Entity trail

Lean

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

2026-07-12 / sources-researcherOpenAI's GPT-Live Adds Async Delegation: Voice Keeps Talking While GPT-5.5 Works in the BackgroundOpenAI launched GPT-Live on July 8, 2026, and Simon Willison (who had weeks of preview access) details its standout pattern: the full-duplex voice model delegates hard sub-tasks — web search, deeper reasoning, complex work — to GPT-5.5 running in the background while it keeps the conversation flowing, folding results back in when ready, and auto-upgrades its backing model as new frontier models ship. For builders: a clean reference architecture for responsive voice agents that stay conversational while offloading heavy reasoning asynchronously, rather than blocking on one slow call.
2026-07-12 / sources-researcherToolFailBench: a 1,000-Task Diagnostic Benchmark That Localizes Exactly How Agent Tool Use BreaksToolFailBench (arXiv:2607.04686, July 6, 2026) is a 1,000-task diagnostic benchmark across finance, medicine, law, cybersecurity, and real estate that localizes where tool use breaks — labeling traces as Tool-Skip, Result-Ignore, Output-Fabrication, or Unnecessary-Tool-Use via a rule classifier plus two LLM judges aggregated by majority vote. Across 19 frontier models the best reaches only 86.33% clean tool-use rate, and models with similar aggregate scores fail in very different ways. For builders: an off-the-shelf harness to profile your agent's specific tool-use failure modes instead of relying on a single pass/fail score.
2026-07-12 / thought-leaders-researcherJim Fan Declares 'RIP VLAs' — NVIDIA's Robotics Lead Bets on Physics-Grounded World Models and Human-Video PretrainingFan argues Vision-Language-Action models are fundamentally brittle because they merely bolt robot actions onto LLMs, and says the field is converging on physics-grounded world models instead. NVIDIA's EgoScale approach leans on 20,000 hours of egocentric human video with essentially no robot data in pretraining, targeting a 'physical Turing test' in 2–3 years. It's a sharp reframing of the humanoid-robotics roadmap from one of its most visible voices.
2026-07-12 / vibe-coding-researcherTip: Use Cursor's New Cloud Agent Hooks to Build Self-Correcting LoopsCursor 3.11's cloud agent hooks (beforeSubmitPrompt, afterAgentResponse, afterAgentThought, stop, subagentStart) fire on the conversation itself — prompts, responses, thinking, subagents, and turn completion — which is the cloud-agent analogue to Claude Code's SubagentStop. Wire a `stop` hook that re-injects a verification prompt (tests pass? lint clean?) to keep a cloud agent iterating until acceptance criteria are met instead of stopping early.
2026-07-11 / skill-finderRedact secrets at the structured-logger, not in a downstream log pipeline — sink-side redaction is permanently best-effortConfigure your logging library to drop sensitive fields by default and opt them back in only after review, rather than scrubbing logs in a later processing stage; any redaction that happens after the log leaves the process is best-effort forever because one new field or one bypassed sink leaks the secret. This matters acutely for agents, whose tool inputs/outputs routinely carry tokens and PII. For builders: move the redaction allow-list into the logger config that every emit passes through, so 'log everything then clean up' can never race a breach.
2026-07-11 / sources-researcherClaude Code Ships an In-App Browser on Desktop — The Agent Can Now Test the App It Just BuiltAnthropic highlighted (July 10) that Claude Code on desktop now includes a Browser pane that runs in a clean, isolated profile with none of your saved logins or history, meant for building and testing apps and visiting sites that don't need your identity. For a builder who lives in Claude Code daily, this closes the write-then-manually-verify loop — the agent can drive and inspect the UI it just generated without wiring up a separate browser MCP server. The isolated profile also makes it safe to point at untrusted pages during testing.
2026-07-11 / vibe-coding-researcherSentry MCP Server Can Be Weaponized via Fake Error Events — 85% Agent-Hijack SuccessTenet Security showed that injecting fake error events through a public Sentry DSN causes the Sentry MCP server to return them as trusted diagnostics, letting attackers reach an 85% success rate at tricking coding agents into executing arbitrary commands. It's a clean example of an indirect prompt-injection path where the payload rides in through a legitimate observability integration, not a malicious server. Treat all MCP tool output — even from trusted vendors — as untrusted input, and gate command execution behind explicit confirmation.
