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…
How Do Enterprise AI Maturity Frameworks Map onto the LLM Consumption Ladder?
How do theoretical frameworks of enterprise Artificial Intelligence (AI) / generative AI maturity map onto the observed, practice-driven progression of large language model (LLM) consumption strategie…
Secure Runtime Evolution for AI Coding Agents
What is the logical progression in AI (Artificial Intelligence) coding-agent runtime design from local process/Operating System (OS) sandboxes, through shared Continuous Integration (CI)/cloud develop…
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…
What benefits, risks, and lifecycle costs of shadow Information Technology (IT)…
What benefits, risks, and lifecycle costs of shadow Information Technology (IT) and custom local tooling are documented, and which governance approaches successfully transition covert local solutions…
How do platform engineering, InnerSource, and standard-core plus…
How do platform engineering, InnerSource, and standard-core plus local-extension operating models balance team autonomy with organisational standardisation, and which patterns most reliably preserve l…
At what scale or under what operating conditions do the aggregate costs of…
At what scale or under what operating conditions do the aggregate costs of fragmented local tooling exceed the productivity gains from customization, and which metrics let organisations detect that cr…
How does local optimisation of team- and role-level tooling in knowledge work…
How does local optimisation of team- and role-level tooling in knowledge work reduce organisation-level throughput, and which interdependencies determine when local gains become global losses?
TOGAF motivation architecture
What does The Open Group Architecture Framework (TOGAF)'s motivation architecture say about the dependency chain from business driver to goal to requirement: does it specify validation rules, or only…
How have software-development commit trends shifted across repository creation,…
What do high-quality longitudinal studies (2019–2026) show about directional shifts and current baseline ranges for repository creation rate, Lines of Code (LOC) velocity, rework share, project abando…
Q6: Leading indicators of instability in split-authority flow systems
Which metrics best predict unsafe queue growth, rising delivery risk, or hidden demand accumulation in a split-authority delivery system, where "split-authority" means a context in which authority is…
Q3: Routing design that isolates exceptions from routine flow
What intake, triage, queueing, escalation, and routing model allows routine work to move quickly while isolating high-risk or ambiguous work?
Q2: Demand segmentation for fast-path vs controlled-path flow
Which work items are low-risk, standard, and reversible enough for fast-path handling, and which require slower expert review or tighter controls?
Operating model synthesis for split-authority delivery systemssynthesis
What operating model improves throughput while reducing delivery risk in a split-authority environment, where "split-authority environment" means a delivery context in which authority is divided among…
AI-first software ecology in large engineering organisations (2025-2030)
What operating model, architecture strategy, and governance practices best improve developer productivity with Artificial Intelligence (AI) assistance in large software organisations, while preserving…
Similarity algorithms and growth policy for a file-based controlled theme…
Which similarity algorithms are appropriate for detecting near-synonym themes in a controlled vocabulary of 20–40 slug-based labels, and what growth policy prevents both vocabulary explosion and colla…
How should financial Retrieval-Augmented Generation (RAG) systems filter…
What pre-retrieval architecture and governance controls most reliably remove low-information content, meaning boilerplate, repeated passages, wrapper text, and other low-signal document fragments, and…
At what threshold does Human-in-the-Loop (HITL) oversight in bank compliance…
What measurable workload, alert-volume, and staffing thresholds indicate that Human-in-the-Loop (HITL) compliance review is no longer a meaningful challenge function, meaning reviewers mostly accept a…
How should banks detect and mitigate user-belief mirroring and sycophantic…
How do standard prompt-engineering patterns used in banking credit and compliance workflows trigger sycophancy, meaning model behaviour that agrees with user-stated beliefs over better-supported answe…
How should banks govern department-level agent sprawl and bottleneck shifts…
How does uncoordinated growth of department-level software agents change systemic risk and reporting integrity in banks, and which governance architecture can maintain consistency across agents, trace…
What Are the Micro-Transaction Costs of Internal Knowledge Sourcing?
What micro-transaction costs are borne by knowledge seekers and providers during internal peer-to-peer transfers, and how do these costs shift the choice between self-solving ("make") and help-seeking…
The Complexity Horizon
In what ways does the Complexity Horizon of deeply nested, microservice-oriented classical architectures create an epistemic barrier where a deterministic system becomes just as uninterpretable and op…
Formal Generalisation Bounds for Tool-Using LLM Systems When Tools Return…
What formal bounds can be stated for generalisation outside the training distribution in tool-using Large Language Model systems when their tools return non-deterministic outputs under unconstrained p…
What Are We Losing and Gaining by Inserting Autonomous Tool-Using Artificial…synthesis
What are we concretely losing and gaining, across the dimensions of capability, reliability, auditability, explainability, and organisational risk, by inserting autonomous tool-using Large Language Mo…
Visibility and exit outcomes
How often does vendor-supplied temporary operational automation produce materially worse visibility and exit outcomes than internally governed temporary operational automation?
