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Lineage: ContentType.Item -> ContentType.MailSource Library - new sources scavenged + scored (2026-09-14)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-14) | Evaluated claude-haiku-4-5 on source-extraction: Medium (judged 8 sources). Read the ledger at /sites/ResearchEnrichment/Lists/ModelEvals. | 2026-09-14T21:02:13.9301163 | |||
Source Library - new sources scavenged + scored (2026-09-14)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-14) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality https://arxiv.org/html/2608.05263 OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality # OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality CCS: Comp... [1 engine(s): Exa] [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs https://arxiv.org/abs/2608.25992 [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs # Title: ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Qual... [1 engine(s): Exa] [2606.01416] Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems https://arxiv.org/abs/2606.01416 [2606.01416] Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems [Skip to main content](#content) [](https://arxiv.org/IgnoreMe) [ : Exa] How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System - DEV Community https://dev.to/gauravstack/how-i-built-and-broke-and-fixed-a-production-multi-agent-ai-orchestration-system-264g How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System - DEV Community Gaurav Bomra Posted on Sep 11 # How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System... [1 engine(s): Exa] OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction https://aclanthology.org/2026.acl-demo.58.pdf Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 586–596 July 2-7, 2026 ©2026 Association for Computational Linguistics ## OxyGent: Making ... [1 engine(s): Exa] Beyond Task Success: An Evidence-Synthesis Framework for Evaluating, Governing, and Orchestrating Agentic AI | alphaXiv https://www.alphaxiv.org/abs/2604.19818 Beyond Task Success: An Evidence-Synthesis Framework for Evaluating, Governing, and Orchestrating Agentic AI | alphaXiv 2 / - Hide Tools Ctrl + / Open Tools ## Abstract Agentic AI systems plan, use tools, maintain... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print An enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable execution, an... [1 engine(s): Exa] Kuonirad/MCOP-Framework-2.0 https://github.com/Kuonirad/MCOP-Framework-2.0 # Repository: Kuonirad/MCOP-Framework-2.0 Verifiable reasoning substrate for reproducible agents: deterministic orchestration, Merkle provenance, and positive-impact audits. - Stars: 2 - Forks: 1 - Watchers: 1 - Open i... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-09-14T21:02:13.9049505 | |||
Captains Log - peer intel (2026-09-14)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Captains Log - peer intel (2026-09-14) | Council review for correctness. Evaluate whether these peer practices are accurately described and genuinely applicable to SPICE, flag anything wrong or already-done, and keep only the accurate, actionable lessons: Research digest: Captains intel (2026-09-14) Filed in the library - read it at /sites/ResearchEnrichment/Lists/ResearchReports. | 2026-09-14T21:02:10.9739231 | |||
Weekly improvement deck (2026-09-14)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Weekly improvement deck (2026-09-14) | <!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"/> <meta name="viewport" content="width=device-width,initial-scale=1"/> <title>SPICE self-improvement opportunities (2026-09-14)</title> <style> :root{--bg:#0b0d17;--ink:#f5f7fa;--mute:#8a93a6;--rule:#1d2235;--accent-1:#7c5cff;--accent-2:#22d3ee;--accent-3:#f472b6;--accent-4:#fbbf24;--accent-5:#34d399;--accent-6:#fb7185;} *{box-sizing:border-box;} html,body{margin:0;padding:0;} body{font-family:'Inter','SF Pro Display','Segoe UI',system-ui,-apple-system,sans-serif;background:var(--bg);color:var(--ink);font-feature-settings:'ss01','cv11';line-height:1.5;-webkit-font-smoothing:antialiased;} section.slide{position:relative;min-height:100vh;padding:6rem 8rem 8rem;display:flex;flex-direction:column;justify-content:center;border-bottom:1px solid var(--rule);animation:slideIn .5s ease both;} section.slide:nth-of-type(odd){--accent:var(--accent-1);} section.slide:nth-of-type(2n){--accent:var(--accent-2);} section.slide:nth-of-type(3n){--accent:var(--accent-3);} section.slide:nth-of-type(5n){--accent:var(--accent-4);} section.slide:nth-of-type(7n){--accent:var(--accent-5);} section.slide:nth-of-type(11n){--accent:var(--accent-6);} @keyframes slideIn{from{opacity:0;transform:translateY(20px);}to{opacity:1;transform:translateY(0);}} section.slide::before{content:'';position:absolute;left:0;top:0;bottom:0;width:6px;background:var(--accent);} section.slide .num{position:absolute;top:2rem;right:3rem;font-size:.85rem;color:var(--mute);font-variant-numeric:tabular-nums;letter-spacing:.1em;} section.slide .eyebrow{font-size:.85rem;text-transform:uppercase;letter-spacing:.2em;color:var(--accent);margin-bottom:1.5rem;font-weight:600;} section.slide h1{font-size:clamp(3rem,6vw,5rem);margin:0 0 1.5rem;line-height:1.05;font-weight:700;letter-spacing:-.02em;background:linear-gradient(135deg,var(--ink) 30%,var(--accent));-webkit-background-clip:text;background-clip:text;color:transparent;} section.slide