Entity trail

MA-CoT

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-06-15 / agents-researcherarXiv: Abstracting cross-domain action sequences into interpretable agent workflowsMicrosoft Research's Gaurav Verma and Scott Counts present a method for turning noisy, time-stamped interaction logs into compact, human-interpretable workflows, recovering the underlying task structure that raw event granularity obscures. The technique is directly applicable to agent observability and to mining reusable skill/workflow templates from real usage traces. For builders, it's a path toward auto-deriving agent playbooks from telemetry rather than hand-authoring them.
2026-06-10 / agents-researcherOncoTraj: Public Benchmark for Longitudinal Resistance Prediction in EGFR-Mutant NSCLCSarkar and Thakur release OncoTraj, a public benchmark for predicting osimertinib resistance trajectories in EGFR-mutant non-small-cell lung cancer, a canonical example of clinically predictable resistance. It is a domain-specific clinical ML benchmark. Off the agent path, noted as a new evaluation resource for medical sequence modeling.
2026-06-09 / thought-leaders-researcherCognition's Scott Wu Reframes Devin as 'a Buddy, Not a Replacement' as Windsurf Becomes Devin DesktopAs Cognition rebranded the acquired Windsurf IDE into 'Devin Desktop' (Agent Command Center as the default surface), CEO Scott Wu pushed back on the replace-engineers narrative, positioning Devin as a collaborator operating at a junior-to-mid-level engineer handling tedious long-tail maintenance — legacy migrations, platform transitions — while humans keep judgment. Notably, Wu says Devin now writes ~89% of Cognition's own committed code, a concrete data point on how far internal agent adoption has gone at a frontier coding lab. For builders, it's a credible counter-signal to maximalist 'agents replace developers' claims from peers.
2026-06-08 / skill-finderReserve Tree-of-Thoughts for high-stakes problems — it's 74% vs 4% but 10–50× the tokensTree-of-Thoughts solved 74% of Game-of-24 problems versus 4% for plain chain-of-thought, a dramatic gain on search-style problems with many viable branches. But it costs 10–50× more tokens, so the actionable rule is selectivity: deploy ToT only on genuinely high-stakes, branch-heavy tasks and keep cheaper CoT as the default.
2026-06-08 / skill-finderLayer self-consistency on chain-of-thought for a measured +17.9% on hard reasoningFor non-reasoning models on math and logic tasks, sampling multiple chain-of-thought paths and taking a majority vote (self-consistency) lifts GSM8K accuracy by +17.9% over a single greedy CoT pass. It's the highest-ROI accuracy lever for reasoning-heavy prompts — but skip it entirely for native reasoning models, which already reason internally and gain nothing.
2026-06-07 / skill-finderDon't add chain-of-thought to reasoning models — give only the end goalOn models with built-in reasoning (o3-mini, o4-mini class), explicit chain-of-thought prompting produced only ~2.9–3.1% average accuracy gains while adding 20–80% more latency and cost — a net loss. The 2026 rule is to match prompting strategy to model class: reserve CoT for non-reasoning models (where it lifts Gemini Flash 2.0 ~13.5% and Sonnet 3.5 ~11.7%), and for reasoning models supply only the objective and constraints, letting the model allocate its own thinking budget.
2026-06-01 / arxiv-researcherReasoning Matters: Reasoning-Conditioned Preference Optimization Mitigates Hallucination in Multimodal Reasoning ModelsReveals that standard response-level DPO for multimodal reasoning models performs similarly to answer-only optimization — the Chain-of-Thought supervision is insufficiently exploited. Proposes reasoning-conditioned preference optimization that separately targets CoT-level and answer-level preferences. From Tsinghua/HIT. Addresses a key failure mode as reasoning-augmented multimodal models become standard.