Longitudinal persistence rates after gap closure for low-code applications,…
What longitudinal evidence exists on persistence rates after the original gap is closed for low-code applications, bots, and agents in live enterprise estates?
Datasets for measuring conversion from demand for local workaround tools to…
What public or internal datasets can validly measure the rate at which demand for local workaround tools, such as local apps, flows, lists, or spreadsheets, is converted into formal central Informatio…
Governance designs where explicit integrator rights substitute for co-location…
Under which governance designs do explicit integrator rights fully substitute for structural co-location of risk, cost, and benefits, and under which conditions do these designs fail?
Matched denominator for comparing post-pipeline release-based failures with…
What common denominator enables direct matched comparison between post-pipeline release-based failure rates and production live-runtime incident rates for the same production workflow?
LLM-First Policy Clarification and Institutional Knowledge Atrophy
How does shifting from peer policy clarification to Large Language Model (LLM)-first interaction affect institutional memory transfer, mentoring, and long-term policy expertise?
Policy Quality Degradation and Cross-Institution Blind Spots When New Policy…
What policy-quality degradation and systemic blind-spot risks emerge when organisations draft new policy versions from Large Language Model (LLM) interpretations of previous policy versions?
Cognitive Closure Under Ambiguity and Confirmation Bias
How do pressures to reach a quick, definite answer under ambiguity and iterative prompt refinement influence acceptance of flawed Large Language Model (LLM) policy interpretations?
De Facto Policy Drift From Repeated Unverified LLM Interpretations
How quickly do repeated unverified Large Language Model (LLM) interpretations create de facto policy norms that diverge from executive intent and board-level risk appetite?
AI-Assisted Policy Interpretation and Accountability Displacement
How does integration of Large Language Models (LLMs) into policy-ambiguity resolution change liability allocation, escalation behaviour, and an organisation's ability to justify the resulting decision…
Layered reasoning stack interfaces
What state abstraction boundaries and interface protocols are most effective for mapping Large Language Model (LLM) candidate outputs into Energy-Based Model (EBM) evaluation state spaces while preser…
Kona and Aleph at their core, with Lean and unifying concepts
What are Kona and Aleph at their core, what do they each do in practice, how does Lean (the theorem prover) relate to them, and which unifying concepts explain where they overlap and differ?
ServiceNow Artificial Intelligence (AI) Control Tower
What is the complete set of features, functions, and capabilities offered by ServiceNow AI Control Tower, and how do those capabilities address enterprise Artificial Intelligence (AI) governance, obse…
Microsoft Copilot Studio
What is the complete set of features, functions, and capabilities offered by Microsoft Copilot Studio, and how do those capabilities support enterprise-grade Artificial Intelligence (AI) agent develop…
Microsoft Foundry (formerly Azure Artificial Intelligence (AI) Foundry)
What is the complete set of features, functions, and capabilities offered by Microsoft Foundry, and how do those capabilities support the full Artificial Intelligence (AI) development lifecycle, from…
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…
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…
Variance Control Comparison Across Delivery Modes
What is the empirical failure-rate distribution of Artificial Intelligence (AI)-assisted code that has passed a standard software delivery pipeline compared with AI-agent-executed business processes a…
Information Technology (IT) throughput capacity as a constraint on unmet…
What is the empirical relationship between Information Technology (IT) throughput capacity and the rate at which unmet operational capability needs accumulate across comparable organisations, and what…
Automated decommission of temporary bridge Artificial Intelligence (AI) agents
What technical and organisational mechanisms most reliably cause temporary bridge Artificial Intelligence (AI) agents to be decommissioned when the corresponding software capability is delivered, and…
External Dependency Surface Taxonomy for Production LLM Agents
What is the complete taxonomy of external dependencies for a production Large Language Model (LLM)-based agent, how does each dependency class fail, what is the blast radius of each failure class, and…
Temporary Automation Demand Persistence and Core Capability Investment…
What evidence exists that temporary automation workarounds displace investment in core software delivery, and what is the observed persistence rate of those workarounds after the underlying systems ca…
Reference architecture definition, framework landscape, and required detail…