h2{font-size:clamp(2.25rem,4.5vw,3.5rem);margin:0 0 2.5rem;line-height:1.1;font-weight:700;letter-spacing:-.02em;} section.slide .subtitle{font-size:1.35rem;color:var(--mute);font-weight:400;} section.slide ul{list-style:none;padding:0;margin:0;font-size:1.6rem;line-height:1.6;display:flex;flex-direction:column;gap:1.1rem;max-width:60rem;} section.slide li{padding-left:2.25rem;position:relative;} section.slide li::before{content:'';position:absolute;left:0;top:.7em;width:1.1rem;height:2px;background:var(--accent);} section.slide li strong{color:var(--accent);font-weight:600;} section.slide img.hero{margin-top:2.5rem;max-width:min(60rem,100%);max-height:42vh;border-radius:12px;border:1px solid var(--rule);box-shadow:0 20px 60px rgba(0,0,0,.45);object-fit:cover;} section.slide.cover{background:radial-gradient(ellipse at 20% 30%,rgba(124,92,255,.18),transparent 50%),radial-gradient(ellipse at 80% 80%,rgba(34,211,238,.12),transparent 50%),var(--bg);} section.slide.cover::before{display:none;} section.slide.cover h1{font-size:clamp(3.5rem,7vw,6rem);max-width:24ch;} section.slide.cover .meta{margin-top:3rem;display:flex;gap:2rem;color:var(--mute);font-size:.95rem;letter-spacing:.05em;} section.slide.cover .meta b{color:var(--ink);font-weight:500;margin-left:.5rem;} footer.brand{position:fixed;bottom:1.25rem;left:2rem;font-size:.75rem;color:var(--mute);letter-spacing:.15em;text-transform:uppercase;mix-blend-mode:difference;pointer-events:none;} @media (max-width:720px){section.slide{padding:4rem 2rem 6rem;}} @media print{section.slide{page-break-after:always;min-height:0;height:auto;animation:none;}} </style> </head> <body> <footer class="brand">SPICE Studio · slide deck</footer> <section class="slide cover"><span class="num">01 / 05</span><div class="eyebrow">presentation</div><h1>SPICE self-improvement opportunities (2026-09-14)</h1><div class="meta"><span>Prepared for<b>The operator and the city crew</b></span><span>By<b>SPICE Studio</b></span></div></section> <section class="slide"><span class="num">02 / 05</span><div class="eyebrow">02 — Dyalwayshappy/Spice</div><h2>Dyalwayshappy/Spice A decision brain for agentic systems: perceive context, compare options, and control execution. - Stars: 248 - Forks: 17 - Watchers: 248 - Open issues: 1 - License: Other - Homepage: https://pypi.... [1 engine(s): Exa]</h2></section> <section class="slide"><span class="num">03 / 05</span><div class="eyebrow">03 — docs/adr/adr-096-agent-loop-intelligence.md</div><h2>docs/adr/adr-096-agent-loop-intelligence.md - Branch: main - Repository: supernovae-st/nika --- --- id: ADR-096 title: "The agent-loop intelligence layer — routing, stall guard, compose, telemetry" status: accepted ... [1 engine(s): Exa]</h2></section> <section class="slide"><span class="num">04 / 05</span><div class="eyebrow">04 — README.md</div><h2>README.md - Branch: main - Repository: Dyalwayshappy/Spice --- Spice — The Decision Layer Above Agents English / 中文 > Agents can **execute**. > But they don’t know what to do ne... [1 engine(s): Exa]</h2></section> <section class="slide"><span class="num">05 / 05</span><div class="eyebrow">05 — Modern</div><h2>Modern Agent Harness Blueprint 2026 - Owner: amazingvince - Created: 2026-03-01T19:51:19Z - Public: yes - Comments: 2 - Forks: 0 ## modern-agentic-harness-blueprint-2026.md Language: Markdown # Blueprint for a Mode... [1 engine(s): Exa]</h2></section> </body> </html> | 2026-09-14T21:02:08.4222457 | |||
Weekly research digest: AI agent frameworks and LLM advances... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Weekly research digest: AI agent frameworks and LLM advances | <MailDelivered at="2026-09-14T21:02:06.5439102+00:00" from="Agency.ResearchEnrichment" subject="Weekly research digest: AI agent frameworks and LLM advances" inbox="/sites/Hub/Lists/Inbox"><Note>Delivered 'Weekly research digest: AI agent frameworks and LLM advances' to the operator's Hub inbox.</Note></MailDelivered> | 2026-09-14T21:02:06.5498788 | |||
Weekly research digest: AI agent frameworks and LLM advances... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Weekly research digest: AI agent frameworks and LLM advances | Research digest: AI agent frameworks and LLM advances Filed in the library - read it at /sites/ResearchEnrichment/Lists/ResearchReports. | 2026-09-14T21:02:06.5408101 | |||
[Echo tool-loop agent - no real LLM configured; deterministic stand-in.]... |
System Account (SPICE.Web) | Engineering | [Echo tool-loop agent - no real LLM configured; deterministic stand-in.] | [Echo tool-loop agent - no real LLM configured; deterministic stand-in.] # Task Run the shadow health review. # Tool catalog (visible to a real model) - Tool.FetchKnowledge: Fetch a knowledge slot by expression. Use this in mid-execution to pull data on demand rather than carrying everything in the front-loaded briefing. Argument: 'expression' = a Kind('arg', name=value) string. Supported kinds: ListView, SavedQuery, ActorMemory, Connector, Mcp, Vector, Graph. Configure a tool-loop-capable IToolLoopAgentProvider plugin to actually call tools. | 2026-09-14T21:00:02.8220323 | |||
Source Library - new sources scavenged + scored (2026-09-14)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-14) | Evaluated claude-haiku-4-5 on source-extraction: Medium (judged 8 sources). Read the ledger at /sites/ResearchEnrichment/Lists/ModelEvals. | 2026-09-14T20:42:34.4677464 | |||
