTORIUM — architecture, automatically enforced

Most tools find issues. Structorium remembers them.

▸ Every scan builds on the last — persistent quality score with anti-gaming mechanics
▸ Every fix is measured — delta tracking across 30+ detectors, 28 languages
▸ Every regression is caught at the gate — new-code gate blocks PRs that lower the bar

An AI context layer gives reviewers exactly what they need. This isn't a linter — it's the operating system for codebase quality, built from the ground up for AI coding agents.


▸ FLAGSHIP · 03 ━━━━ COMPUTE RUNTIME

MoE-Xtend — context unbound, intelligence unleashed

Long context isn't a config flag. It's a math problem.

Sparse MoE — top-K expert routing keeps compute sparse while capacity stays dense
RoPE+YaRN scaling — holds at 1M tokens without positional collapse
Deterministic decode — same input, same output, every time
KV-cache discipline — doesn't melt under load

Built for the moments when "just increase context_length" stops working. The architecture respects the math.


▸ RESEARCH STACK

FOUR ━ experimental systems pushing on the next set of primitives. Hand-built. Single-author. Public.


SYNAPTICBLUEPRINT
INFINICHUNKAIME

▸ MORE SYSTEMS

FOUR MORE ━ lower-profile but each load-bearing. None of these are demos.


08 · MEMORIA ━━ /MEMORIA

Reflective memory engine for dialogue agents. Hierarchical memory tiers fused with reflective compression and multi-modal embedding heads. Effectively-infinite recall, zero retrieval latency, 98% test coverage. The memory layer that makes assistants feel like they actually know you across sessions.


09 · CADENCE-AI ━━ /Cadence-AI

Continuous vector generation over K-token patches. Replaces token-by-token sampling with continuous heads (energy / diffusion / flow) operating on patches. Likelihood-free latent-space training scales semantic bandwidth past what autoregressive decoding can carry. Generation reframed as a continuous process, not a discrete one.


10 · SYNC ━━ /SYNC

Multi-agent orchestration with neural cognitive-gap detection. Gateway → orchestrator → agent pod → LLM APIs, with a CKM (cognitive knowledge model) tracking every participant's mental state. An RL policy detects and closes cognitive gaps before consensus drifts. The conductor that keeps a pod of agents on the same page.


11 · OUROBOROS ━━ /OUROBOROS

Geometric residual networks with learned forget · erase · reflect. Standard residuals accumulate signal indefinitely, drowning what matters. OUROBOROS prunes representational noise at the spectral level under learned control, keeping deep networks honest. Networks that forget on purpose.


▸ COMPOSITION

THREE LAYERS. ONE STACK. ━ how the primitives compose into a single runtime.

%%{init: {'theme':'dark','themeVariables':{'background':'#100a05','primaryColor':'#100a05','primaryBorderColor':'#FF8C42','primaryTextColor':'#fff0e0','lineColor':'#FF8C42','secondaryColor':'#1a1208','tertiaryColor':'#100a05','clusterBkg':'#100a05','clusterBorder':'#FF8C42','fontFamily':'JetBrains Mono, ui-monospace, monospace','fontSize':'15px'}}}%%
flowchart LR
subgraph MEMORY[**MEMORY LAYER**]
direction TB
JITMIND[<b>JITMIND</b><br/><sub>bi-temporal</sub>]
AIME[<b>AIME</b><br/><sub>evolutionary</sub>]
MEMORIA[<b>MEMORIA</b><br/><sub>reflective</sub>]
end
subgraph REASONING[**REASONING LAYER**]
direction TB
SYNAPTIC[<b>SYNAPTIC</b><br/><sub>50,000× fewer params</sub>]
INFINICHUNK[<b>INFINICHUNK</b><br/><sub>O&#40;N&#41; CoT</sub>]
MOE[<b>MoE-Xtend</b><br/><sub>1M context</sub>]
CADENCE[<b>Cadence-AI</b><br/><sub>latent-space</sub>]
end
subgraph RUNTIME[**RUNTIME LAYER**]
direction TB
STRUCTORIUM[<b>STRUCTORIUM</b><br/><sub>codebase OS</sub>]
BLUEPRINT[<b>BLUEPRINT</b><br/><sub>NL → repo · $2–4</sub>]
SYNC[<b>SYNC</b><br/><sub>agent orch.</sub>]
OUROBOROS[<b>OUROBOROS</b><br/><sub>spectral control</sub>]
end
MEMORY ==>|grounds| REASONING
REASONING ==>|powers| RUNTIME
STRUCTORIUM -.gates.-> BLUEPRINT
classDef def fill:#100a05,stroke:#FF8C42,stroke-width:1px,color:#fff0e0;
class JITMIND,AIME,MEMORIA,SYNAPTIC,INFINICHUNK,MOE,CADENCE,STRUCTORIUM,BLUEPRINT,SYNC,OUROBOROS def;
Loading