What should a practical reference architecture include, which established architecture frameworks define or structure it, and how much detail should be specified across capabilities, components, flow…
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…
Empirical evidence on rollout of organisation-wide low-code and no-code programs
What does peer-reviewed and independently verified empirical evidence reveal about the outcomes, success factors, governance models, and failure modes of organisation-wide low-code or no-code (LCNC) p…
Vendor Non-Compliance With or Absence of Implementation Standards
What failure modes have been empirically observed in organisations where vendors do not comply with established implementation standards, or where implementation standards are absent or insufficiently…
PromptQL definition, research foundations, and related technologies
What is PromptQL, what active research areas are most closely related to it, what prior research foundations PromptQL appears to build on, and which adjacent technologies should be considered when eva…
What is Anthropic's '4D' framework for Artificial Intelligence (AI) fluency,…
What is Anthropic's "4D" framework for Artificial Intelligence (AI) fluency, what do each of the four Ds, Delegation, Description, Discernment, and Diligence, mean in practice, and how does this frame…
Architectural patterns for reliable organizational process identification,…
What integrated architectural configuration of retrieval, reconciliation, constraint enforcement, memory, validation, escalation, and governance mechanisms most reliably enables visual workflow toolin…
Graph database landscape
For the hosted graph database platforms identified in the 2026 Software-as-a-Service (SaaS) knowledge-ontology research, Neo4j AuraDB, Amazon Neptune, Stardog Cloud, Ontotext GraphDB, and Memgraph Clo…
Agent-to-Agent (A2A)-to-tool-calling unification
To what extent does unifying specialised Agent-to-Agent (A2A) protocols into a standardised tool-calling interface affect orchestration overhead and reasoning accuracy in hierarchical multi-agent syst…
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…
Knowledge Graph lifecycle management for multi-step software agents
What are the best practices for maintaining and evolving a Knowledge Graph (KG), a structured graph of entities and relationships, that serves multi-step software agents, covering schema versioning, e…
Knowledge Graph in the live execution path of multi-step Large Language Model…
What architectural patterns, operational practices, and failure modes arise when a Knowledge Graph (KG) becomes a key part of the live execution path for multi-step Large Language Model (LLM) systems,…
Hardware load and Large Language Model (LLM) inference performance
How does hardware resource load, Central Processing Unit (CPU), Graphics Processing Unit (GPU), and memory pressure, affect Large Language Model (LLM) inference performance, specifically latency, thro…
Hosted Software-as-a-Service (SaaS) graph database options for knowledge…
Which hosted Software-as-a-Service (SaaS) graph database platforms are suitable for building and querying a knowledge ontology, and how do they compare on data model support, query language, pricing,…
Control deficiencies from bypassing designated workforce record platforms
What control deficiencies are most common when designated workforce record platforms are bypassed by spreadsheet, presentation, and list-based shadow workflows?
Taxonomy criteria: process inefficiency versus hidden control and dependency…
Which explicit criteria best distinguish ordinary process inefficiency from hidden control and dependency risk in workforce-capacity and skill-tracking workflows?
Process-Risk-Control (PRC) scoring impacts from unstandardized workforce…
How should inherent risk, meaning exposure before relying on controls, and control effectiveness, meaning the demonstrated reliability of the mitigating control, scores in a PRC library change when wo…
Language Server Protocol (LSP)-style policy surfaces and workforce taxonomies…
How can workforce-capacity and skills-taxonomy structures integrate with a Language Server Protocol (LSP)-style policy diagnostic surface to detect persistent capability mismatches automatically in en…
National Institute of Standards and Technology (NIST) Special Publication (SP)…
How do missing provenance, lineage, and change-history controls in Microsoft Lists, Excel, and PowerPoint workforce artifacts conflict with NIST SP 800-53 Rev. 5 integrity-related controls?
Key-person dependency and Basel execution, delivery, and process-management…
How should key-person dependency in workforce-critical processes be mapped to execution, delivery, and process-management risk categories in Basel Committee framing?
Control Objectives for Information and Related Technologies (COBIT) and…
What minimum process-definition conditions do COBIT 2019 and CMMI require before mitigation of workforce-process risk can be considered effective and sustainable?