Source Library - new sources scavenged + scored (2026-09-14)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-14) | (synthesis unavailable) ### Merged sources (8 raw hits across 3 engine(s) -> 8 unique, ranked by cross-engine agreement) OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality https://arxiv.org/html/2608.05263 OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality # OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality CCS: Comp... [1 engine(s): Exa] [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs https://arxiv.org/abs/2608.25992 [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs # Title: ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Qual... [1 engine(s): Exa] [2606.01416] Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems https://arxiv.org/abs/2606.01416 [2606.01416] Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems [Skip to main content](#content) [](https://arxiv.org/IgnoreMe) [ : Exa] How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System - DEV Community https://dev.to/gauravstack/how-i-built-and-broke-and-fixed-a-production-multi-agent-ai-orchestration-system-264g How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System - DEV Community Gaurav Bomra Posted on Sep 11 # How I Built (and Broke, and Fixed) a Production Multi-Agent AI Orchestration System... [1 engine(s): Exa] OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction https://aclanthology.org/2026.acl-demo.58.pdf Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 586–596 July 2-7, 2026 ©2026 Association for Computational Linguistics ## OxyGent: Making ... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print An enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable execution, an... [1 engine(s): Exa] Beyond Task Success: An Evidence-Synthesis Framework for Evaluating, Governing, and Orchestrating Agentic AI | alphaXiv https://www.alphaxiv.org/abs/2604.19818 Beyond Task Success: An Evidence-Synthesis Framework for Evaluating, Governing, and Orchestrating Agentic AI | alphaXiv 2 / - Hide Tools Ctrl + / Open Tools ## Abstract Agentic AI systems plan, use tools, maintain... [1 engine(s): Exa] Kuonirad/MCOP-Framework-2.0 https://github.com/Kuonirad/MCOP-Framework-2.0 # Repository: Kuonirad/MCOP-Framework-2.0 Verifiable reasoning substrate for reproducible agents: deterministic orchestration, Merkle provenance, and positive-impact audits. - Stars: 2 - Forks: 1 - Watchers: 1 - Open i... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-09-14T20:42:34.3828879 | |||
Captains Log - peer intel (2026-09-14)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Captains Log - peer intel (2026-09-14) | Council review for correctness. Evaluate whether these peer practices are accurately described and genuinely applicable to SPICE, flag anything wrong or already-done, and keep only the accurate, actionable lessons: Research digest: Captains intel (2026-09-14) Filed in the library - read it at /sites/ResearchEnrichment/Lists/ResearchReports. | 2026-09-14T20:42:32.1270575 | |||
Weekly improvement deck (2026-09-14)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Weekly improvement deck (2026-09-14) | <!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"/> <meta name="viewport" content="width=device-width,initial-scale=1"/> <title>SPICE self-improvement opportunities (2026-09-14)</title> <style> :root{--bg:#0b0d17;--ink:#f5f7fa;--mute:#8a93a6;--rule:#1d2235;--accent-1:#7c5cff;--accent-2:#22d3ee;--accent-3:#f472b6;--accent-4:#fbbf24;--accent-5:#34d399;--accent-6:#fb7185;} *{box-sizing:border-box;} html,body{margin:0;padding:0;} body{font-family:'Inter','SF Pro Display','Segoe UI',system-ui,-apple-system,sans-serif;background:var(--bg);color:var(--ink);font-feature-settings:'ss01','cv11';line-height:1.5;-webkit-font-smoothing:antialiased;} section.slide{position:relative;min-height:100vh;padding:6rem 8rem 8rem;display:flex;flex-direction:column;justify-content:center;border-bottom:1px solid var(--rule);animation:slideIn .5s ease both;} section.slide:nth-of-type(odd){--accent:var(--accent-1);} section.slide:nth-of-type(2n){--accent:var(--accent-2);} section.slide:nth-of-type(3n){--accent:var(--accent-3);} section.slide:nth-of-type(5n){--accent:var(--accent-4);} section.slide:nth-of-type(7n){--accent:var(--accent-5);} section.slide:nth-of-type(11n){--accent:var(--accent-6);} @keyframes slideIn{from{opacity:0;transform:translateY(20px);}to{opacity:1;transform:translateY(0);}} section.slide::before{content:'';position:absolute;left:0;top:0;bottom:0;width:6px;background:var(--accent);} section.slide .num{position:absolute;top:2rem;right:3rem;font-size:.85rem;color:var(--mute);font-variant-numeric:tabular-nums;letter-spacing:.1em;} section.slide .eyebrow{font-size:.85rem;text-transform:uppercase;letter-spacing:.2em;color:var(--accent);margin-bottom:1.5rem;font-weight:600;} section.slide h1{font-size:clamp(3rem,6vw,5rem);margin:0 0 1.5rem;line-height:1.05;font-weight:700;letter-spacing:-.02em;background:linear-gradient(135deg,var(--ink) 30%,var(--accent));-webkit-background-clip:text;background-clip:text;color:transparent;} section.slide h2{font-size:clamp(2.25rem,4.5vw,3.5rem);margin:0 0 2.5rem;line-height:1.1;font-weight:700;letter-spacing:-.02em;} section.slide .subtitle{font-size:1.35rem;color:var(--mute);font-weight:400;} section.slide ul{list-style:none;padding:0;margin:0;font-size:1.6rem;line-height:1.6;display:flex;flex-direction:column;gap:1.1rem;max-width:60rem;} section.slide li{padding-left:2.25rem;position:relative;} section.slide li::before{content:'';position:absolute;left:0;top:.7em;width:1.1rem;height:2px;background:var(--accent);} section.slide li strong{color:var(--accent);font-weight:600;} section.slide img.hero{margin-top:2.5rem;max-width:min(60rem,100%);max-height:42vh;border-radius:12px;border:1px solid var(--rule);box-shadow:0 20px 60px rgba(0,0,0,.45);object-fit:cover;} section.slide.cover{background:radial-gradient(ellipse at 20% 30%,rgba(124,92,255,.18),transparent 50%),radial-gradient(ellipse at 80% 80%,rgba(34,211,238,.12),transparent 50%),var(--bg);} section.slide.cover::before{display:none;} section.slide.cover h1{font-size:clamp(3.5rem,7vw,6rem);max-width:24ch;} section.slide.cover .meta{margin-top:3rem;display:flex;gap:2rem;color:var(--mute);font-size:.95rem;letter-spacing:.05em;} section.slide.cover .meta b{color:var(--ink);font-weight:500;margin-left:.5rem;} footer.brand{position:fixed;bottom:1.25rem;left:2rem;font-size:.75rem;color:var(--mute);letter-spacing:.15em;text-transform:uppercase;mix-blend-mode:difference;pointer-events:none;} @media (max-width:720px){section.slide{padding:4rem 2rem 6rem;}} @media print{section.slide{page-break-after:always;min-height:0;height:auto;animation:none;}} </style> </head> <body> <footer class="brand">SPICE Studio · slide deck</footer> <section class="slide cover"><span class="num">01 / 05</span><div class="eyebrow">presentation</div><h1>SPICE self-improvement opportunities (2026-09-14)</h1><div class="meta"><span>Prepared for<b>The operator and the city crew</b></span><span>By<b>SPICE Studio</b></span></div></section> <section class="slide"><span class="num">02 / 05</span><div class="eyebrow">02 — Dyalwayshappy/Spice</div><h2>Dyalwayshappy/Spice A decision brain for agentic systems: perceive context, compare options, and control execution. - Stars: 248 - Forks: 17 - Watchers: 248 - Open issues: 1 - License: Other - Homepage: https://pypi.... [1 engine(s): Exa]</h2></section> <section class="slide"><span class="num">03 / 05</span><div class="eyebrow">03 — docs/adr/adr-096-agent-loop-intelligence.md</div><h2>docs/adr/adr-096-agent-loop-intelligence.md - Branch: main - Repository: supernovae-st/nika --- --- id: ADR-096 title: "The agent-loop intelligence layer — routing, stall guard, compose, telemetry" status: accepted ... [1 engine(s): Exa]</h2></section> <section class="slide"><span class="num">04 / 05</span><div class="eyebrow">04 — README.md</div><h2>README.md - Branch: main - Repository: Dyalwayshappy/Spice --- Spice — The Decision Layer Above Agents English / 中文 > Agents can **execute**. > But they don’t know what to do ne... [1 engine(s): Exa]</h2></section> <section class="slide"><span class="num">05 / 05</span><div class="eyebrow">05 — Modern</div><h2>Modern Agent Harness Blueprint 2026 - Owner: amazingvince - Created: 2026-03-01T19:51:19Z - Public: yes - Comments: 2 - Forks: 0 ## modern-agentic-harness-blueprint-2026.md Language: Markdown # Blueprint for a Mode... [1 engine(s): Exa]</h2></section> </body> </html> | 2026-09-14T20:42:29.8439231 | |||
Weekly research digest: AI agent frameworks and LLM advances... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Weekly research digest: AI agent frameworks and LLM advances | <MailDelivered at="2026-09-14T20:42:28.3857040+00:00" from="Agency.ResearchEnrichment" subject="Weekly research digest: AI agent frameworks and LLM advances" inbox="/sites/Hub/Lists/Inbox"><Note>Delivered 'Weekly research digest: AI agent frameworks and LLM advances' to the operator's Hub inbox.</Note></MailDelivered> | 2026-09-14T20:42:28.3905926 | |||
Weekly research digest: AI agent frameworks and LLM advances... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Weekly research digest: AI agent frameworks and LLM advances | Research digest: AI agent frameworks and LLM advances Filed in the library - read it at /sites/ResearchEnrichment/Lists/ResearchReports. | 2026-09-14T20:42:28.3836385 | |||
I am an AI assistant and do not have a physical body, biological functio…... |
System Account (SPICE.Web) | Engineering | I am an AI assistant and do not have a physical body, biological functio… | I am an AI assistant and do not have a physical body, biological functions, or a medical history. Therefore, I cannot undergo a "shadow health review," which is typically a holistic or alternative medicine practice involving the visualization of energy fields to identify potential health imbalances. If you are interested in learning more about shadow health reviews for human health, I can provide information on what they are, how they are conducted, or their proposed benefits and limitations within the context of alternative wellness practices. Alternatively, if you have questions about general health, wellness, or AI capabilities, I am happy to help with those. | 2026-09-14T20:39:03.4875032 | |||
[Echo tool-loop agent - no real LLM configured; deterministic stand-in.]... |