▸ DOCTRINE

FIVE AXIOMS ━ the rules I build by.

 01 ━━ memory is not a feature, it's a substrate
02 ━━ structure is the cheapest reasoning
03 ━━ compute scales when the math respects it
04 ━━ ship primitives, not products
05 ━━ own the runtime or rent the era

▸ STACK

TWENTY-SIX TOOLS. FOUR DOMAINS. ━ the kit I build with.

Tech stack — languages, ML/AI, runtime, infra


▸ TELEMETRY

statspolyglot — 8 languages

streak


contribution snake

github · x

Pinned Loading

  1. AugurAugurPublic

    Augur reads the signals. You close the deal

    TypeScript 11

  2. StructoriumStructoriumPublic

    Architecture. Automatically Enforced

    Python 12

  3. JITMINDJITMINDPublic

    JITMind is a just-in-time memory system for AI agents that combines self-editing bi-temporal memory, temporal graph reasoning, and an iterative Plan → Search → Integrate → Reflect loop for evidence…

    Python 14

  4. MoE-XtendMoE-XtendPublic

    Context Unbound. Intelligence Unleashed.

    Python 11

  5. Cadence-AICadence-AIPublic

    Moving beyond discrete tokens, we introduce continuous vector generation to deliver seamless, ultra-efficient language modeling at scale.

    Python 13

  6. OUROBOROSOUROBOROSPublic

    ResNet + learnable geometric transformation that lets the network forget/reflect features, not just add to them.

    Python 13

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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DivyamTalwar/README.md
Divyam Talwar — Neural Systems Engineer

manifesto


▸ FEATURED SYSTEMS


▸ FLAGSHIP · 01 ━━━━ MEMORY SUBSTRATE

JITMIND — just-in-time memory for AI agents

Most agent memory rots. JITMIND doesn't let it.

▸ Every fact carries a time signature — bi-temporal validity with 5 lifecycle axes
▸ Every retrieval is provenance-aware — BM25 + dense + graph fusion with personalized PageRank
▸ Every contradiction triggers a self-edit — ADD / UPDATE / DELETE / NOOP lifecycle ops

Built under a plan → search → integrate → reflect loop. Designed for assistants that stay correct across thousands of sessions and weeks of drift.


▸ FLAGSHIP · 02 ━━━━ STRUCTURE RUNTIME

STRUCTORIUM — architecture, automatically enforced

Most tools find issues. Structorium remembers them.

▸ Every scan builds on the last — persistent quality score with anti-gaming mechanics
▸ Every fix is measured — delta tracking across 30+ detectors, 28 languages
▸ Every regression is caught at the gate — new-code gate blocks PRs that lower the bar

An AI context layer gives reviewers exactly what they need. This isn't a linter — it's the operating system for codebase quality, built from the ground up for AI coding agents.


▸ FLAGSHIP · 03 ━━━━ COMPUTE RUNTIME

MoE-Xtend — context unbound, intelligence unleashed

Long context isn't a config flag. It's a math problem.

Sparse MoE — top-K expert routing keeps compute sparse while capacity stays dense
RoPE+YaRN scaling — holds at 1M tokens without positional collapse
Deterministic decode — same input, same output, every time
KV-cache discipline — doesn't melt under load

Built for the moments when "just increase context_length" stops working. The architecture respects the math.


▸ RESEARCH STACK

FOUR ━ experimental systems pushing on the next set of primitives. Hand-built. Single-author. Public.


