Macro-level hallucination risk in schema-free GraphRAG clustering
How does the noisy baseline produced by unconstrained entity extraction corrupt the hierarchical summaries generated by standard Graph Retrieval-Augmented Generation (GraphRAG) community-detection pip…
Context collision and relational blindness in flat-vector RAG
Given that classical flat-vector Retrieval-Augmented Generation (RAG) acts as an external access mechanism rather than a persistent internal memory state, how do contradictory semantic overlaps in top…
Symbolic-connectionist synchronisation in hybrid agent memory
How can hybrid agent-memory architectures keep structured symbolic knowledge bases synchronised with unstructured Large Language Model (LLM) and retrieval-layer memory so that updates remain consisten…
Evaluation frameworks for agentic memory quality, relevance, and retrieval…
What benchmark suite and metric design best measures the quality, relevance, retrieval accuracy, freshness, and governance correctness of agentic memory systems across heterogeneous tasks?
AWS AgentCore and AWS-native Knowledge Context Layer
What Amazon Web Services (AWS) AgentCore capabilities and AWS-native services are required to design and operate a Knowledge Context Layer (KCL) that continuously acquires, curates, evolves, and serve…
TBox-driven vs ABox-emergent ontology approaches in GraphRAG systems
To what extent do TBox (Terminological Box)-driven (predefined upper- and mid-level) ontologies outperform, underperform, or complement ABox (Assertion Box)-emergent (bottom-up, data-driven) approache…
Migration trade-offs from vector Retrieval-Augmented Generation to…
What are the performance, cost, scalability, and practical trade-offs of migrating from traditional vector-based Retrieval-Augmented Generation (RAG) systems to ontology-backed Knowledge Graph Retriev…
Amazon Web Services (AWS) Bedrock platform capabilities
What is the complete set of features, functions, and capabilities offered by Amazon Web Services (AWS) Bedrock, including its model access, agent building, knowledge bases, guardrails, evaluation, and…
When Retrieval-Augmented Generation source documents change after agent build…
When the source documents indexed in a Retrieval-Augmented Generation (RAG) pipeline change after an agent has been built and tested, what failure modes and behavioral regressions can result in produc…
What is the architecture and practical applicability of OpenFactCheck as an…
What is the architecture, evaluation methodology, and practical applicability of OpenFactCheck as an automated, modular, claim-level fact-checking pipeline for Artificial Intelligence (AI)-generated c…
What are the capabilities, architectural assumptions, and practical deployment…
What are the capabilities, underlying architectural assumptions, and practical deployment constraints of Loki as an MIT-licensed automated fact-checking tool optimised for journalists and content mode…
What is the minimal viable schema for an Artificial Intelligence bill of…
What is the minimal viable set of schema properties required to describe Artificial Intelligence (AI) system dependencies for systems that use prompts, retrieval knowledge bases, memory, and tools in…
What systematic review methodologies and Artificial Intelligence (AI)-assisted…
What systematic review methodologies, Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA), Cochrane review, narrative synthesis, meta-ethnography, and realist synthesis, and wh…
What automated claim verification approaches against scientific literature…
What automated claim verification approaches against scientific literature, specifically arXiv preprints, are used in research synthesis systems, what search strategies maximise recall and precision f…
What security capabilities are required in an enterprise Artificial…
What security capabilities are required in an enterprise Artificial Intelligence (AI) system, beyond basic Application Programming Interface (API) access controls and audit logging, to address prompt…
Is knowledge scaffolding an established concept within context engineering for…
Is knowledge scaffolding an established concept within context engineering for Large Language Models (LLMs) and Artificial Intelligence (AI) agents, and if so, how is it defined, implemented, and dist…
Permission-safe Retrieval-Augmented Generation (RAG) in enterprise information…
What are the technical constraints on permission-safe Retrieval-Augmented Generation (RAG) in an enterprise information architecture with incoherent access controls, collaboration groups created ad ho…
Knowledge curation governance as an enterprise AI capability in regulated…
What operational models exist for governing authoritative knowledge as a managed enterprise capability for Artificial Intelligence (AI) consumption in regulated financial institutions, covering domain…
Layered Organisation Large Language Model
Is it technically feasible and economically viable for an organisation to build a customised Large Language Model (LLM) layer that injects and optimises over organisation-specific context - internal k…
Application Programming Interface (API) Context Hubs, Retrieval-Augmented…
What approaches are being used to enable Artificial Intelligence (AI) agents to discover, understand, and invoke external Application Programming Interfaces (APIs), and how do the three major emerging…
Artificial Intelligence (AI) Memory Systems
What is the current state of Artificial Intelligence (AI) memory systems — across Retrieval-Augmented Generation (RAG) research, commercial AI vendor implementations (GitHub Copilot, Gemini, Claude, a…
Aligned Decision-Making
