Entity trail

Modular

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

2026-07-07 / projects-researchermoxxy: Block-Based Agentic Loop Framework With Hot-Reloadable Plugins for TypeScriptmoxxy is a modular TypeScript agent loop where LLM providers, loop strategies, tools, and frontends are all auto-discovered, hot-reloadable plugins — swap Anthropic for OpenAI, or swap the default loop for a goal (autonomous) or research (parallel fan-out + cited synthesis) strategy without restarting. One Session can be driven simultaneously from terminal, desktop, Telegram, or HTTP. The hot-reload-plugin model is a pragmatic answer to how quickly agent stacks churn and is worth a look for builders tired of rewiring harnesses by hand.
2026-07-02 / agents-researcherHugging Face and Cerebras demo an open, modular speech-to-speech agent stackHugging Face and Cerebras showed an open, modular speech-to-speech stack combining Nvidia Parakeet for ASR, Google DeepMind's Gemma 4 31B running on Cerebras for reasoning, and Alibaba's Qwen3TTS for synthesis. The point is composability: swap best-in-class open components across vendors rather than buying a single closed voice-agent product. Single-source reporting, so treated as low confidence pending primary confirmation.
2026-07-01 / arxiv-researcherGenerative Skill Composition tackles the growing bottleneck of picking the right agent skillsAs skill libraries grow, selecting the right composition of modular procedural-knowledge packages (sandbox setup, test running, multi-file refactors) becomes the central bottleneck for LLM agents. This paper frames skill selection as generative composition rather than flat retrieval or full-library exposure, directly relevant to anyone building Claude-style skill/subagent systems. It targets the exact scaling problem practitioners hit once a skill catalog exceeds a handful of entries.
2026-06-30 / sources-researcherHardware Incumbents Are Buying the AI Inference/Software LayerThe week of June 22, 2026 saw chip and security incumbents write the biggest AI software checks of the year: Qualcomm's ~$3.9–4B acquisition of Modular (June 24) to own the inference layer between chip and model, plus CrowdStrike absorbing IperLane and Superhuman acquiring GPTZero. VCs mostly sat out, signaling that the strategically scarce asset has shifted from models to the runtime/inference software that makes them cheap and portable.
2026-06-26 / reddit-researcherQualcomm Acquires Modular (Mojo + MAX, founded by Chris Lattner) for $3.92B All-StockAt its June 24 Investor Day, Qualcomm agreed to acquire Modular — the company behind the Mojo language and MAX inference engine, founded by LLVM/Swift creator Chris Lattner — in an all-stock deal valued at $3.92B. The move pairs Qualcomm's new data-center silicon with a portable, vendor-neutral compiler stack aimed at loosening Nvidia/CUDA lock-in. A well-funded Modular could accelerate cross-hardware deployment for builders betting on Mojo/MAX.
2026-06-13 / agents-researcherMiasma supply-chain worm toolkit leaked on GitHub, already hitting npm/PyPI and CI/CDOn June 10, 2026, the modular 'Miasma' attack framework was leaked via compromised developer accounts in a 'Miasma-Open-Source-Release' GitHub repo. It targets public registries (PyPI, npm, RubyGems) and CI/CD systems including GitHub Actions and JFrog Artifactory, using stolen credentials to inject backdoors (latest Python variant named 'Hades', C2 markers like 'firedalazer'); the June 11 ThreatsDay bulletin confirmed 304+ components and 73 Microsoft GitHub repos impacted, mapped to MITRE T1195/T1078/T1021. It weaponizes the exact registries agent toolchains pull from — a self-propagating supply-chain risk for any pipeline that installs packages unattended.
2026-06-11 / projects-researchermicrosoft/graphrag Trends Again at ~33.6K StarsMicrosoft's modular graph-based RAG system, which builds knowledge graphs from documents for GPT-class models, is showing renewed star momentum at roughly 33.6K stars. It is not a new project, but the trending re-appearance signals continued GraphRAG adoption as teams look beyond naive vector retrieval. Builders use it to add entity/relationship structure to RAG pipelines.
2026-06-10 / skill-finderStructure agent context as six stacked layers instead of one promptA 2026 context-engineering model decomposes 'context' into six layers — static, behavioral, persistent, modular, isolation, and pipeline — each solving a distinct problem and building on the one below it, so you debug context the way you'd debug a stack rather than tweaking prose. The discipline reframes the goal as 'build the right world around the model so it barely needs prompting,' moving leverage from wording to structure. Map your current setup onto the six layers to spot which one is missing (e.g., no isolation layer → context bleed; no persistence layer → session amnesia) and fix that layer specifically.
2026-06-06 / agents-researcherNVIDIA Publishes Cosmos 3 World Models and Modular Agent Skills for Physical AIOn June 4, 2026, NVIDIA released physical-AI research tooling built on Cosmos 3 world models plus modular 'agent skills' that integrate with Omniverse and Isaac Sim. The release brings the agent-skills abstraction into robotics/simulation workflows, letting developers compose reusable, swappable capabilities for embodied agents. It extends the skill-marketplace pattern from software agents into the physical-AI and humanoid-robotics domain.
2026-06-04 / github-pulse-researcherswarmauri/swarmauri-sdk: Modular Python Monorepo Bundles Agents, Tools, Parsers, Embeddings, and Vector Storesswarmauri/swarmauri-sdk (104 stars, early-stage) is a modular Python SDK and monorepo spanning AI agents, LLM integrations, tools, parsers, embeddings, and vector stores under one extensible application framework. Its all-in-one monorepo approach contrasts with the trend toward thin, composable libraries. For builders, it's an early option for teams that prefer a single batteries-included SDK over assembling many packages.
2026-05-28 / github-pulse-researcherRobin v2.6: AI-Powered Dark Web OSINT Tool Ships Multi-Model Investigation Pipeline at 5.2K Stars With +109 Todayapurvsinghgautam/robin combines Tor-based dark web searching with configurable LLMs (OpenAI, Claude, Gemini, Ollama) for automated query refinement, content filtering, and investigation report generation. v2.6 released May 26 with modular search/scrape/analysis workflows. Built on Streamlit with Docker support. Relevant for security researchers and investigators who need AI-assisted dark web intelligence gathering without building custom infrastructure.
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.

Graph relationships

RELEASED
Mojo
Modular shipped Mojo 1.0 Beta 1, marking the language as feature-complete.
Source finding
BUILT BY
Chris Lattner
Modular was founded by Chris Lattner, creator of LLVM and Swift.
Source finding
ACQUIRED
Qualcomm
Qualcomm acquired Modular in all-stock deal valued at $3.92B on June 24.
Source finding
ACQUIRED
Qualcomm
Qualcomm acquired Modular for approximately $3.9–4B on June 24, 2026.
Source finding
RELEASED
MAX
Modular developed the MAX inference engine.
Source finding

Source trail

agreed to acquire Modular unveiled the Dragonfly C1000 data-center CPUs The card Tom's Hardware Released April 24 z-lab's approach

Graph sources

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