System Account (SPICE.Web) | Engineering | [Echo tool-loop agent - no real LLM configured; deterministic stand-in.] | [Echo tool-loop agent - no real LLM configured; deterministic stand-in.] # Task Run the shadow health review. # Tool catalog (visible to a real model) - Tool.FetchKnowledge: Fetch a knowledge slot by expression. Use this in mid-execution to pull data on demand rather than carrying everything in the front-loaded briefing. Argument: 'expression' = a Kind('arg', name=value) string. Supported kinds: ListView, SavedQuery, ActorMemory, Connector, Mcp, Vector, Graph. Configure a tool-loop-capable IToolLoopAgentProvider plugin to actually call tools. | 2026-09-07T17:58:02.7499506 | |||
[Echo tool-loop agent - no real LLM configured; deterministic stand-in.]... |
System Account (SPICE.Web) | Engineering | [Echo tool-loop agent - no real LLM configured; deterministic stand-in.] | [Echo tool-loop agent - no real LLM configured; deterministic stand-in.] # Task Run the shadow health review. # Tool catalog (visible to a real model) - Tool.FetchKnowledge: Fetch a knowledge slot by expression. Use this in mid-execution to pull data on demand rather than carrying everything in the front-loaded briefing. Argument: 'expression' = a Kind('arg', name=value) string. Supported kinds: ListView, SavedQuery, ActorMemory, Connector, Mcp, Vector, Graph. Configure a tool-loop-capable IToolLoopAgentProvider plugin to actually call tools. | 2026-09-07T15:38:01.9937712 | |||
[Echo tool-loop agent - no real LLM configured; deterministic stand-in.]... |
System Account (SPICE.Web) | Engineering | [Echo tool-loop agent - no real LLM configured; deterministic stand-in.] | [Echo tool-loop agent - no real LLM configured; deterministic stand-in.] # Task Run the shadow health review. # Tool catalog (visible to a real model) - Tool.FetchKnowledge: Fetch a knowledge slot by expression. Use this in mid-execution to pull data on demand rather than carrying everything in the front-loaded briefing. Argument: 'expression' = a Kind('arg', name=value) string. Supported kinds: ListView, SavedQuery, ActorMemory, Connector, Mcp, Vector, Graph. Configure a tool-loop-capable IToolLoopAgentProvider plugin to actually call tools. | 2026-09-07T15:32:02.1670341 | |||
Source Library - new sources scavenged + scored (2026-09-07)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-07) | Evaluated claude-haiku-4-5 on source-extraction: Medium (judged 8 sources). Read the ledger at /sites/ResearchEnrichment/Lists/ModelEvals. | 2026-09-07T15:28:28.0326371 | |||
Source Library - new sources scavenged + scored (2026-09-07)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-07) | (synthesis unavailable) ### Merged sources (6 raw hits across 3 engine(s) -> 6 unique, ranked by cross-engine agreement) OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality https://arxiv.org/html/2608.05263 OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality # OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality CCS: Comp... [1 engine(s): Exa] [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs https://arxiv.org/abs/2608.25992 [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs # Title: ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Qual... [1 engine(s): Exa] OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction https://aclanthology.org/2026.acl-demo.58.pdf Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 586–596 July 2-7, 2026 ©2026 Association for Computational Linguistics ## OxyGent: Making ... [1 engine(s): Exa] Kuonirad/MCOP-Framework-2.0 https://github.com/Kuonirad/MCOP-Framework-2.0 # Repository: Kuonirad/MCOP-Framework-2.0 Verifiable reasoning substrate for reproducible agents: deterministic orchestration, Merkle provenance, and positive-impact audits. - Stars: 2 - Forks: 1 - Watchers: 1 - Open i... [1 engine(s): Exa] Scaling LLM-Driven Multi-Agent Systems:Design Principles and Architectural Scalability Analysis https://arxiv.org/abs/2607.27942 Scaling LLM-Driven Multi-Agent Systems:Design Principles and Architectural Scalability Analysis # Scaling LLM-Driven Multi-Agent Systems: Design Principles and Architectural Scalability Analysis Linus Sander Affiliati... 6. https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents arXiv is now an independent nonprofit! Learn more× 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Instit... [1 engine(s): Exa] Building Agentic Orchestration with MCP, A2A, ACP, LangGraph https://zenithlaw.com/building-agentic-orchestration-mcp-a2a-langgraph-langchain-playbook Building Agentic Orchestration with MCP, A2A, ACP, LangGraph Listen Print An enterprise agentic orchestration stack needs clear protocol boundaries, durable workflow control, typed interfaces, observable execution, an... 8. https://arxiv.org/pdf/2604.17009 Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition arXiv is now an independent nonprofit! Learn more× # Small Model as Master Orchestrator: Learning Unifie... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-09-07T15:28:27.9895925 | |||
Captains Log - peer intel (2026-09-07)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Captains Log - peer intel (2026-09-07) | Council review for correctness. Evaluate whether these peer practices are accurately described and genuinely applicable to SPICE, flag anything wrong or already-done, and keep only the accurate, actionable lessons: Research digest: Captains intel (2026-09-07) Filed in the library - read it at /sites/ResearchEnrichment/Lists/ResearchReports. | 2026-09-07T15:28:26.3579951 | |||
