The Intent Debt — Knowledge Graph Meshup
type: CreativeWork
description: A knowledge graph collection of Addy Osmani's The Intent Debt (O'Reilly Radar, 2026-08-14), coherently meshed with supplementary content from the agent-rdf-memory skill, Kingsley Uyi Idehen's Agent Skills, Filesystems, and Context Graphs, and The File Create, Save, and Share Paradigm — Revisited. The mesh thesis: intent debt is paid down by externalizing intent into artifacts agents can read, and agent-rdf-memory, Agent Skills, Filesystems/WebDAV, and Context Graphs are the concrete mechanisms for doing that at scale.
about: The Intent Debt
date created: 2026-08-14T00:00:00Z
author: this

Intent Debt Meshup Ontology
type: Ontology
name: Intent Debt — Externalized Intent Ontology
description: Lightweight ontology for modeling the Triple Debt Model's debt kinds, the practices and mechanisms that externalize intent into artifacts agents can read, and the mesh between The Intent Debt and the supplementary OpenLink/agent-rdf-memory sources.

Debt Kind
type: Class
name: The Three Debts
comment: One of the three kinds of software debt in Margaret-Anne Storey's Triple Debt Model: technical, cognitive, or intent debt.

Externalization Mechanism
type: Class
comment: A mechanism that moves intent out of human heads and into artifacts an agent can read — an RDF memory store, an agent skill, a filesystem interface, or a context graph.

Paydown Practice
type: Class
comment: A practice for paying down intent debt by externalizing rationale as a first-class artifact.

has debt kind
type: Property
comment: Links a system, article, or claim to the debt kind it concerns.
domain: Resource
range: Debt Kind

externalized via
type: Property
comment: Links intent or rationale to the mechanism that externalizes it.
domain: Resource
range: Externalization Mechanism

kg-generator
type: SoftwareApplication
description: Knowledge Graph generation skill of the ai-agent-skills repository: transforms source documents into standards-compliant RDF using curated prompt templates.
is part of: ai-agent-skills

rdf-infographic-skill
type: SoftwareApplication
description: RDF-based HTML and Markdown infographic generation skill: converts RDF knowledge graphs into interactive, self-contained HTML infographics with a strict harness contract.
is part of: ai-agent-skills

DeepSeek V4 Flash
type: SoftwareApplication
description: The language model that authored this RDF collection and its HTML/Markdown companions under the ai-agent-skills contract.

ai-agent-skills
type: CodeRepository
description: OpenLink Software's collection of reusable AI agent skills for querying semantic web data sources, knowledge graphs, and databases.

The Intent Debt
type: NewsArticle
type: Article
type: CreativeWork
abstract: Technical debt lives in your code. Cognitive debt lives in your head. Intent debt lives in the artifacts you may never have written: the goals, constraints, and rationale for why the system is the way it is. It is the one kind of debt your agents cannot pay down for you — and agentic engineering makes it the most expensive. Addy Osmani's The Intent Debt (O'Reilly Radar, 2026-08-14, republished from addyosmani.com with the author's permission) builds on Margaret-Anne Storey's Triple Debt Model: technical debt accumulates in code, cognitive debt erodes shared understanding in people, and intent debt is the absence or erosion of the externalized rationale that explains why a system is the way it is. Because agents start every session cold and fabricate plausible rationales for decisions they never made, unexternalized intent now accrues interest every session, multiplied by every agent on the team. The paydown is externalization: write the spec for the intent, treat AGENTS.md as an intent ledger, capture decisions where they happen, and make the learning loop write intent back down. This collection meshes that thesis with three supplementary sources — the agent-rdf-memory skill (a queryable RDF behavioral contract that externalizes agent intent as a first-class artifact), Kingsley Uyi Idehen's Agent Skills, Filesystems, and Context Graphs (the convergence architecture in which skills encapsulate intent, filesystems carry artifacts, and context graphs materialize meaning), and The File Create, Save, and Share Paradigm — Revisited (WebDAV and Briefcase as the distribution layer for intent artifacts humans and agents can both read).
article body: Technical debt lives in the code. Cognitive debt lives in people. Intent debt lives in artifacts — the goals, constraints, and rationale for why the system is the way it is. Intent debt is the one kind of debt agents cannot pay down for you: a model can infer a plausible rationale from code, but a guess about intent is not the intent. The paydown is externalizing the why as a first-class artifact: specs for intent, AGENTS.md as an intent ledger, lightweight decision logs, and learning loops that write intent back down.
author: Addy Osmani
publisher: O'Reilly Radar
date published: 2026-08-14T16:04:40Z
date modified: 2026-08-14T16:04:40Z
language: en
main entity of page: https://oreillyradar.substack.com/p/the-intent-debt
is part of: oreillyradar.substack.com
is based on: The Intent Debt
keywords: intent debt, technical debt, cognitive debt, comprehension debt, Triple Debt Model, AI agents, agentic engineering, externalized rationale, AGENTS.md, decision logs, ADR, agent skills, context graphs, WebDAV, agent-rdf-memory, orchestration tax
about: Intent Debt
citation: Agent Skills, Filesystems, and Context Graphs: Collapsing Software Complexity at the Root
citation: The File Create, Save, and Share Paradigm — Revisited
citation: agent-rdf-memory
has debt kind: Intent Debt
has part: Three Places Debt Can Live
has part: Why Intent Debt Is the One Agents Can't Help With
has part: Agents Make the Unwritten Cost Compound Much Faster
has part: The Other Half of the Comprehension Debt Argument
has part: What High Intent Debt Looks Like
has part: Paying It Down: Externalize Intent as a First-Class Artifact
has part: Where the Value Moved
has part: The Mesh: Externalized Intent in the OpenLink Data Space
has part: Related Reading
has part: Frequently Asked Questions
has part: Glossary of Terms
has part: Paying Down Intent Debt: Externalize Intent as a First-Class Artifact
was generated by: kg-generator
was generated by: rdf-infographic-skill
was generated by: DeepSeek V4 Flash