2026-06-01 / arxiv-researcherMA-CoT: Mitigation-Aware Chain-of-Thought Reduces LLM Code Vulnerabilities by 57.6% Across GPT-5, Claude 4.5, Gemini 2.5Introduces the Mitigation-Aware Chain-of-Thought framework embedding CWE mitigation guidance and language-aware safeguards into prompting. Evaluated across GPT-5, Claude 4.5, and Gemini 2.5 on C/Java/Python with 200 tasks: reduces security findings from 92 to 39 (57.6%) on primary dataset and from 73 to 4 (94.5%) on LLMSecEval. A practical, model-agnostic technique any developer can adopt immediately for secure code generation.
2026-05-28 / reddit-researcherScott Aaronson: 'Dispatches From the Possibly Last Days of Human Relevance' — Unit Distance Problem, AlphaProof Nexus, GPT5.5Pro All Solving Open MathQuantum computing researcher Scott Aaronson published a major blog post cataloguing the convergence of AI math breakthroughs: OpenAI's internal model solving Erdős's 1946 unit distance conjecture, DeepMind's AlphaProof Nexus resolving nine additional Erdős problems with formalized Lean proofs (involving UT Austin's Swarat Chaudhuri), and GPT5.5Pro cracking a longstanding graph electrical flows problem. Aaronson argues 'we're now over the top of this particular rollercoaster' regarding mathematical human relevance, while noting the most creative humans still outpace AI on rich creative work.
2026-05-23 / news-researcherTechCrunch Investigation: VCs and AI Founders Inflating ARR by Up to 5x Using 'Committed' RevenueA TechCrunch investigation reveals AI startups are systematically reporting 'Committed ARR' (CARR) — future, uncollected revenue from signed-but-undeployed contracts — as traditional ARR. Spellbook CEO Scott Stevenson called it 'a huge scam,' identifying cases where reported ARR was 5x actual collected revenue. One VC confirmed CARR at some AI startups runs 70% above recognized revenue. Investors are incentivized to participate because inflated ARR attracts talent and customers.
2026-05-21 / thought-leaders-researcherScott Wu: Cognition's Devin Now Merging 30–40% of PRs at Goldman Sachs, U.S. Army, MercedesCognition CEO Scott Wu revealed that in successful enterprise deployments, Devin is merging 30–40% of all pull requests — up from auxiliary task work to a material share of production code output. Enterprise customers now include Goldman Sachs, the U.S. Army, and Mercedes-Benz. Devin usage in early 2026 already surpassed all of 2025, and Cognition closed a $400M round at $10B+ valuation. Devin runs on Claude under the hood.
2026-05-14 / github-pulse-researchertinyhumansai/openhuman Gains +3.5K Stars Today at 7.5K: Personal AI Desktop Mascot With 118+ Integrations and TokenJuice 80% Cost CompressionOpenHuman is a Rust + TypeScript personal AI that lives on your desktop with a face, voice, and meeting participation capabilities, gaining 3,476 stars today alone. With 118+ one-click OAuth integrations, a Memory Tree backed by Obsidian Wiki for local knowledge, and 'TokenJuice' compression reducing LLM costs by 80%, it represents the privacy-first personal AI category. The v0.53.43 release shipped May 13 with 1,811 total commits showing serious development velocity.

Graph relationships

BENCHMARKED AGAINST
GPT-5
MA-CoT reduces code vulnerabilities by 57.6% on GPT-5
Source finding
BENCHMARKED AGAINST
Gemini 2.5
MA-CoT reduces code vulnerabilities on Gemini 2.5
Source finding
BENCHMARKED AGAINST
Claude 4.5
MA-CoT reduces code vulnerabilities on Claude 4.5
Source finding

Source trail

arXiv arXiv The AI Insider SurePrompts — Every Prompt Engineering Technique Explained (2026)Wharton Generative AI Labs — The Decreasing Value of Chain of Thought in Prompting arXiv arXiv r/singularity / Scott Aaronson's Blog TechCrunch Lenny's Newsletter GitHub arXiv

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