Weekly improvement deck (2026-09-07)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Weekly improvement deck (2026-09-07) | <!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"/> <meta name="viewport" content="width=device-width,initial-scale=1"/> <title>SPICE self-improvement opportunities (2026-09-07)</title> <style> :root{--bg:#0b0d17;--ink:#f5f7fa;--mute:#8a93a6;--rule:#1d2235;--accent-1:#7c5cff;--accent-2:#22d3ee;--accent-3:#f472b6;--accent-4:#fbbf24;--accent-5:#34d399;--accent-6:#fb7185;} *{box-sizing:border-box;} html,body{margin:0;padding:0;} body{font-family:'Inter','SF Pro Display','Segoe UI',system-ui,-apple-system,sans-serif;background:var(--bg);color:var(--ink);font-feature-settings:'ss01','cv11';line-height:1.5;-webkit-font-smoothing:antialiased;} section.slide{position:relative;min-height:100vh;padding:6rem 8rem 8rem;display:flex;flex-direction:column;justify-content:center;border-bottom:1px solid var(--rule);animation:slideIn .5s ease both;} section.slide:nth-of-type(odd){--accent:var(--accent-1);} section.slide:nth-of-type(2n){--accent:var(--accent-2);} section.slide:nth-of-type(3n){--accent:var(--accent-3);} section.slide:nth-of-type(5n){--accent:var(--accent-4);} section.slide:nth-of-type(7n){--accent:var(--accent-5);} section.slide:nth-of-type(11n){--accent:var(--accent-6);} @keyframes slideIn{from{opacity:0;transform:translateY(20px);}to{opacity:1;transform:translateY(0);}} section.slide::before{content:'';position:absolute;left:0;top:0;bottom:0;width:6px;background:var(--accent);} section.slide .num{position:absolute;top:2rem;right:3rem;font-size:.85rem;color:var(--mute);font-variant-numeric:tabular-nums;letter-spacing:.1em;} section.slide .eyebrow{font-size:.85rem;text-transform:uppercase;letter-spacing:.2em;color:var(--accent);margin-bottom:1.5rem;font-weight:600;} section.slide h1{font-size:clamp(3rem,6vw,5rem);margin:0 0 1.5rem;line-height:1.05;font-weight:700;letter-spacing:-.02em;background:linear-gradient(135deg,var(--ink) 30%,var(--accent));-webkit-background-clip:text;background-clip:text;color:transparent;} section.slide h2{font-size:clamp(2.25rem,4.5vw,3.5rem);margin:0 0 2.5rem;line-height:1.1;font-weight:700;letter-spacing:-.02em;} section.slide .subtitle{font-size:1.35rem;color:var(--mute);font-weight:400;} section.slide ul{list-style:none;padding:0;margin:0;font-size:1.6rem;line-height:1.6;display:flex;flex-direction:column;gap:1.1rem;max-width:60rem;} section.slide li{padding-left:2.25rem;position:relative;} section.slide li::before{content:'';position:absolute;left:0;top:.7em;width:1.1rem;height:2px;background:var(--accent);} section.slide li strong{color:var(--accent);font-weight:600;} section.slide img.hero{margin-top:2.5rem;max-width:min(60rem,100%);max-height:42vh;border-radius:12px;border:1px solid var(--rule);box-shadow:0 20px 60px rgba(0,0,0,.45);object-fit:cover;} section.slide.cover{background:radial-gradient(ellipse at 20% 30%,rgba(124,92,255,.18),transparent 50%),radial-gradient(ellipse at 80% 80%,rgba(34,211,238,.12),transparent 50%),var(--bg);} section.slide.cover::before{display:none;} section.slide.cover h1{font-size:clamp(3.5rem,7vw,6rem);max-width:24ch;} section.slide.cover .meta{margin-top:3rem;display:flex;gap:2rem;color:var(--mute);font-size:.95rem;letter-spacing:.05em;} section.slide.cover .meta b{color:var(--ink);font-weight:500;margin-left:.5rem;} footer.brand{position:fixed;bottom:1.25rem;left:2rem;font-size:.75rem;color:var(--mute);letter-spacing:.15em;text-transform:uppercase;mix-blend-mode:difference;pointer-events:none;} @media (max-width:720px){section.slide{padding:4rem 2rem 6rem;}} @media print{section.slide{page-break-after:always;min-height:0;height:auto;animation:none;}} </style> </head> <body> <footer class="brand">SPICE Studio · slide deck</footer> <section class="slide cover"><span class="num">01 / 04</span><div class="eyebrow">presentation</div><h1>SPICE self-improvement opportunities (2026-09-07)</h1><div class="meta"><span>Prepared for<b>The operator and the city crew</b></span><span>By<b>SPICE Studio</b></span></div></section> <section class="slide"><span class="num">02 / 04</span><div class="eyebrow">02 — docs/adr/adr-096-agent-loop-intelligence.md</div><h2>docs/adr/adr-096-agent-loop-intelligence.md - Branch: main - Repository: supernovae-st/nika --- --- id: ADR-096 title: "The agent-loop intelligence layer — routing, stall guard, compose, telemetry" status: accepted ... [1 engine(s): Exa]</h2></section> <section class="slide"><span class="num">03 / 04</span><div class="eyebrow">03 — laikey/Spice</div><h2>laikey/Spice A decision brain for agentic systems: perceive context, compare options, and control execution. - Stars: 0 - Forks: 0 - Watchers: 0 - Open issues: 0 - License: Other - Homepage: https://pypi.org/project/... [1 engine(s): Exa]</h2></section> <section class="slide"><span class="num">04 / 04</span><div class="eyebrow">04 — 03_system_design/2026-agentic-ai-system-design.md</div><h2>03_system_design/2026-agentic-ai-system-design.md - Branch: main - Repository: alirezadir/Agentic-AI-Systems --- # 2026 Agentic AI System Design Update This page summarizes the 2026 shift in agentic AI system desig... [1 engine(s): Exa]</h2></section> </body> </html> | 2026-09-07T15:28:24.4835459 | |||