Basel Committee on Banking Supervision (BCBS), International Organization for…
How do Basel Committee on Banking Supervision (BCBS), International Organization for Standardization (ISO) 31000, and National Institute of Standards and Technology (NIST) frameworks classify risk whe…
Implementation Patterns for Regulatory Compliance in Artificial…
What specific implementation patterns, including externalized machine-executable policy rules (Policy-as-Code (PaC)), rules engines, input, tool-use, and output safety controls (guardrails), output va…
Hybrid Architecture Design
How should hybrid architectures be designed so that probabilistic LLMs handle interpretation and insight generation while deterministic layers enforce final governance, compliance, and high-stakes dec…
Build vs improve tradeoff
Given constrained engineering capacity, how should organisations allocate effort between (1) building features within an existing system and (2) improving the system itself (tooling, process, architec…
What tiered human oversight models maintain meaningful human-in-the-loop (HITL)…
Under high-volume deployment of multi-step Artificial Intelligence (AI) systems, what factors cause human-in-the-loop (HITL) oversight to degrade into rubber-stamping, meaning approval without genuine…
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…
How do open-weight policy enforcement reasoning models, exemplified by OpenAI's…
How do open-weight, meaning released-weight and self-hostable, policy enforcement reasoning models, exemplified by OpenAI's gpt-oss-safeguard, classify text against strict, customizable policies, and…
How can findings from OpenFactCheck, Loki, FActScore, gpt-oss-safeguard, and…synthesis
How can the findings from research into OpenFactCheck, Loki, FActScore, gpt-oss-safeguard, and Barnum statement identification techniques be synthesised into concrete, actionable improvements to the a…
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…
How do you capture a runtime-observed Artificial Intelligence Bill of Materials…
How do you instrument a real agentic Artificial Intelligence workload, meaning a tool-using workload that plans or acts across multiple steps, to capture a runtime-observed Artificial Intelligence Bil…
How does the European Union (EU) AI Act and related international AI governance…
- [fact; source: https://owaspaibom.org/] Artificial Intelligence Bill of Materials (AIBOM) is used here in the Open Worldwide Application Security Project (OWASP) sense of an artifact intended to mak…
What introspection, export, and control surfaces actually exist across…
What logs, traces, audit Application Programming Interfaces (APIs), Artificial Intelligence Bill of Materials (AIBOM) export capabilities, version-pinning mechanisms, allowlists, and policy hooks actu…
How do OAuth 2.0, OpenID Connect, and SPIFFE token propagation work in real…
How do OAuth 2.0 (Open Authorisation), OpenID Connect (OIDC), and SPIFFE (Secure Production Identity Framework for Everyone) token propagation mechanisms work in real multi-agent Artificial Intelligen…
How do you construct a declared design-time Artificial Intelligence Bill of…
How do you extract and construct a declared design-time Artificial Intelligence Bill of Materials (AIBOM), covering model, prompt or system instruction, tools, Retrieval-Augmented Generation (RAG) kno…
What measurement systems and frameworks exist for quantifying Information…
What measurement systems and frameworks exist for quantifying Information Technology (IT) system legibility, defined here as the ability to reason about, understand, and comprehensively characterise t…
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…
How does STORM's perspective discovery step work, and what is the…
How does the STORM (Synthesis of Topic Outlines through Retrieval and Multi-perspective question generation) system's perspective discovery step generate diverse expert viewpoints before decomposing a…
What structured approaches and Artificial Intelligence (AI) agent workflow…
What structured approaches, from academic writing pedagogy, Artificial Intelligence (AI)-assisted writing tools, and agent workflow design, exist for converting synthesised research findings into poli…
What are the established norms from academic pre-print repositories and…
What are the established norms and practical conventions from academic pre-print repositories (arXiv, Social Science Research Network (SSRN), Open Science Framework (OSF)) and Personal Knowledge Manag…
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 structured knowledge-gap tracking and automatic backlog-promotion patterns…
What structured knowledge-gap tracking and automatic backlog-promotion patterns exist in Personal Knowledge Management (PKM) systems (linked-note methods such as Zettelkasten, Obsidian, Roam Research,…
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 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 adversarial review and red-teaming methods are most effective for…
What adversarial review and red-teaming methods, drawn from Artificial Intelligence (AI) safety research, debate-based evaluation, formal argumentation theory, and scientific peer review practice, are…
What architectural capabilities and contractual conditions are required to…
What architectural capabilities and contractual conditions are required for an enterprise to maintain multi-platform portability and mitigate Artificial Intelligence (AI) vendor lock-in risk from: Mic…
How should human-in-the-loop (HITL) design be adapted when AI review volume…
How should human-in-the-loop (HITL) design be adapted when Artificial Intelligence (AI) review volume reaches the point where human reviewers become a throughput bottleneck or default to rubber-stampi…
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…
Vendor-agnostic enterprise Artificial Intelligence (AI) capability model
What is the complete set of architectural capabilities required to run Artificial Intelligence (AI) safely at scale in a regulated enterprise, how do Microsoft's Copilot family (Microsoft 365 Copilot…
What does TerminalBench reveal about minimal toolsets and coding agent…
What does the TerminalBench benchmark reveal about the relationship between toolset minimalism and coding agent performance, and what design principles does it suggest for effective Artificial Intelli…
