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| 1 | +- [Critical Digital Pedagogy in Higher Education | Athabasca University Press](https://www.aupress.ca/books/120310-critical-digital-pedagogy-in-higher-education/) |
| 2 | + - [[Critical pedagogy]], [[Neoliberalism in higher education]] |
| 3 | +- [3. The Panoptic Gaze and the Discourse of Academic Integrity | Critical Digital Pedagogy in Higher Education | AU Press—Digital Publications](https://read.aupress.ca/read/critical-digital-pedagogy-in-higher-education/section/81d95cf4-591b-4eda-8d9d-d29d505111be#ch03) |
| 4 | + - [[Academic Integrity]], [[Surveillance capitalism]], [[Remote proctoring]], [[Critical pedagogy]], [[High stakes exams]] |
| 5 | +- [The Machine That Stops You From Thinking](https://www.goedel.io/p/the-machine-that-stops-you-from-thinking) |
| 6 | + - [[Cognitive offloading]], [[Artificial intelligence in society]], [[Judgment]], [[Overconfidence]], [[Self-reported measures]], [[System one and two]] |
| 7 | + - >AI introduces a third cognitive layer that does not fit neatly into either category. They call it System 3: external, algorithmic cognition operating entirely outside the human mind. |
| 8 | + - >When the AI was right, 92.7 % of participants who consulted it followed its answer. When the AI was wrong, 79.8 % still followed it. Across both conditions, the AI-using group was more confident in their answers, even as the wrong-AI subgroup performed substantially worse than the control group working without any AI. |
| 9 | +- [LadybugDB/ladybug-wasm](https://github.com/LadybugDB/ladybug-wasm) |
| 10 | + - [[Graph database]], [[Webassembly]], [[Database in the browser]], [[LadybugDB]] |
| 11 | +- [LadybugDB/mcp-server-ladybug](https://github.com/LadybugDB/mcp-server-ladybug) |
| 12 | + - [[Graph database]], [[Model context protocol]], [[LadybugDB]] |
| 13 | +- [tejzpr/Smriti-MCP: Smriti is a Model Context Protocol (MCP) server that provides persistent, graph-based memory for LLM applications. Built on LadybugDB (embedded property graph database), it uses EcphoryRAG-inspired multi-stage retrieval - combining cue extraction, graph traversal, vector similarity, and multi-hop association - to deliver human-like memory recall.](https://github.com/tejzpr/Smriti-MCP) |
| 14 | + - [[AI memory]], [[GraphRAG]], [[Graph database]], [[Retrieval augmented generation]], [[Model context protocol]], [[Associative learning]], [[Memory]], [[LadybugDB]] |
| 15 | + - [[2510.08958] EcphoryRAG: Re-Imagining Knowledge-Graph RAG via Human Associative Memory](https://arxiv.org/abs/2510.08958) |
| 16 | +- [inventivepotter/dotmd: A markdown knowledgebase search tool combining semantic search, BM25 keyword matching, and knowledge graph traversal with reciprocal rank fusion and cross-encoder reranking. Python-powered, fully embedded (LanceDB + LadybugDB + SQLite).](https://github.com/inventivepotter/dotmd) |
| 17 | + - [[Knowledge base]], [[Graph database]], [[Knowledge graph]], [[SQLite]], [[Search engine]], [[Python]], [[Markdown]], [[SQLite]], [[LadybugDB]] |
| 18 | +- [[1910.09017] Demystifying Graph Databases: Analysis and Taxonomy of Data Organization, System Designs, and Graph Queries](https://arxiv.org/abs/1910.09017) |
| 19 | + - [[Graph database]], [[GQL]] |
| 20 | +- [GrafeoDB/graph-bench: Benchmark suite for graph databases. Built to compare Grafeo with Neo4j, Memgraph, ArangoDB, FalkorDB, Nebula Graph and LadybugDB.](https://github.com/GrafeoDB/graph-bench) |
| 21 | + - [[Graph database]], [[benchmark]] |
| 22 | +- [GrafeoDB/grafeo: Grafeo is a pure-Rust, high-performance graph database that can be embedded as a library or run as a standalone database, with optional in-memory or persistent storage. Grafeo supports both LPG and RDF and all major query languages.](https://github.com/GrafeoDB/grafeo?tab=readme-ov-file) |
| 23 | + - [[Graph database]], [[Rust]], [[RDF]], [[SPARQL]], [[GQL]], [[Webassembly]], [[Database in the browser]], [[Vector database]], [[AI memory]], [[AST]], [[Model context protocol]], [[LlamaIndex]], [[GraphRAG]] |
| 24 | + - [GrafeoDB/grafeo-web: Grafeo graph database in the browser. Zero backend. Your data stays on the client.](https://github.com/GrafeoDB/grafeo-web) |
| 25 | + - [Grafeo – A fast, lean, embeddable graph database built in Rust | Hacker News](https://news.ycombinator.com/item?id=47467567) |
| 26 | + - [GrafeoDB/grafeo-mcp: Exposes Grafeo as a set of MCP tools so that AI agents and assistants can query, traverse and mutate graph data.](https://github.com/GrafeoDB/grafeo-mcp) |
| 27 | + - [GrafeoDB/grafeo-llamaindex: LlamaIndex integration for the Grafeo graph database. Implements GrafeoPropertyGraphStore, a LlamaIndex PropertyGraphStore backend that supports both structured and vector queries.](https://github.com/GrafeoDB/grafeo-llamaindex) |
| 28 | + - https://github.com/search?q=grafeodb&type=repositories |