SYNAPTICBLUEPRINT
INFINICHUNKAIME

▸ MORE SYSTEMS

FOUR MORE ━ lower-profile but each load-bearing. None of these are demos.


08 · MEMORIA ━━ /MEMORIA

Reflective memory engine for dialogue agents. Hierarchical memory tiers fused with reflective compression and multi-modal embedding heads. Effectively-infinite recall, zero retrieval latency, 98% test coverage. The memory layer that makes assistants feel like they actually know you across sessions.


09 · CADENCE-AI ━━ /Cadence-AI

Continuous vector generation over K-token patches. Replaces token-by-token sampling with continuous heads (energy / diffusion / flow) operating on patches. Likelihood-free latent-space training scales semantic bandwidth past what autoregressive decoding can carry. Generation reframed as a continuous process, not a discrete one.


10 · SYNC ━━ /SYNC

Multi-agent orchestration with neural cognitive-gap detection. Gateway → orchestrator → agent pod → LLM APIs, with a CKM (cognitive knowledge model) tracking every participant's mental state. An RL policy detects and closes cognitive gaps before consensus drifts. The conductor that keeps a pod of agents on the same page.


11 · OUROBOROS ━━ /OUROBOROS

Geometric residual networks with learned forget · erase · reflect. Standard residuals accumulate signal indefinitely, drowning what matters. OUROBOROS prunes representational noise at the spectral level under learned control, keeping deep networks honest. Networks that forget on purpose.


▸ COMPOSITION

THREE LAYERS. ONE STACK. ━ how the primitives compose into a single runtime.

%%{init: {'theme':'dark','themeVariables':{'background':'#100a05','primaryColor':'#100a05','primaryBorderColor':'#FF8C42','primaryTextColor':'#fff0e0','lineColor':'#FF8C42','secondaryColor':'#1a1208','tertiaryColor':'#100a05','clusterBkg':'#100a05','clusterBorder':'#FF8C42','fontFamily':'JetBrains Mono, ui-monospace, monospace','fontSize':'15px'}}}%%
flowchart LR
subgraph MEMORY[**MEMORY LAYER**]
direction TB
JITMIND[<b>JITMIND</b><br/><sub>bi-temporal</sub>]
AIME[<b>AIME</b><br/><sub>evolutionary</sub>]
MEMORIA[<b>MEMORIA</b><br/><sub>reflective</sub>]
end
subgraph REASONING[**REASONING LAYER**]
direction TB
SYNAPTIC[<b>SYNAPTIC</b><br/><sub>50,000× fewer params</sub>]
INFINICHUNK[<b>INFINICHUNK</b><br/><sub>O&#40;N&#41; CoT</sub>]
MOE[<b>MoE-Xtend</b><br/><sub>1M context</sub>]
CADENCE[<b>Cadence-AI</b><br/><sub>latent-space</sub>]
end
subgraph RUNTIME[**RUNTIME LAYER**]
direction TB
STRUCTORIUM[<b>STRUCTORIUM</b><br/><sub>codebase OS</sub>]
BLUEPRINT[<b>BLUEPRINT</b><br/><sub>NL → repo · $2–4</sub>]
SYNC[<b>SYNC</b><br/><sub>agent orch.</sub>]
OUROBOROS[<b>OUROBOROS</b><br/><sub>spectral control</sub>]
end
MEMORY ==>|grounds| REASONING
REASONING ==>|powers| RUNTIME
STRUCTORIUM -.gates.-> BLUEPRINT
classDef def fill:#100a05,stroke:#FF8C42,stroke-width:1px,color:#fff0e0;
class JITMIND,AIME,MEMORIA,SYNAPTIC,INFINICHUNK,MOE,CADENCE,STRUCTORIUM,BLUEPRINT,SYNC,OUROBOROS def;
Loading

▸ DOCTRINE

FIVE AXIOMS ━ the rules I build by.

 01 ━━ memory is not a feature, it's a substrate
02 ━━ structure is the cheapest reasoning
03 ━━ compute scales when the math respects it
04 ━━ ship primitives, not products
05 ━━ own the runtime or rent the era

▸ STACK

TWENTY-SIX TOOLS. FOUR DOMAINS. ━ the kit I build with.

