A W3C DCAT catalog of all published content from The Mantle Institute: essays, interactive resources, playbook skills, future role profiles, and knowledge references on human agency in the AI era.
Essays and analysis on human agency, AI adoption, and the future of work.
Four things leaders must get right on automation and AI
The automation opportunity is not just a growth play. For many organisations it is increasingly a capacity question. What separates transformation that lasts from programmes that fail to return benefits.
In an AI-augmented ecosystem, the things organisations have traditionally hired for move down the priority list. Here is what moves up, and what education needs to produce.
When the Scaffolding Becomes the Job: Notes from a Fortnight of Operational AI
A fortnightly synthesis of AI strategy, healthcare technology, and transformation signals for practitioners navigating the human side of change.
AI is not taking the world. It is clarifying it, revealing what has always mattered most. Five missions for the people willing to step into what only they can do.
The Ocean Ecosystem: A Post-Transformation Paradigm for AI
After twenty years of transformation programmes, the ocean offers the clearest model for what determines whether AI adoption actually works — and data is only one of four elements.
On knowing where you came from, and why it matters more than ever.
On building AI that activates rather than replaces
If the goal is human flourishing, every adoption decision becomes a question about who gets activated and what they get to keep.
On the different classes of Human + AI engagement emerging, and why agency matters more than adoption.
On capability debt, the silent gap GenAI and remote work are widening, and four structural moves to close it.
An interactive ocean exploration game. Guide Wren through two levels of the deep — gathering knowledge, finding your shoal, and learning that you are not alone in what you don't yet know. Based on The Practitioner.
An illustrated fable for young readers about purpose, work, and finding your place. Wren the fish leaves the safety of the Grey Bay and discovers that the work she always did matters — when it is in the service of something real. With narrated audio.
Human/AI skills and workflow patterns across the Ocean Framework.
A four-persona method for extracting the incontrovertible truth from any written argument — what it cannot escape claiming, what it is really fighting against, and the subsidiary truths that survive the debate.
A human-led, AI-assisted workflow for producing rigorous, adversarially-reviewed written content — from rough idea to publish-ready article — at a fraction of the usual time investment.
The foundational layer of Human/AI collaboration — everyday tasks where AI assistance is straightforward, immediate, and accessible regardless of technical background.
A judgment-led, two-phase workflow for fulfilling customer dataset requests — AI-driven search and generation, with adversarial loops on both data and documentation before secure airlock publish.
A fifteen-minute end-of-session protocol for AI-augmented work — five questions that extract genuine learning from every build session and compound your Learning Rate over time.
How to progress from manual AI lineage logging to an automated workflow that captures your working process as a byproduct of how you work — voice notes, session hooks, and AI-assisted structuring.
How to find, start, and maintain a small group of practitioners who compound your learning — including cold-start approaches for remote and isolated practitioners.
A personal AI-assisted database of failures and their extracted lessons — with a two-step capture workflow, AI-assisted processing, and pattern-finding that turns individual mistakes into a map of your specific failure modes.
AI-augmented role profiles grounded in the SFIA framework.
A senior clinician who uses AI decision-support tools to coordinate complex care pathways — synthesising multi-modal patient data, flagging risk signals, and ensuring that clinical judgement always holds primacy over algorithmic recommendation.
A researcher who works alongside AI systems to accelerate hypothesis generation, literature synthesis, and analytical modelling — while maintaining rigorous human oversight of methodology, interpretation, and publication integrity.
An executive leader responsible for shaping an organisation's AI adoption strategy — ensuring that AI investment is maturity-matched, ethically grounded, and aligned to human capability development rather than headcount reduction.
An operations professional who designs and manages AI-assisted workflows — identifying automation opportunities, managing exception handling, and ensuring that human accountability is never displaced by process automation.
A senior technical leader who designs the systems, governance layers, and integration patterns that allow AI to operate safely inside complex organisations — ensuring explainability, auditability, and appropriate human oversight at every boundary.
The senior leader responsible for building and sustaining an AI-augmented organisation that earns the right to run itself — establishing the Creed that governs how AI is used across every team, setting the Current that aligns autonomous practitioners without constant supervision, and reading the ecological health of the whole organisation using the diagnostic instruments the ocean requires.