What framework should an organisation adopt to ensure that AI agents making or supporting decisions have access to the right layered organisational context — spanning regulatory boundaries, values and…
Latent Concept Extraction from Confluence
What are the best approaches for extracting latent concepts from a Confluence wiki, representing them as word embeddings in a vector database (VDB) and as a knowledge graph (KG), and how can the resul…
Context Compression and RAG Techniques for Organisational Knowledge
What are the current best practices and bleeding-edge techniques - including Retrieval-Augmented Generation (RAG), context compression, and context architecture - for selectively surfacing the rig…
ChatGPT Actions and custom GPTs
Can a ChatGPT custom Generative Pre-trained Transformer (GPT) be configured with Actions that: (a) call a self-hosted HTTP endpoint to add a memory, (b) call `search_brain` before responding to surfac…
SWAT technique in a fresh-context loop
When the SWAT (Strengths, Weaknesses, Assumptions, Threats) technique is executed repeatedly in a loop where each invocation uses a fresh Large Language Model (LLM) context window and the caller blind…
YouTube transcripts via third-party transcript APIs (AssemblyAI / Supadata)
Can a third-party transcript API (AssemblyAI, Supadata, Kagi, or similar) retrieve YouTube
transcripts from a GitHub Actions runner, bypassing YouTube's IP-based block on the
internal transcript endpo…
Telegram bot as mobile memory capture and retrieval channel
Can a Telegram bot serve as a low-friction mobile capture and retrieval surface for the Memory-System? Specifically: (a) message received → file written to GitHub repo via API, (b) messages starting w…
Slack as a mobile memory capture and retrieval channel
Can a Slack bot in a personal or team workspace serve as a memory capture and retrieval surface? What is the minimum viable setup: slash command vs bot, incoming webhook vs Socket Mode, and does a fre…
ServiceNow AI: Knowledge Management, RAG Pipelines, and Agent Frameworks
How is ServiceNow evolving its platform to support AI-powered knowledge management, retrieval-augmented generation (RAG), and agent frameworks — and what should an organisation investing in ServiceNow…
Context engineering: first principles of steering LLM output without control
What are the first principles of context engineering — and what novel approaches emerge when it is understood as two distinct but coupled mechanisms: (1) making the next predicted token more likely to…
LanceDB index rebuild speed from git
Can the LanceDB index be rebuilt from the `.md` files in the repo on startup fast enough to enable stateless (per-request) deployment? Measure rebuild time at: current corpus size, 100 files, 500 file…
Claude for iOS: MCP remote integration for memory capture and retrieval
Does the Claude iOS app support MCP connections to a remote server? If so: (a) what transport is supported (HTTP/SSE vs stdio), (b) does it require the same `.mcp.json` config as Claude Desktop, (c) w…
Semantic and full-text search over the research corpus
What combination of full-text search (keyword/BM25) and semantic search (embeddings/vector) is most appropriate for querying the `Research/completed/` corpus, given the constraints of a git-based, loc…
iOS Shortcuts for research capture and query
What iOS Shortcuts workflows provide the most value for a personal research system hosted on GitHub — covering both low-friction research capture (adding a URL or idea to the backlog from anywhere on…
Conversational and chat interface for querying the research corpus
What is the best approach to expose the `Research/completed/` corpus as a queryable, conversational interface — so that a user (or an AI agent) can ask "what do I know about X?" and receive a grounded…
YouTube transcripts via Gemini API (native YouTube URL support)
Can we use the Gemini API (already configured in `davidamitchell/Latest-developments-`) to
extract full transcripts from YouTube videos without being blocked by YouTube's IP restrictions?
LLM Hallucinations — Types, Causes, and Current Mitigation Approaches
What are the established types, root causes, and current mitigation strategies for hallucinations in large language models, and what does the macroscopic (training-level) view leave unexplained that m…
Local index vs reference
For each type of research content, should we store a local copy / index, or just maintain a reference (URL, citation)? What are the right trade-offs between storage cost, offline access, durability, a…
Local database: requirements and technology choice
If we decide to use a local database for indexing and state (rather than JSON files), what are the requirements and what technology should we choose?
Knowledge Representation for Agent Context
What techniques — latent semantic extraction, knowledge graphs, concept maps, hierarchical document compression, and layered abstraction — most effectively represent and compress large knowledge corpo…
AI for Control Testing, Gap Identification, and Policies/Standards Reviews
Which organisations are using AI to automate control testing, identify control gaps, or conduct policies and standards reviews — and what does the current vendor, practitioner, and regulatory landscap…
Agent Memory Management and Context Injection
What is the current state of agent memory management systems — beyond RAG — and which approaches best address the real constraints of latency, knowledge freshness, scoping, governance, quality, and di…
Indexing and tracking method for research content
What is the best method for indexing and tracking research content (transcripts, papers, notes) given the constraints of a git-based, local-first repo?