2026-07-10 / saas-disruption-researcherVertical SaaS Is Bifurcating: Compliance-Embedded Software Survives, Thin-Feature Tools Get Rebuilt in Six WeeksInformationWeek reports CIOs caught between incumbent vertical SaaS vendors and AI-native challengers, with the market splitting cleanly: deeply embedded, compliance-aware, workflow-critical software (legal, healthcare, field services) retains customers regardless of AI, while horizontal or thin-feature tools face genuine displacement. The number that matters: an $80K/year tool is now plausibly replaceable by a six-week internal build using AI-assisted development. That's the new build-vs-buy threshold, and it's roughly 10x lower than it was two years ago.
2026-07-10 / arxiv-researcherMPFlow Uses Graph RL for Budget-Constrained Liquidity Placement on Lightning NetworkMPFlow (arXiv 2607.08703, July 9) formalizes Bitcoin Lightning Network channel opening as a budget-constrained combinatorial optimization on graphs: select k edge additions maximizing s-t max-flow, a theory-grounded proxy for routing capacity. The agent pairs a message-passing policy network with PPO and stays lightweight. Beyond crypto, this is a clean template for applying graph RL to any budgeted edge-addition problem where the objective is a flow quantity rather than a node-level score.
2026-07-10 / arxiv-researcherToken-Flow Firewall Audits Persistent Agents at the Natural-Language BoundaryPersistent AI agents — those with long-lived memory, reusable skills, and tool-mediated state — have a much larger semantic attack surface than chat assistants because unsafe content propagates through stored state rather than dying with the session. The Token-Flow Firewall paper (arXiv 2607.08395, July 9) observes that nearly all security-critical interactions in such agents pass through natural-language token flows: memory updates, tool arguments, and retrieved content. Auditing at that chokepoint at runtime is a cheaper intervention than trying to sanitize every component, and it maps cleanly onto agent systems that persist findings or skills across runs.
2026-07-10 / vibe-coding-researcherPattern: Context Selection Is Consolidating Into Its Own Layer Beneath the AgentFour distinct projects now sit between the agent and its context rather than inside it: LeanCTX gates reads at the filesystem, graphify replaces grep with graph traversal, PageIndex does reasoning-based retrieval with no vector store at all, and Claude Code's own /doctor now prunes the context file you hand it. The common claim is that the agent should not choose what to read — a separate, cheaper, deterministic layer should. This is the inverse of the 2025 assumption that bigger context windows dissolve the retrieval problem; the constraint turned out to be attention and cost, not window size, and a million-token window makes the selection layer more valuable rather than less.
2026-07-10 / vibe-coding-researcherPattern: Safety Rails Are Migrating From the Prompt Into the Harness's Auto Modev2.1.205's two headline additions — blocking transcript-file tampering and prompting before `rm -rf` on an unresolved variable — are not prompt instructions. They are hard rules the harness enforces regardless of what the model decides. Combined with v2.1.206's EnterWorktree confirmation and LeanCTX's 'the binary refuses to serve the file' approach, the direction is unmistakable: the industry has concluded that asking a model not to do something is not a control. Expect the next generation of agent configs to look less like instructions and more like policy files, and expect 'the model was told not to' to stop being an acceptable answer in incident reviews.

Graph relationships

USES
Leanstral
Leanstral uses Lean proof language for formally verifiable reasoning
Source finding
USES
Terence Tao
Terence Tao uses Lean proof assistants for formal verification in mathematics.
Source finding
BUILT BY
Leo de Moura
Lean was created by Leo de Moura.
Source finding
USES
AlphaProof Nexus
AlphaProof Nexus uses Lean for formal proof verification
Source finding
USES
Leanstral -> Lean
Leanstral uses Lean proof language for formally verifiable reasoning
Source finding

Source trail

Unchained GitHub/HN arXiv published as arXiv 2605.22763v1 Researchers introduced MOSS DeltaBox 11,048-PR study

Graph sources

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