What strategies are effective for open-source software maintainers dealing with…
What strategies are effective for open-source software (OSS) maintainers in filtering, managing, and sustaining project health against a rising volume of low-quality Artificial Intelligence (AI) agent…
What design patterns govern effective extension and plugin systems for…
What design patterns and architectural principles govern effective extension and plugin systems for Artificial Intelligence (AI) coding agent harnesses, and what are the key trade-offs between extensi…
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…
Artificial Intelligence coding harness quality benchmarks
What benchmarks, metrics, and evaluation methodologies are used to measure the quality of Artificial Intelligence (AI) coding harnesses, including Integrated Development Environment (IDE) plugins, age…
Ubiquitous Language in Artificial Intelligence (AI)-augmented development
How significantly does maintaining a living Ubiquitous Language (UL), in the Domain-Driven Design (DDD) sense of a shared, precise domain vocabulary used consistently in both code and conversation, im…
Test-Driven Development (TDD) and fast feedback loops in Artificial…
How does enforcing Test-Driven Development (TDD) with AI coding assistants, writing failing tests before asking the AI to implement, change the quality and stability of the AI output compared to "writ…
Software Engineering fundamentals and AI code generationsynthesis
Drawing on the planned seven-item research programme on Software Engineering (SE) fundamentals in Artificial Intelligence (AI)-augmented development, six completed primary items plus external anchors…
Grill-Me technique: iterative structured interviewing for human and Artificial…
How effectively does the "Grill Me" technique, relentless iterative structured interviewing of the human developer by the AI assistant to build a shared design concept before generating any code, redu…
Fundamentals-first versus specs-to-code
What empirical patterns emerge when comparing real-world software projects built with a strict fundamentals-first Artificial Intelligence (AI) workflow, structured alignment, modules with simple inter…
Deep modules in AI-augmented development
How much more effective is Artificial Intelligence (AI) at understanding, navigating, and correctly modifying a codebase composed of deep modules with simple interfaces versus one filled with many sha…
Artificial Intelligence code entropy and complexity
Does repeated Artificial Intelligence (AI) code generation without strong architectural guardrails demonstrably increase software entropy and complexity over time, as predicted by the entropy model de…
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…
Which software categories face declining demand versus increasing demand as…
As Artificial Intelligence (AI) coding agents, such as Anthropic Claude Code, OpenAI Codex, and GitHub Copilot Workspace, make custom software generation materially cheaper, which categories of commer…
Alternative Continuous Integration and Continuous Delivery pipeline platforms…
What alternative Continuous Integration and Continuous Delivery (CI/CD) pipeline platforms, specifically Harness, Amazon Web Services (AWS) CodeBuild and CodeDeploy, and Jenkins, can serve as the gove…
Universal Entity Lifecycle Governance Framework (UELGF) extension
What concrete reference architecture and tooling specification, covering policy-as-code engines such as Open Policy Agent (OPA) and Cedar, observability pipelines such as OpenTelemetry (OTel), and mod…
How do academic and scientific publishing systems handle post-publication…
How do established academic and scientific publishing systems (journal publishers, preprint servers, living review platforms) handle post-publication corrections, amendments, retractions, and formal c…
ServiceNow workflow orchestration and agentic Artificial Intelligence (AI)…
What workflow orchestration and governance capabilities does ServiceNow currently provide for Artificial Intelligence (AI) agent workloads, specifically its identity resolution, permissions, audit tra…
Enterprise data stack value-distribution frameworks
What frameworks - specifically the seven-layer enterprise stack and the Software Repricing Matrix described in the April 2026 Liam Hyland ServiceNow analysis video, together with comparable frameworks…
Universal Entity Lifecycle Governance Framework (UELGF)
What is the complete specification of the Universal Entity Lifecycle Governance Framework (UELGF), integrating foundational definitions and principles, entity taxonomy and Confidentiality, Integrity,…
Universal Entity Lifecycle Governance Framework (UELGF)
What policy architecture, covering Policy Administration Point (PAP), Policy Decision Point (PDP), Policy Enforcement Point (PEP), and Policy Information Point (PIP), and what 8-layer organisational c…
Universal Entity Lifecycle Governance Framework (UELGF)
How should the UELGF specify governed golden rails for each entity type and Confidentiality, Integrity, and Availability (CIA) tier such that the rail is generative, with a complete governed scaffold…
Universal Entity Lifecycle Governance Framework (UELGF)
What are the foundational definitions, formal principles, and architectural properties required to specify the Universal Entity Lifecycle Governance Framework (UELGF) such that it applies consistently…
Universal Entity Lifecycle Governance Framework (UELGF)
What canonical entity taxonomy and Confidentiality, Integrity, and Availability (CIA) classification system should the UELGF use to determine governance intensity, ensuring that every entity type, fro…
Universal Entity Lifecycle Governance Framework (UELGF)
How should the UELGF formally specify the decommission lifecycle, including a complete trigger taxonomy, procedural requirements differentiated by CIA tier, a ghost-entity detection and remediation me…
Universal policy synchronisation and integrity
What mechanism ensures that the Policy Decision Point (PDP) evaluates a governed asset against logically identical policy at every lifecycle phase, such that a soft gate in Development and a hard gate…
What is the strongest evidence-based argument that investing in software…
What is the strongest evidence-based argument - drawing on Yann LeCun's primary sources, the formal methods literature, the systems capability debt research already in this corpus, and empirical evide…