The technical leader who designs and governs the knowledge infrastructure — the Reef — that every AI-augmented practitioner in the organisation depends on. Responsible for ensuring that domain expertise is captured in reusable Skill templates, that knowledge navigability is maintained as the Reef grows, and that the line between what should be automated and what must stay human is enforced at the architecture level.
The operational leader responsible for ensuring groups of AI-augmented practitioners move in formation — compounding collective intelligence rather than keeping learning locked in individual workflows. Responsible for the pastoral layer that reads team health before tissue tears, and for maintaining the Handoff Contracts and governance architecture that keep multi-disciplinary AI workflows coherent under pressure.
The AI-augmented knowledge worker operating at the front line of an ocean organisation — a practitioner who carries deep domain expertise into close partnership with AI, producing insight that neither could generate alone. The School Practitioner is the unit of productive capability in the ocean: their judgement directs the AI, their expertise validates its output, and their Creed governs what it will and will not produce.
The people and culture leader responsible for the human architecture of an ocean organisation — designing the Creed, governing the conditions in which practitioners thrive or deplete, and maintaining the Validator Accountability Protocol that distinguishes genuine human-AI collaboration from passive rubber-stamping. Where the Shoal Orchestrator keeps the teams moving, the Ecological Intelligence Lead keeps the water worth swimming in.
The Mantle Institute — Knowledge References
Curated references to frameworks, standards, legislation, and guides relevant to responsible AI adoption.
Designed to help organisations make decisions about access to sensitive data: safe projects, safe people, safe data, safe settings, safe outputs. Developed by the ONS and now the backbone of Secure Data Environments and Trusted Research Environments across the NHS.
DCB0129 — Clinical Risk Management: Manufacture of Health IT
The clinical safety standard that applies to any health IT system whose malfunction or misuse could harm a patient. Covers clinical safety cases, hazard logs, and the requirement for a designated Clinical Safety Officer. Applies to most AI tools entering clinical pathways.
DCB0160 — Clinical Risk Management: Deployment of Health IT
The deploying organisation's counterpart to DCB0129. NHS trusts accepting health IT systems must conduct their own clinical safety assessment in their own context — they cannot simply accept the vendor's safety case. Most organisations do not know they hold this obligation.
TOGAF — The Open Group Architecture Framework
The global standard for enterprise architecture. Its four domains — business, data, application, technology — remain relevant for AI deployments, though most organisations skip straight to application and technology. That is precisely where AI strategies fail.
The most extraordinary manufacturing feat in human history: firing lasers at tin beads to generate plasma hotter than the sun, producing chips with features measured in nanometres. Essential context for anyone thinking seriously about AI's physical cost.
Anthropic's initiative exploring AI safety, transparency, and the long-term trajectory of frontier AI development. Relevant to anyone thinking about responsible AI adoption and what 'AI for good' actually requires in practice.
SFIA — Skills Framework for the Information Age
The global standard for defining digital and technology skills. The Future Roles section uses SFIA levels (3–7) and skill codes to ground AI-augmented roles in an established professional framework — connecting emerging human-AI capabilities to a language organisations already use for workforce planning.
NHS England's guidance on information governance for AI — covering data protection obligations, transparency requirements, and accountability frameworks specific to health and care settings. The bit most AI projects in the NHS skip until legal asks why they skipped it. Essential reading before any AI system touches patient data.
A Guide to Using AI in the Public Sector
The UK government's practical guidance for public sector organisations adopting AI — covering how to identify opportunities, assess readiness, procure responsibly, and govern deployment. Written for decision-makers rather than technologists. Useful framing for NHS and government bodies navigating AI adoption without a clear internal playbook.
The world's first comprehensive legal framework for artificial intelligence — risk-tiered, with outright prohibitions at the top and lighter obligations for minimal-risk systems. Healthcare AI sits firmly in the high-risk category. If you are deploying AI in a clinical or regulated setting, this is not optional reading: it is the compliance baseline that will shape procurement, governance, and accountability across the NHS and beyond.
A structured lens for reading the environment an organisation operates in: Political, Economic, Sociological, Technological, Legal, Environmental. Simple in concept, deceptively powerful in practice. Most strategy work skips it — which is why most strategies fail to anticipate the conditions they land in. Essential groundwork before any AI adoption plan that expects to survive contact with reality.