Entity trail

Seer

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

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-09-13 / agents-researcherFirecrawl documents the AI software factory as five gates, with published numbers from Sentry, Stripe, Spotify and FaireA Firecrawl post on 2026-09-11 frames production coding-agent pipelines as five stages with a gate at each: intake (Sentry's Seer scores incoming issues for actionability), isolation (Stripe boots pre-warmed devboxes in about 10 seconds), tools (Stripe's Toolshed exposes roughly 500 internal tools over MCP), verification (Spotify's LLM judge vetoes about 25% of agent sessions), and merge gate (Faire requires two human reviews on agent-authored PRs). The argument worth taking is that every company that made this work built the gates before the fleet, because generation scales with spend and review does not. It is a vendor blog, but each number is attributed to a named first-party engineering post.
2026-09-13 / hn-researcherArmin Ronacher's P(doom) Rebuttal: Pacing Fails Because Only Two Labs Matter and METR Is Tied to BothRonacher answered the Amodei essay on September 12, arguing the pacing proposal is unenforceable because OpenAI and Anthropic are the only two companies that count and the proposed overseer, METR, has ties to both, so the independence the scheme rests on does not exist. He cites Amodei's own stated p(doom) of 10-25% and an OpenAI employee above 10%, and puts OpenAI's burn at '18 million USD' casually spent. His alternative is forced open weights: 'a powerful technology that is out there for everyone to use comes with built-in pacing,' and he places the real failure on regulation, not on release speed.
2026-05-28 / agents-researcherCalibrated Collective Oversight: arXiv Paper Shows Weaker Overseers Can Constrain Misaligned Stronger AgentsOverman & Bayati (submitted May 27, arXiv 2605.28807) introduce Calibrated Collective Oversight (CCO), a framework that combines diverse scoring functions into a penalty measuring deviation from a conservative baseline, calibrated via Conformal Decision Theory. Testing on modified SWE-bench and MACHIAVELLI benchmarks, weaker overseers successfully constrained misaligned stronger agents — ethical violations decreased substantially while task performance remained intact. Directly relevant to the scaling oversight problem as agents approach superhuman capability.
2026-05-27 / arxiv-researcherLandseer: First Framework for Composing ML Defenses Across Robustness, Privacy, and Fairness SimultaneouslySharma et al. present Landseer, a modular framework for integrating multiple ML defenses that typically address threats in isolation (robustness, privacy, fairness). Real-world deployments require these defenses composed together, but the interaction effects on performance and security are poorly understood. Landseer provides the first systematic way to evaluate defense compositions and their tradeoffs.
2026-04-27 / hn-researcherEvanFlow: 16-Skill TDD Feedback Loop for Claude Code Hits 70 Points on HNEvanFlow is a new Claude Code plugin with 16 cohesive skills that orchestrate brainstorm→plan→execute→TDD→iterate loops with real human checkpoints at design approval, plan approval, and after iteration. For plans with 3+ independent units, it forks into parallel coder/overseer orchestration with integration tests as executable contracts. Safety mechanisms cite 2026 research showing 62% of LLM-generated test assertions are wrong — both the TDD skill and overseer explicitly check whether a one-character bug would still pass assertions. Install via Claude Code plugin marketplace.
2026-04-14 / arxiv-researcherSLALOM: Solving the 'Stopped Clock' Problem in LLM Social Simulations via Trajectory ValidationLee and Seering present SLALOM, a framework addressing the 'stopped clock' problem in LLM-based social simulations: current evaluation confirms correct final outcomes while ignoring whether the trajectory was sociologically plausible. Because LLM reasoning is opaque, verifying that social mechanisms operate correctly — not just that endpoints match — requires longitudinal observation metrics. For builders using LLM agents to model social dynamics or user behavior, this provides the first trajectory-aware validation methodology.

Graph relationships

RELEASED
Sentry
Sentry released Seer to score incoming issues for actionability in AI software factories.
Source finding
RELEASED
Sentry -> Seer
Sentry released Seer to score incoming issues for actionability in AI software factories.
Source finding

Source trail

Firecrawl's Harness's State of Agent DLC 2026 Armin Ronacher / Hacker News (114pts, 79 comments)arXiv arXiv GitHub / Hacker News (70pts, 31 comments)arXiv

Graph sources

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