What does synthesising LeCun's architectural critique of Large Language Models…
What does the synthesis of Yann LeCun's architectural critique of Large Language Models (LLMs), no causal world model, no consequence reasoning, verifiable only in formal systems, with the systems cap…
What constraints do vendor platforms impose on governance, and how should…
What governance constraints are imposed by major vendor Artificial Intelligence (AI) and low-code platforms, specifically, what governance capabilities are natively supported versus where external con…
How can enterprise data governance frameworks be consistently enforced within…
How can enterprise data governance frameworks be consistently enforced within Artificial Intelligence (AI) and visual, minimal-code application environments, specifically, how should data classificati…
How should AI and low-code governance integrate with existing software…
How should Artificial Intelligence (AI) and low-code governance integrate with existing software development and platform engineering practices, specifically, how should governance controls be integra…
How can enterprise Artificial Intelligence (AI) and low-code governance…
How can enterprise Artificial Intelligence (AI) and low-code governance frameworks be aligned with external regulatory and compliance obligations, specifically, what is the mapping between governance…
What observability and telemetry model is required to govern Artificial…
What observability and telemetry model is required to govern AI and low-code systems at scale, specifically, what must be logged, at what frequency, and at what level of granularity, including prompt…
What lifecycle management model is required for Artificial Intelligence (AI)…
What comprehensive lifecycle management model is required for AI models, prompts, and low-code applications, covering versioning strategies, deployment controls, rollback mechanisms, ownership trackin…
Where should governance enforcement points be implemented within enterprise…
Where should governance enforcement points be implemented within enterprise architecture for Artificial Intelligence (AI) and low-code systems, specifically, at which architectural layers (Application…
What is the cost, performance, and delivery impact of governance controls on AI…
What is the cost, performance, and delivery impact of governance controls on AI and low-code development, specifically, what economic model quantifies the trade-offs between governance strength and de…
Implicit rate-limiting controls removed by agentic Artificial Intelligence (AI)
Prior to agentic Artificial Intelligence (AI), the blast radius of ungoverned citizen development was implicitly bounded by human speed, attention, fatigue, and working hours, controls that are not do…
Deployment pipeline as the only enforceable control gate for citizen-developed…
In an environment where citizen development tooling is already licensed and accessible to non-technical staff, and where the distinction between personal productivity and production automation has col…
Policy coherence as a machine-checkable prerequisite
Contradictory or outdated policy documents are a chronic governance failure that organisations tolerate because the consequences under human operation are slow-moving. Under agentic operation, agents…
Systems capability debt as the root cause of citizen development
What empirical evidence exists that systems capability debt, the accumulated gap between what people need from their systems and what those systems deliver across integration, functionality, data acce…
Systems capability debt, citizen development, and agentic AI risk
Does the synthesis of technical debt literature (Cunningham, Kruchten), systems capability research, transaction cost economics (Coase, Williamson), operational risk frameworks (Basel III/IV, Risk and…
Multi-provider AI control planes
Which platforms or architectural designs provide multi-provider Artificial Intelligence (AI) control planes that unify discoverability, oversight, logging, security, data-access control, Financial Ope…
Global artificial intelligence agent regulation in financial services
What regulatory obligations do financial-services regulators globally, including the European Union (EU), Australia, New Zealand (NZ), the United States (US), and the United Kingdom (UK), impose on Ar…
Business-led low-code agent governance
Under what conditions does business-led low-code Artificial Intelligence (AI) agent creation produce durable organisational value versus technical debt and governance fragmentation, and what foundatio…
Automated governance assurance and change control verification patterns for…
What technical patterns exist for automating governance assurance and change control verification in Artificial Intelligence (AI)-assisted delivery pipelines, specifically audit evidence generation, p…
Harness-level selection and use of tools, agents, skills, prompts, and…
When should teams choose tools, agent definition files, skills, prompts, instruction files, and AGENTS.md, and what verifiable best practices align with how major harnesses actually select and apply e…
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…
oh-my-codex and AI Agent Workflow Patterns
What patterns from oh-my-codex (OMX) and similar AI agent workflow projects (AGENTS.md, SKILL.md, etc.) are most applicable to improving the instructions, skills, agents, and tooling across davidamitc…
Anthropic Claude Code leak
What does the accidental March 2026 leak of Anthropic's Claude Code source code reveal about: (1) the codebase architecture, (2) how key engineering problems are solved, (3) the prompting and instruct…
Claude Code npm Source Map Leak
How did the March 2026 accidental leak of Anthropic's Claude Code source code via an npm (Node Package Manager) package occur, and what processes and protections can organisations adopt to prevent sim…
AI Funding and Capital Investment Landscape
Which Artificial Intelligence (AI)-related and tech companies are receiving and deploying capital investment in 2023-2026, who the major investors are, where investment is concentrated, and what actio…
Backpressure Infrastructure and the Theory of Constraints
What is backpressure infrastructure, specifically as it pertains to the Theory of Constraints (TOC), and what does academic research and real-world white papers say about its practical application?