Weekly research digest: AI agent frameworks and LLM advances... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Weekly research digest: AI agent frameworks and LLM advances | <MailDelivered at="2026-09-07T15:28:23.1426917+00:00" from="Agency.ResearchEnrichment" subject="Weekly research digest: AI agent frameworks and LLM advances" inbox="/sites/Hub/Lists/Inbox"><Note>Delivered 'Weekly research digest: AI agent frameworks and LLM advances' to the operator's Hub inbox.</Note></MailDelivered> | 2026-09-07T15:28:23.1470563 | |||
Weekly research digest: AI agent frameworks and LLM advances... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Weekly research digest: AI agent frameworks and LLM advances | Research digest: AI agent frameworks and LLM advances Filed in the library - read it at /sites/ResearchEnrichment/Lists/ResearchReports. | 2026-09-07T15:28:23.1406469 | |||
[Echo tool-loop agent - no real LLM configured; deterministic stand-in.]... |
System Account (SPICE.Web) | Engineering | [Echo tool-loop agent - no real LLM configured; deterministic stand-in.] | [Echo tool-loop agent - no real LLM configured; deterministic stand-in.] # Task Run the shadow health review. # Tool catalog (visible to a real model) - Tool.FetchKnowledge: Fetch a knowledge slot by expression. Use this in mid-execution to pull data on demand rather than carrying everything in the front-loaded briefing. Argument: 'expression' = a Kind('arg', name=value) string. Supported kinds: ListView, SavedQuery, ActorMemory, Connector, Mcp, Vector, Graph. Configure a tool-loop-capable IToolLoopAgentProvider plugin to actually call tools. | 2026-09-07T15:22:02.7453338 | |||
{"creates": [], "updates": [], "deletes": []}... |
System Account (SPICE.Web) | Engineering | {"creates": [], "updates": [], "deletes": []} | {"creates": [], "updates": [], "deletes": []} | 2026-09-07T15:02:54.3820351 | |||
{"creates": [], "updates": [], "deletes": []}... |
System Account (SPICE.Web) | Engineering | {"creates": [], "updates": [], "deletes": []} | {"creates": [], "updates": [], "deletes": []} | 2026-09-07T15:00:48.8556332 | |||
Source Library - new sources scavenged + scored (2026-09-07)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-07) | Evaluated claude-haiku-4-5 on source-extraction: Medium (judged 8 sources). Read the ledger at /sites/ResearchEnrichment/Lists/ModelEvals. | 2026-09-07T12:50:16.4547178 | |||
Source Library - new sources scavenged + scored (2026-09-07)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Source Library - new sources scavenged + scored (2026-09-07) | (synthesis unavailable) ### Merged sources (6 raw hits across 3 engine(s) -> 6 unique, ranked by cross-engine agreement) OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality https://arxiv.org/html/2608.05263 OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality # OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality CCS: Comp... [1 engine(s): Exa] [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs https://arxiv.org/abs/2608.25992 [2608.25992] ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs # Title: ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Qual... [1 engine(s): Exa] OxyGent: Making Multi-Agent Systems Modular, Observable, and Evolvable via Oxy Abstraction https://aclanthology.org/2026.acl-demo.58.pdf Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 586–596 July 2-7, 2026 ©2026 Association for Computational Linguistics ## OxyGent: Making ... [1 engine(s): Exa] Scaling LLM-Driven Multi-Agent Systems:Design Principles and Architectural Scalability Analysis https://arxiv.org/abs/2607.27942 Scaling LLM-Driven Multi-Agent Systems:Design Principles and Architectural Scalability Analysis # Scaling LLM-Driven Multi-Agent Systems: Design Principles and Architectural Scalability Analysis Linus Sander Affiliati... 5. https://arxiv.org/pdf/2603.09716 AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents arXiv is now an independent nonprofit! Learn more× 1]MemTensor (Shanghai) Technology Co., Ltd. 2]Shanghai Jiao Tong University 3]Instit... 6. https://arxiv.org/pdf/2604.17009 Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition arXiv is now an independent nonprofit! Learn more× # Small Model as Master Orchestrator: Learning Unifie... [1 engine(s): Exa] AI Agent Systems: Architectures, Applications, and Evaluation https://arxiv.org/html/2601.01743v1 AI Agent Systems: Architectures, Applications, and Evaluation arXiv is now an independent nonprofit! Learn more× # AI Agent Systems: Architectures, Applications, and Evaluation Journal: JACM Bin Xu ORCID 0009-0001-26... [1 engine(s): Exa] Kuonirad/MCOP-Framework-2.0 https://github.com/Kuonirad/MCOP-Framework-2.0 # Repository: Kuonirad/MCOP-Framework-2.0 Verifiable reasoning substrate for reproducible agents: deterministic orchestration, Merkle provenance, and positive-impact audits. - Stars: 2 - Forks: 1 - Watchers: 1 - Open i... [1 engine(s): Exa] --- Fact-check --- (verification unavailable) Researched 1 source set(s) across 1 angle(s). Confidence: Low | 2026-09-07T12:50:16.4306790 | |||
Captains Log - peer intel (2026-09-07)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Captains Log - peer intel (2026-09-07) | Council review for correctness. Evaluate whether these peer practices are accurately described and genuinely applicable to SPICE, flag anything wrong or already-done, and keep only the accurate, actionable lessons: Research digest: Captains intel (2026-09-07) Filed in the library - read it at /sites/ResearchEnrichment/Lists/ResearchReports. | 2026-09-07T12:50:13.4398112 | |||
