Entity trail

Build Cross

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

2026-07-09 / saas-disruption-researcherBespoke Labs Raises $40M to Build the Training 'Environments' That Make Agents Reliable — Not Another Foundation ModelBespoke Labs raised a $40M Series A (Wing VC and 8VC leading; angels including Jeff Dean and researchers from Anthropic, OpenAI, and Meta) to build simulation-and-evaluation environments where agents can safely learn, test, and improve before production. It's an architectural bet that the missing layer isn't a bigger model but the harness that makes agents dependable — the same 'environments/evals as infrastructure' pattern showing up across the agent-tooling stack. For builders shipping agentic products, this signals eval/training environments becoming a distinct, fundable category.
2026-07-08 / arxiv-researcherPACR-Video Enables Parameter-Efficient Multi-Shot Long-Video ExtrapolationPACR-Video is a parameter-efficient framework for multi-shot long-video extrapolation that preserves recurring entities across shots via prompt-adapter context routing. It is interesting for video-generation builders needing entity consistency across long sequences without full fine-tuning. Importance is kept low pending released code and quantitative results.
2026-07-08 / arxiv-researcherDynaKRAG Adds Learnable Evidence Control to Multi-Hop RAGDynaKRAG introduces learnable evidence control for multi-hop retrieval-augmented generation, letting the system decide which sequentially-retrieved documents to retain as new bridge facts emerge, instead of naively accumulating context. This targets a concrete pain point for RAG builders: context bloat and irrelevant-evidence drift across hops. The learnable retain/drop gate is the transferable idea.
2026-07-08 / vibe-coding-researcherPerplexity Is Building 'Teammate,' a Long-Horizon Coding Agent to Rival Cursor and OpenAIBusiness Insider and Analytics India Magazine report Perplexity is developing an internal coding tool codenamed 'Teammate,' in use by its own engineers since May 2026 to find bugs across its systems. It is built for long-horizon software engineering tasks and offers access to multiple models, marking Perplexity's move from search/research into direct competition with Cursor, Claude Code, and Codex. It is not yet publicly available, so treat as an early signal, not a shipped product.
2026-07-07 / saas-disruption-researcherCROSS-CATEGORY: Incumbents Reopen Themselves as 'Platforms of Agents' via MCP — Greenhouse's ATS MCP Goes Broad July 6Greenhouse made its MCP broadly available July 6 (alongside a Notetaker and job/analytics agents), joining Workday's new build-connect-verify agent developer tools, Looker/Tableau Next's agentic BI, and Vercel's agent stack. Across HR, analytics and devtools the system-of-record is deliberately exposing itself as MCP tools so external agents run the workflow. The shared bet across three unrelated categories: commoditize your own UI, defend the data — MCP is becoming the integration moat that replaces bespoke connectors.
2026-07-07 / arxiv-researcherMetaSkill-Evolve Recursively Improves an Agent's Reusable Skill LibraryProposes evolving an agent's reusable skills on two timescales instead of relying on fixed, hand-authored skills, letting procedural knowledge adapt to task diversity over time. It targets self-improving, skill-based agent architectures. Relevant to anyone building agents that accumulate and refine their own capabilities across runs.
2026-07-07 / rss-researcherUN launches global push for AI governance amid 'catastrophic harm' warningsUN News reports a renewed global push for coordinated AI governance in July 2026, framed around warnings of potential 'catastrophic harm' from advanced systems. The effort lands the same week as the US White House frontier-model standards move, highlighting competing national and multilateral approaches to frontier oversight. Relevant backdrop for builders anticipating divergent compliance regimes across jurisdictions.
2026-07-02 / agents-researcherAutoMem frames agent memory as a learned cognitive skillAutoMem treats memory not as a fixed retrieval heuristic but as a learned skill — the model learns what to encode, when to retrieve, and how to organize knowledge. Tagged cs.MA (multi-agent), it targets the context-management bottleneck that limits long-running agents. Relevant to anyone building agents that must accumulate and reuse state across sessions rather than re-reading everything each turn.
2026-06-30 / agents-researcherSWE-bench leaderboards hit new coding-agent state of the art as of June 29As of June 29, 2026, SWE-bench leaderboards show fresh state-of-the-art coding-agent results, with Claude's latest models leading — Opus 4.8 topping the active SWE-bench Pro board around 69.2%, and Fable/Mythos 5 leading the Verified board. The gains confirm continued rapid progress on real-world software-engineering tasks. Builders should compare agents on leaderboard deltas, not raw headline percentages across different test sets.
2026-06-29 / skill-finderHarden your LLM-as-judge mechanically: shuffle, pin, rotate families, calibrate — and apply IRT to the judgesThe 2026 consensus names five judge biases (position, verbosity, self-preference, format, calibration drift) and the mitigations that actually survive production are mechanical: shuffle order on every pairwise call and only count consistent wins, pin the judge contract/version, rotate judges across model families (especially to defeat self-preference), and calibrate against humans. A newer line applies Item Response Theory to the judges themselves — treating reliability as a property of the measurement instrument and flagging rubric criteria that are too ambiguous or too sensitive. Builders running eval pipelines should bake order-swapping and cross-family rotation into the harness rather than trusting a single judge model's score.
2026-06-29 / rss-researcherIndie AI Builder: One-Time Credit Purchases Outperform a Weak Subscription ModelAn r/SaaS builder weighing whether to leave a $150K job reports that most revenue comes from one-time credit purchases rather than subscriptions, which 'aren't convincing' enough to retain users. It's a real-world note on the credits-vs-subscription monetization debate that recurs across AI-powered tools.
2026-06-29 / rss-researcherOpenAI Developing a Custom Inference Chip to Cut Nvidia DependenceOpenAI is building an inference-specific chip aimed at higher performance and better energy efficiency across its data centers, part of a push to reduce reliance on Nvidia GPUs and own more of its infrastructure stack. It extends the 2026 pattern of frontier labs vertically integrating silicon to control cost and supply.

Source trail

agentskills.io SiliconANGLE arXiv arXiv Business Insider Multiple Sources arXiv

Graph sources

entity graphfindings textkg entitiesnewsletter issues