Multi-agent repo setup
What are the best practices for setting up a GitHub repository so that it can be worked on effectively by multiple Artificial Intelligence (AI) agents, specifically: (1) Claude via the iOS Claude app,…
Claude Code on the web
Does Claude Code on the web automatically initialise git submodules when cloning a repository, and if so, can it access private submodules (such as `davidamitchell/Skills` referenced at `.github/skill…
Environment setup consistency
Given the two primary agent entry points, (A) assigning a GitHub issue to the Copilot coding agent and (B) using the Claude iOS `code` feature, what environment does each agent start in, and what cont…
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…
The Software Factory
If the cost of producing high-quality, standardised, integrated software is approaching zero — as Artificial Intelligence (AI) coding agents and software factory patterns suggest — what must organisat…
Agent orchestration patterns
What agent orchestration patterns, verification strategies, and multi-model delegation techniques are demonstrated by Burke Holland's Anvil, Max, and the orchestrator/planner/coder/designer multi-agen…
How to best use awesome-copilot in this repo and across personal repos
What resources from `davidamitchell/awesome-copilot` — GitHub Copilot (GHC) instructions, skills, agents, workflows, hooks, and plugins — provide the most leverage when applied to this Research repo a…
Code Architecture Inspection Across Repositories
What practical implementation approaches exist for automatically inspecting and understanding how a set of repositories is architected, how they relate to and couple with each other, and whether they…
Tracking How Work Travels Across Organisational Systems
Can we track how a unit of 'Work' -- an idea or concept -- travels across organisational systems (SharePoint, Confluence, Azure DevOps (ADO)/Jira, Git, monitoring systems, and data platforms), and wha…
Cross-Scanner Compliance Evidence and Waiver Normalisation in GitHub Actions
How should an organisation running multiple compliance scanners in GitHub Actions normalise evidence, severity, waiver handling, and developer-facing output so that heterogeneous tools behave like one…
Compliance Scanning via GitHub Actions — Broad Policy as Code Across a…
How can GitHub Actions (with GitHub Advanced Security (GHAS) and CodeQL already enabled) be extended to enforce a broad, organisation-wide compliance policy — covering naming conventions, architectura…
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…
Coding AI Agent Skills Survey
What actively maintained, publicly available agent skills, prompt libraries, instructions files, and system prompts exist — from vendors such as Microsoft and from the Open Source Software (OSS) commu…
Dependency Mapping Across .NET Codebases, Terraform, Dynatrace, Confluence, Log…
What practical tools and methodologies are being used to map dependencies across .NET codebases, Terraform configurations, Dynatrace Application Performance Management (APM) monitoring, and solution d…
More formal proof engineering
What does Leanstral - an open-source agent for formal proof engineering - offer as a practical path to trustworthy, formally verified software built with Artificial Intelligence (AI) assistance, and h…
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…
Vision-Language Joint Embedding Predictive Architecture (VL-JEPA) and concept…
What is Vision-Language Joint Embedding Predictive Architecture (VL-JEPA) - specifically its concept prediction mechanism - and what practical options exist for a developer consumer of existing fronti…
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…
GitAgent and declarative agent definition
What is GitAgent (https://github.com/open-gitagent/gitagent), how can it be used in this repository, what concepts does it build on and produce, and how does the broader idea of declarative agent defi…
Adaptive Policy-Based Authorization (APBA)
How does Adaptive Policy-Based Authorization (APBA) align with the dynamic access-control requirements of National Institute of Standards and Technology (NIST) Special Publication (SP) 800-53 and ISO/…
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…
Ricardian Contract model
What is the Ricardian Contract model proposed by Ian Grigg in 1996, how has it evolved over the past three decades, who is actively building with it today, and what does the latest academic and applie…
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…
Hosting options for the Research repo
What is the best free or very-low-cost hosting option for this research repository that supports full-text search, and optionally vector/graph database capabilities, without requiring SEO, custom DNS,…
Best practices in financial forecasting for IT operational run costs
What are the established best practices for financially responsible forecasting of Information Technology (IT) operational run costs — covering cost estimation by technology and infrastructure type, r…
Research loop evaluation rubric
What structured rubric should be used to evaluate the outputs of this repository's research loop agent — and what does a minimal viable implementation of a Continuous Integration (CI)-integrated eval…
Superpowers as inspiration
What ideas, patterns, and workflow practices from `davidamitchell/superpowers` (a fork of `obra/superpowers`) can be used as inspiration for improving agent tooling in `davidamitchell/Latest-developme…
Language designed for LLM agents to produce
Is anyone actively developing a programming language or structured output format specifically designed for LLM agents to generate — rather than humans to write — that structurally addresses generation…
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…
Interface and delivery
Once research is complete and outputs are produced, how should they be surfaced and delivered to the people (or agents) who need them? What interfaces make research outputs most usable?