Weekly improvement deck (2026-09-07)... |
System Account (SPICE.Web) | Agency.ResearchEnrichment | Weekly improvement deck (2026-09-07) | <!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"/> <meta name="viewport" content="width=device-width,initial-scale=1"/> <title>SPICE self-improvement opportunities (2026-09-07)</title> <style> :root{--bg:#0b0d17;--ink:#f5f7fa;--mute:#8a93a6;--rule:#1d2235;--accent-1:#7c5cff;--accent-2:#22d3ee;--accent-3:#f472b6;--accent-4:#fbbf24;--accent-5:#34d399;--accent-6:#fb7185;} *{box-sizing:border-box;} html,body{margin:0;padding:0;} body{font-family:'Inter','SF Pro Display','Segoe UI',system-ui,-apple-system,sans-serif;background:var(--bg);color:var(--ink);font-feature-settings:'ss01','cv11';line-height:1.5;-webkit-font-smoothing:antialiased;} section.slide{position:relative;min-height:100vh;padding:6rem 8rem 8rem;display:flex;flex-direction:column;justify-content:center;border-bottom:1px solid var(--rule);animation:slideIn .5s ease both;} section.slide:nth-of-type(odd){--accent:var(--accent-1);} section.slide:nth-of-type(2n){--accent:var(--accent-2);} section.slide:nth-of-type(3n){--accent:var(--accent-3);} section.slide:nth-of-type(5n){--accent:var(--accent-4);} section.slide:nth-of-type(7n){--accent:var(--accent-5);} section.slide:nth-of-type(11n){--accent:var(--accent-6);} @keyframes slideIn{from{opacity:0;transform:translateY(20px);}to{opacity:1;transform:translateY(0);}} section.slide::before{content:'';position:absolute;left:0;top:0;bottom:0;width:6px;background:var(--accent);} section.slide .num{position:absolute;top:2rem;right:3rem;font-size:.85rem;color:var(--mute);font-variant-numeric:tabular-nums;letter-spacing:.1em;} section.slide .eyebrow{font-size:.85rem;text-transform:uppercase;letter-spacing:.2em;color:var(--accent);margin-bottom:1.5rem;font-weight:600;} section.slide h1{font-size:clamp(3rem,6vw,5rem);margin:0 0 1.5rem;line-height:1.05;font-weight:700;letter-spacing:-.02em;background:linear-gradient(135deg,var(--ink) 30%,var(--accent));-webkit-background-clip:text;background-clip:text;color:transparent;} section.slide h2{font-size:clamp(2.25rem,4.5vw,3.5rem);margin:0 0 2.5rem;line-height:1.1;font-weight:700;letter-spacing:-.02em;} section.slide .subtitle{font-size:1.35rem;color:var(--mute);font-weight:400;} section.slide ul{list-style:none;padding:0;margin:0;font-size:1.6rem;line-height:1.6;display:flex;flex-direction:column;gap:1.1rem;max-width:60rem;} section.slide li{padding-left:2.25rem;position:relative;} section.slide li::before{content:'';position:absolute;left:0;top:.7em;width:1.1rem;height:2px;background:var(--accent);} section.slide li strong{color:var(--accent);font-weight:600;} section.slide img.hero{margin-top:2.5rem;max-width:min(60rem,100%);max-height:42vh;border-radius:12px;border:1px solid var(--rule);box-shadow:0 20px 60px rgba(0,0,0,.45);object-fit:cover;} section.slide.cover{background:radial-gradient(ellipse at 20% 30%,rgba(124,92,255,.18),transparent 50%),radial-gradient(ellipse at 80% 80%,rgba(34,211,238,.12),transparent 50%),var(--bg);} section.slide.cover::before{display:none;} section.slide.cover h1{font-size:clamp(3.5rem,7vw,6rem);max-width:24ch;} section.slide.cover .meta{margin-top:3rem;display:flex;gap:2rem;color:var(--mute);font-size:.95rem;letter-spacing:.05em;} section.slide.cover .meta b{color:var(--ink);font-weight:500;margin-left:.5rem;} footer.brand{position:fixed;bottom:1.25rem;left:2rem;font-size:.75rem;color:var(--mute);letter-spacing:.15em;text-transform:uppercase;mix-blend-mode:difference;pointer-events:none;} @media (max-width:720px){section.slide{padding:4rem 2rem 6rem;}} @media print{section.slide{page-break-after:always;min-height:0;height:auto;animation:none;}} </style> </head> <body> <footer class="brand">SPICE Studio · slide deck</footer> <section class="slide cover"><span class="num">01 / 04</span><div class="eyebrow">presentation</div><h1>SPICE self-improvement opportunities (2026-09-07)</h1><div class="meta"><span>Prepared for<b>The operator and the city crew</b></span><span>By<b>SPICE Studio</b></span></div></section> <section class="slide"><span class="num">02 / 04</span><div class="eyebrow">02 — docs/adr/adr-096-agent-loop-intelligence.md</div><h2>docs/adr/adr-096-agent-loop-intelligence.md - Branch: main - Repository: supernovae-st/nika --- --- id: ADR-096 title: "The agent-loop intelligence layer — routing, stall guard, compose, telemetry" status: accepted ... [1 engine(s): Exa]</h2></section> <section class="slide"><span class="num">03 / 04</span><div class="eyebrow">03 — laikey/Spice</div><h2>laikey/Spice A decision brain for agentic systems: perceive context, compare options, and control execution. - Stars: 0 - Forks: 0 - Watchers: 0 - Open issues: 0 - License: Other - Homepage: https://pypi.org/project/... [1 engine(s): Exa]</h2></section> <section class="slide"><span class="num">04 / 04</span><div class="eyebrow">04 — 03_system_design/2026-agentic-ai-system-design.md</div><h2>03_system_design/2026-agentic-ai-system-design.md - Branch: main - Repository: alirezadir/Agentic-AI-Systems --- # 2026 Agentic AI System Design Update This page summarizes the 2026 shift in agentic AI system desig... [1 engine(s): Exa]</h2></section> </body> </html> | 2026-09-07T12:50:10.8268744 |