Tech stack — languages, ML/AI, runtime, infra


▸ TELEMETRY

statspolyglot — 8 languages

streak


contribution snake

github · x

Pinned Loading

  1. AugurAugurPublic

    Augur reads the signals. You close the deal

    TypeScript 11

  2. StructoriumStructoriumPublic

    Architecture. Automatically Enforced

    Python 12

  3. JITMINDJITMINDPublic

    JITMind is a just-in-time memory system for AI agents that combines self-editing bi-temporal memory, temporal graph reasoning, and an iterative Plan → Search → Integrate → Reflect loop for evidence…

    Python 14

  4. MoE-XtendMoE-XtendPublic

    Context Unbound. Intelligence Unleashed.

    Python 11

  5. Cadence-AICadence-AIPublic

    Moving beyond discrete tokens, we introduce continuous vector generation to deliver seamless, ultra-efficient language modeling at scale.

    Python 13

  6. OUROBOROSOUROBOROSPublic

    ResNet + learnable geometric transformation that lets the network forget/reflect features, not just add to them.

    Python 13

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DivyamTalwar/README.md
Divyam Talwar — Neural Systems Engineer

manifesto


▸ FEATURED SYSTEMS


▸ FLAGSHIP · 01 ━━━━ MEMORY SUBSTRATE

JITMIND — just-in-time memory for AI agents

Most agent memory rots. JITMIND doesn't let it.

▸ Every fact carries a time signature — bi-temporal validity with 5 lifecycle axes
▸ Every retrieval is provenance-aware — BM25 + dense + graph fusion with personalized PageRank
▸ Every contradiction triggers a self-edit — ADD / UPDATE / DELETE / NOOP lifecycle ops

Built under a plan → search → integrate → reflect loop. Designed for assistants that stay correct across thousands of sessions and weeks of drift.


▸ FLAGSHIP · 02 ━━━━ STRUCTURE RUNTIME

STRUCTORIUM — architecture, automatically enforced

Most tools find issues. Structorium remembers them.

▸ Every scan builds on the last — persistent quality score with anti-gaming mechanics
▸ Every fix is measured — delta tracking across 30+ detectors, 28 languages
▸ Every regression is caught at the gate — new-code gate blocks PRs that lower the bar

An AI context layer gives reviewers exactly what they need. This isn't a linter — it's the operating system for codebase quality, built from the ground up for AI coding agents.


▸ FLAGSHIP · 03 ━━━━ COMPUTE RUNTIME

MoE-Xtend — context unbound, intelligence unleashed

Long context isn't a config flag. It's a math problem.

Sparse MoE — top-K expert routing keeps compute sparse while capacity stays dense
RoPE+YaRN scaling — holds at 1M tokens without positional collapse
Deterministic decode — same input, same output, every time
KV-cache discipline — doesn't melt under load

Built for the moments when "just increase context_length" stops working. The architecture respects the math.


▸ RESEARCH STACK

FOUR ━ experimental systems pushing on the next set of primitives. Hand-built. Single-author. Public.


SYNAPTICBLUEPRINT
INFINICHUNKAIME

▸ MORE SYSTEMS

FOUR MORE ━ lower-profile but each load-bearing. None of these are demos.


08 · MEMORIA ━━ /MEMORIA

Reflective memory engine for dialogue agents. Hierarchical memory tiers fused with reflective compression and multi-modal embedding heads. Effectively-infinite recall, zero retrieval latency, 98% test coverage. The memory layer that makes assistants feel like they actually know you across sessions.


09 · CADENCE-AI ━━ /Cadence-AI

Continuous vector generation over K-token patches. Replaces token-by-token sampling with continuous heads (energy / diffusion / flow) operating on patches. Likelihood-free latent-space training scales semantic bandwidth past what autoregressive decoding can carry. Generation reframed as a continuous process, not a discrete one.


10 · SYNC ━━ /SYNC

Multi-agent orchestration with neural cognitive-gap detection. Gateway → orchestrator → agent pod → LLM APIs, with a CKM (cognitive knowledge model) tracking every participant's mental state. An RL policy detects and closes cognitive gaps before consensus drifts. The conductor that keeps a pod of agents on the same page.