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 Process Mapping
What options exist within ServiceNow for documenting, mapping, and maintaining business and IT processes — and which approaches are sustainable enough in practice to stay meaningful, current, and actu…
Self-hosted MCP server options
What is the minimum viable self-hosted deployment of `mcp_server.py` (or a write-only HTTP wrapper) that: (a) is reachable from the public internet, (b) has zero or near-zero ongoing cost, (c) require…
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…
Emergent Patterns in Software Engineering Prompts and SDLC Guidance
What are the current and emergent best practices for crafting AI agent prompts and tooling guidance tailored to each phase of the Software Development Life Cycle (SDLC) — covering discovery, requireme…
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…
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…
How organisations practically implement IT RUN vs BUILD cost allocation
How have organisations actually implemented a working RUN vs BUILD IT cost allocation — specifically: how did they agree on what counts as an "application", how did they get consistent work-item taggi…
Slack and MS Teams integration for research delivery and capture
What is the most practical way to integrate the research corpus with Slack and/or Microsoft Teams — for both outbound delivery (notifying when new research is completed) and inbound capture (receiving…
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…
RUN vs BUILD IT spending allocation in non-IT primary businesses
How do non-IT primary businesses (manufacturing, retail, finance) calculate and apportion IT spending between RUN (nondiscretionary operational sustainment) and BUILD (discretionary strategic enhancem…
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…
Guiding Headless Agents via LSP-Like Mechanisms for Org Policy Conformance
Who is building solutions that allow headless autonomous coding agents to be guided in real time by LSP-like mechanisms — rather than CI gates or pre-commit hooks — to conform to an organisation's sec…
YouTube transcripts via yt-dlp audio + Whisper transcription
Can we bypass YouTube's IP-based transcript block by downloading the **audio track** with
`yt-dlp` (a different endpoint from the transcript API) and then transcribing it with
OpenAI Whisper?
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?
Swarm Intelligence, PCA, Genetic Algorithms, and Reinforcement Learning —…
What is the structured, decision-oriented landscape of four advanced technique families — Swarm Intelligence, Principal Component Analysis (PCA) and its modern extensions, Genetic Algorithms and Evolu…
Self-improving Artificial Intelligence (AI) agent evaluation loop architecture
What is the most principled architecture for a Self-Improving AI Agent Evaluation Loop — specifically, how should a nested inner/outer loop be designed so that a "Meta-Optimizer" rewrites system promp…
Artificial Intelligence (AI) coding assistant deployment outcomes
Which organisations have published or disclosed coherent AI strategies specifically targeting software engineering, what outcomes have they measured, and what does the trajectory from AI-assisted codi…
Sources of research: what to monitor and how
What are the best sources for AI/ML research, and what is the right monitoring strategy for each — RSS, YouTube channels, arXiv, newsletters, GitHub?
Research output types
What are the possible output types from a research item, and how should each type be handled, stored, and acted upon?
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?
Evaluating and improving autonomous research loop quality
How can the quality of research items produced by the `research-loop.yml` autonomous pipeline be systematically evaluated, and what changes to `research-prompt.md` and the loop's prompting strategy wo…
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 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…
Enterprise Artificial Intelligence (AI) efficiency programme outcomes
Which published AI strategies — corporate, national, or sector-specific — are explicitly designed around business efficiency as the primary objective, what measurable outcomes have they produced, and…
YouTube transcript fetcher for research
Can we port the YouTube transcript fetcher from `davidamitchell/Latest-developments-` to this repo and adapt it for research use (bulk fetch, save transcripts, not just email digest)?
GitHub wiki for research content
What is the best approach for publishing completed research items from `Research/completed/` into the GitHub wiki, and what tooling is needed to keep it current and readable?
Simple process for adding a research item
What is the minimum-friction workflow for adding a new research item so that good ideas get captured before they are lost?
Keeping research backlog separate from repo improvement backlog
What is the cleanest way to separate two distinct types of work — *what to research* vs *how to improve this repo* — so that neither overwhelms the other and each can be prioritised independently?
GitHub Specify, Ralph Loops, and Lisa Planning
What is "Specify" in the context of GitHub-integrated AI development workflows, how does the Ralph loop implement proof-driven development in practice, and what role does Lisa planning play in the spe…
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…
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?