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…
Governance latency and contextual debt in AWS Context Ontology Accelerator…
To what extent does the human-in-the-loop governance requirement in the Amazon Web Services (AWS) Context Ontology Accelerator (COA) workflow exacerbate the stability-plasticity dilemma for agents con…
Hybrid memory integration
How can Artificial Intelligence (AI) agents effectively synchronize structured semantic memory, meaning ontologies and knowledge graphs, with latent knowledge encoded in Large Language Model (LLM) wei…
Episodic-to-semantic memory consolidation in AI agents
What techniques enable AI agents to reliably generalize from specific episodic experiences (interaction logs, task traces, observed events) to durable semantic memory entries (ontological facts, proce…
Privacy-preserving long-term memory for Artificial Intelligence agents
How can Artificial Intelligence (AI) agents preserve the utility of long-term memory for personalisation and historical context while enforcing privacy, security, and data-sovereignty controls strong…
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…
Autonomous forgetting and information curation for long-term agent memory
How can Artificial Intelligence (AI) agents implement autonomous forgetting mechanisms and information-curation policies that preserve long-term memory utility while preventing retrieval quality, late…
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?
Episodic-to-semantic memory consolidation architectures for agents
What architectures most effectively consolidate raw episodic traces into reusable semantic knowledge for Artificial Intelligence (AI) agents, and which triggers, review loops, and intermediate represe…
LLM Training Prior Contamination in Compliance Interpretation
What failure modes emerge when Large Language Models (LLMs) combine generic public legal knowledge with proprietary organisational policy in compliance interpretation tasks?
Amazon Bedrock AgentCore and related suite
What is the complete set of features, functions, and capabilities offered by Amazon Bedrock AgentCore and its related suite, including AgentCore Gateway, AgentCore Memory, AgentCore Identity, and the…
Ontology landscape for curated lexical and structured enterprise context
For a curated corpus that mixes lexical documents, structured artifacts, application programming interface (API) landscapes, access controls, infrastructure definitions, schemas, and process documenta…
What entity-relation schema and write/query patterns best support cross-session…
What entity-relation schema and write-query prompt patterns best support cross-session research provenance and concept reuse for an Artificial Intelligence (AI) research agent using the `@modelcontext…
What technical architecture best supports cross-item synthesis, knowledge…
What technical architecture best supports three distinct but related capabilities in a file-based research corpus (~200 items, growing weekly): (1) a meta-distillation layer that proactively aggregate…
What are best practices for transparent, user-controlled context management in…
What are the best practices for transparent, deterministic, and user-controlled context management in Large Language Model (LLM) coding agent harnesses, and what are the demonstrable harms of opaque c…
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…
Recall competitive landscape and clone feasibility
What core capabilities does Recall provide, who else is building similar products (including projects in the davidamitchell GitHub organization and relevant open-source tools), what components can we…
Artificial Intelligence (AI)-assisted daily productivity digest
What are the established patterns and tooling approaches for using Artificial Intelligence (AI) to generate actionable daily and weekly productivity digests from personal task management systems?
Sup…
The role of AGENTS.md in a repo using .github/copilot-instructions.md as the…
`AGENTS.md` has emerged as the cross-tool convergence format for agent project instructions, supported by OpenAI Codex, GitHub Copilot, Claude Code, Cursor, Aider, Gemini Command Line Interface (CLI),…
Agent instruction loading and skills access
Given the current repo setup -- instructions in `.github/copilot-instructions.md`, skills submodule at `.github/skills/`, no `AGENTS.md` at root, no `CLAUDE.md` at root -- what does each agent actuall…
Working memory architecture, prefrontal cortex contextual gating, and…
How do human brains store, compress, retrieve, and dynamically layer multiple types of contextual knowledge — values, goals, rules, current state, and immediate task — when making decisions, and what…
Applied context engineering
What practical patterns, workflow best practices, and agent development guidelines emerge from synthesising the `muratcankoylan/Agent-Skills-for-Context-Engineering` skill library with the context eng…
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…
Stateless-agent assumption failure
When an agentic workflow spans multiple session boundaries — each session starting with a fresh context window and no memory of prior runs — what are the mechanisms by which external state becomes orp…
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…
Intent Driven Development
What is Intent Driven Development (IDD) — as a methodology that moves past Test Driven Development (TDD) and Specification Driven Development (SDD) — and what context and concept layering mechanisms 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…
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…
AI concept classification taxonomy
What is a coherent, internally consistent classification taxonomy for the core concepts in AI-assisted and agentic systems — covering prompt types, instruction types, prompt/content/intent engineering…
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…
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…
AI coding harnesses: agent execution model, memory, and context management…
What are the core architectural and philosophical principles behind the AI coding harnesses (agentic IDEs and agent runtimes) published or released by Anthropic, OpenAI, and the broader ecosystem of c…
iOS Shortcuts + GitHub API
Can an iOS Shortcut write a timestamped `.md` file directly to a GitHub repo via the Contents API (`PUT /repos/{owner}/{repo}/contents/{path}`) with a stored Personal Access Token (PAT), with enough r…
Inbox folder pattern
Does removing the folder-selection decision from the capture path meaningfully reduce friction? Design and evaluate an `inbox/` folder pattern where: (a) any capture tool writes unstructured notes to…
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…
An Integrative Framework for Agent Decision-Making
How can the DIKW (Data → Information → Knowledge → Wisdom) progression be operationalised within agentic systems to produce intent-aligned, context-aware decisions that reconcile conflicting knowledge…
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 retention: mechanisms for ensuring completed research is recalled and…
What mechanisms ensure that knowledge from completed research items is retained, recalled when contextually relevant, and applied to decisions — rather than being archived indefinitely with no re-enga…
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…
Knowledge linking: building a connected research corpus via explicit…
What is the minimum viable approach to making the `Research/completed/` corpus a connected knowledge network — where items explicitly reference related items, contradictions and confirmations are surf…
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…
Information synthesis
What is the best way to synthesise information from multiple sources in a manner that is minimally lossy — preserving the most signal while compressing volume — drawing on information theory, entropy,…
Context Mode: MCP tool output compression and the LLM context window management…
What is Context Mode's architecture and actual effectiveness for compressing MCP tool outputs in Claude Code, what are its real-world limitations (especially regarding MCP tool interception), and what…