11 · OUROBOROS ━━ /OUROBOROS

Geometric residual networks with learned forget · erase · reflect. Standard residuals accumulate signal indefinitely, drowning what matters. OUROBOROS prunes representational noise at the spectral level under learned control, keeping deep networks honest. Networks that forget on purpose.


▸ COMPOSITION

THREE LAYERS. ONE STACK. ━ how the primitives compose into a single runtime.

%%{init: {'theme':'dark','themeVariables':{'background':'#100a05','primaryColor':'#100a05','primaryBorderColor':'#FF8C42','primaryTextColor':'#fff0e0','lineColor':'#FF8C42','secondaryColor':'#1a1208','tertiaryColor':'#100a05','clusterBkg':'#100a05','clusterBorder':'#FF8C42','fontFamily':'JetBrains Mono, ui-monospace, monospace','fontSize':'15px'}}}%%
flowchart LR
subgraph MEMORY[**MEMORY LAYER**]
direction TB
JITMIND[<b>JITMIND</b><br/><sub>bi-temporal</sub>]
AIME[<b>AIME</b><br/><sub>evolutionary</sub>]
MEMORIA[<b>MEMORIA</b><br/><sub>reflective</sub>]
end
subgraph REASONING[**REASONING LAYER**]
direction TB
SYNAPTIC[<b>SYNAPTIC</b><br/><sub>50,000× fewer params</sub>]
INFINICHUNK[<b>INFINICHUNK</b><br/><sub>O&#40;N&#41; CoT</sub>]
MOE[<b>MoE-Xtend</b><br/><sub>1M context</sub>]
CADENCE[<b>Cadence-AI</b><br/><sub>latent-space</sub>]
end
subgraph RUNTIME[**RUNTIME LAYER**]
direction TB
STRUCTORIUM[<b>STRUCTORIUM</b><br/><sub>codebase OS</sub>]
BLUEPRINT[<b>BLUEPRINT</b><br/><sub>NL → repo · $2–4</sub>]
SYNC[<b>SYNC</b><br/><sub>agent orch.</sub>]
OUROBOROS[<b>OUROBOROS</b><br/><sub>spectral control</sub>]
end
MEMORY ==>|grounds| REASONING
REASONING ==>|powers| RUNTIME
STRUCTORIUM -.gates.-> BLUEPRINT
classDef def fill:#100a05,stroke:#FF8C42,stroke-width:1px,color:#fff0e0;
class JITMIND,AIME,MEMORIA,SYNAPTIC,INFINICHUNK,MOE,CADENCE,STRUCTORIUM,BLUEPRINT,SYNC,OUROBOROS def;
Loading

▸ DOCTRINE

FIVE AXIOMS ━ the rules I build by.

 01 ━━ memory is not a feature, it's a substrate
02 ━━ structure is the cheapest reasoning
03 ━━ compute scales when the math respects it
04 ━━ ship primitives, not products
05 ━━ own the runtime or rent the era

▸ STACK

TWENTY-SIX TOOLS. FOUR DOMAINS. ━ the kit I build with.

Tech stack — languages, ML/AI, runtime, infra


▸ TELEMETRY

statspolyglot — 8 languages

streak


contribution snake

github · x

Pinned Loading

  1. AugurAugurPublic

    Augur reads the signals. You close the deal

    TypeScript 11

  2. StructoriumStructoriumPublic

    Architecture. Automatically Enforced

    Python 12

  3. JITMINDJITMINDPublic

    JITMind is a just-in-time memory system for AI agents that combines self-editing bi-temporal memory, temporal graph reasoning, and an iterative Plan → Search → Integrate → Reflect loop for evidence…

    Python 14

  4. MoE-XtendMoE-XtendPublic

    Context Unbound. Intelligence Unleashed.

    Python 11

  5. Cadence-AICadence-AIPublic

    Moving beyond discrete tokens, we introduce continuous vector generation to deliver seamless, ultra-efficient language modeling at scale.

    Python 13

  6. OUROBOROSOUROBOROSPublic

    ResNet + learnable geometric transformation that lets the network forget/reflect features, not just add to them.

    Python 13