| 29 | +- [Mapping AI into Production: A Field Experiment on Firm Performance by Hyunjin Kim, Dahyeon Kim, Rembrand Koning :: SSRN](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6513481) |
| 30 | + - [[Artificial intelligence in the workplace]], [[Startup]], [[Return on investment]], [[Productivity]] |
| 31 | +- [microsoft/agent-framework: A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.](https://github.com/microsoft/agent-framework) |
| 32 | + - [[AI agents]], [[Microsoft]], [[AI engineering]] |
| 33 | +- [Inquiry and Authentic Assessment – www.hackscience.education](https://www.hackscience.education/inquiry-and-authentic-assessment/) |
| 34 | + - [[Authentic assessment]], [[Inquiry based learning]] |
| 35 | +- [Awesome Open Source AI](https://awesomeosai.com/) |
| 36 | + - [[Artificial intelligence]], [[Open source]], [[Open LLM]] |
| 37 | +- [Google's Head Of Learning Says AI Can't Solve Education's Real Problem](https://www.forbes.com/sites/danfitzpatrick/2026/04/05/googles-head-of-learning-says-ai-cant-solve-educations-real-problem/) |
| 38 | + - [[Student motivation]], [[Artificial intelligence in education]], [[Google]] |
| 39 | +- [Eight years of wanting, three months of building with AI - Lalit Maganti](https://lalitm.com/post/building-syntaqlite-ai/) |
| 40 | + - [[AI engineering]], [[SQLite]] |
| 41 | +- [safishamsi/graphify: Claude Code skill. Drop code, papers, images, or notes into a folder and get a knowledge graph with community detection, god nodes, and honest audit trail.](https://github.com/safishamsi/graphify) |
| 42 | + - [[AI Skill]], [[Knowledge graph]], [[Claude]], [[AST]], [[Wiki]], [[Markdown]], [[Knowledge base]], [[Graph database]], [[GraphRAG]], [[Social network analysis]], [[AI memory]] |
| 43 | + - [71.5x token reduction by compiling your raw folder into a knowledge graph instead of reading files. Built from Karpathy's workflow : r/ClaudeCode](https://www.reddit.com/r/ClaudeCode/comments/1sdaakg/715x_token_reduction_by_compiling_your_raw_folder/) |
| 44 | + - [graspologic-org/graspologic: Python package for graph statistics](https://github.com/graspologic-org/graspologic) |
| 45 | + - [networkx/networkx: Network Analysis in Python](https://github.com/networkx/networkx) |
| 46 | + - [GitHub - boshu2/agentops: The missing DevOps layer for coding agents. Flow, feedback, and memory that compounds between sessions. · GitHub](https://github.com/boshu2/agentops) |
| 47 | +- [GitHub - abhigyanpatwari/GitNexus: GitNexus: The Zero-Server Code Intelligence Engine - GitNexus is a client-side knowledge graph creator that runs entirely in your browser. Drop in a GitHub repo or ZIP file, and get an interactive knowledge graph wit a built in Graph RAG Agent. Perfect for code exploration · GitHub](https://github.com/abhigyanpatwari/GitNexus) |
| 48 | + - [[git]], [[GraphRAG]], [[Knowledge graph]], [[Webassembly]], [[Graph database]], [[AST]], [[Model context protocol]], [[AI agents]], [[AI engineering]], [[LadybugDB]] |
| 49 | + - [GitNexus](https://gitnexus.vercel.app/) |
| 50 | + - [GitHub - ShunsukeHayashi/gitnexus-stable-ops: Production toolkit for running GitNexus at scale — 26 repos, 43K symbols, 100K edges, zero data loss. Docker, cron, AI agent integration. Featured in GitNexus Community Integrations. · GitHub](https://github.com/ShunsukeHayashi/gitnexus-stable-ops) |
| 51 | +- [GitHub - onllm-dev/4DPocket: Self-hosted AI-powered personal knowledge base. Save content from 17+ platforms, auto-tag, summarize, and connect with semantic search. · GitHub](https://github.com/onllm-dev/4DPocket) |
| 52 | + - [[Knowledge base]], [[Curation]], [[Bookmark]] |
| 53 | +- [GitHub - nesquena/hermes-webui: Hermes WebUI · GitHub](https://github.com/nesquena/hermes-webui) |
| 54 | + - [[hermes]] |
| 55 | + - [hermes-webui/HERMES.md at master · nesquena/hermes-webui · GitHub](https://github.com/nesquena/hermes-webui/blob/master/HERMES.md) |
| 56 | +- [GitHub - VoltAgent/awesome-design-md: Collection of DESIGN.md files that capture design systems from popular websites. Drop one into your project and let coding agents build matching UI. · GitHub](https://github.com/VoltAgent/awesome-design-md) |
| 57 | + - [[Web design]], [[AI Skill]], [[AI engineering]], [[hermes]] |
| 58 | +- [TrendingBotsAI (@trendingbots): "I am absolutely blown away by Hermes agent @Teknium @sudoingX @NousResearch What are the best tips to get the most out of Hermes agent? Really eager to learn more 🚀" | XCancel](https://xcancel.com/trendingbots/status/2040801763976990976#m) |
| 59 | + - [[hermes]] |
| 60 | +- [AgentMail | Email Inbox API for AI Agents](https://www.agentmail.to/) |
| 61 | + - [[Email]], [[AI agents]], [[AI engineering]] |
| 62 | +- [GitHub - outsourc-e/hermes-workspace: Native web workspace for Hermes Agent — chat, terminal, memory, skills, inspector. · GitHub](https://github.com/outsourc-e/hermes-workspace) |
| 63 | + - [[hermes]] |
| 64 | +- |
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