The Intent Debt
type: Article
name: The Intent Debt (original)
description: The original version of The Intent Debt as published on Addy Osmani's blog site; the O'Reilly Radar Substack post is a republication with the author's permission.
author: Addy Osmani

pullQuote
type: Quotation
text: The why is the one thing it can only fabricate.
author: Addy Osmani
description: Punch line of The Intent Debt: of the three debts, intent debt is the only one an agent cannot bail you out of — the why is the one thing it can only fabricate. Rendered as the synopsis deck pull-quote.

Three Places Debt Can Live
type: CreativeWork
abstract: Margaret-Anne Storey's Triple Debt Model is a clean way to think about software health: technical debt lives in the code, cognitive debt lives in people, and intent debt lives in artifacts. The three are independent — you can have low technical debt and high intent debt — and each one bills you separately.
position: 1
is part of: The Intent Debt
has part: Technical Debt
has part: Cognitive Debt
has part: Intent Debt
has part: The three debts are independent

Technical Debt
type: DefinedTerm
type: Debt Kind
description: Accumulation of implementation choices that make the system harder to change later: the tangled module, the shortcut taken under deadline, the abstraction that leaked. Understood for decades; felt through slow builds, fragile tests, and the dread of touching one particular file.
position: 1
is part of: Three Places Debt Can Live

Cognitive Debt
type: DefinedTerm
type: Debt Kind
description: Erosion of shared understanding — the gap between how much code exists and how much any human understands; Osmani calls it comprehension debt. Builds up when the system grows faster than the team's mental model, so pristine code can still carry crippling cognitive debt.
position: 2
is part of: Three Places Debt Can Live

Intent Debt
type: DefinedTerm
type: Debt Kind
alternate name: The debt agents can't pay
description: Absence or erosion of the externalized rationale, goals, and constraints that explain why the system is the way it is. The key word is externalized: rationale must be written down where a teammate, a future you, or an agent can read it. When intent debt runs high, the system drifts from what you meant it to do.
position: 3
is part of: Three Places Debt Can Live

The three debts are independent
type: CreativeWork
description: You can have low technical debt and high intent debt. You can understand a system completely yourself while its intent exists nowhere outside your skull — enormous intent debt for everyone else. From the inside they feel alike, but each one bills you separately.
position: 4
is part of: Three Places Debt Can Live

Why Intent Debt Is the One Agents Can't Help With
type: CreativeWork
abstract: AI makes technical debt cheaper to take on and cheaper to pay down, and cognitive debt recovers more easily than most engineers expect. Intent is different: an agent cannot generate intent, because intent is the one input that has to come from you. A guess about intent is not the intent.
position: 2
is part of: The Intent Debt
has part: Agents pay technical debt down
has part: Agents restore comprehension on demand
has part: Intent must originate with you
has part: The invented confident-sounding reason
has part: The why is the one thing it can only fabricate

Agents pay technical debt down
type: CreativeWork
description: AI generates code faster than ever, which makes technical debt cheaper to take on and cheaper to pay down. Point an agent at a tangled module and it will refactor it.
position: 1
is part of: Why Intent Debt Is the One Agents Can't Help With

Agents restore comprehension on demand
type: CreativeWork
description: When you don't understand a chunk of the system, you ask the agent to explain it and rebuild part of the lost mental model on demand, because the code still exists and the model can read it back to you.
position: 2
is part of: Why Intent Debt Is the One Agents Can't Help With

Intent must originate with you
type: CreativeWork
description: An agent can't generate intent, because intent is the one input that has to come from you. A model can infer a plausible rationale from the code, the same way you can guess why a previous engineer did something — but a guess about intent isn't the intent.
position: 3
is part of: Why Intent Debt Is the One Agents Can't Help With

The invented confident-sounding reason
type: CreativeWork
description: The model doesn't know whether that 300ms debounce was a deliberate UX decision, a benchmark result, or a number someone typed once and never revisited. It will invent a confident-sounding reason, which is worse than admitting it doesn't know.
position: 4
is part of: Why Intent Debt Is the One Agents Can't Help With

The why is the one thing it can only fabricate
type: CreativeWork
description: Of the three debts, intent debt is the only one where the agent can't bail you out. It can write the code and restore your comprehension. The why is the one thing it can only fabricate.
position: 5
is part of: Why Intent Debt Is the One Agents Can't Help With

Agents Make the Unwritten Cost Compound Much Faster
type: CreativeWork
abstract: Teams got away with high intent debt for years because intent moved person to person — hallway conversations, code review comments, the engineer who had been there four years as walking intent documentation. Agents break that model: each one is a teammate who has never met you, starts sessions cold, and fills every gap with a plausible guess.
position: 3
is part of: The Intent Debt
has part: Intent used to move person to person
has part: Agents break the tacit-transfer model
has part: The economics of not writing things down changed
has part: The twenty agents you're so excited to parallelize
has part: Orchestration tax is partly intent-debt tax

Intent used to move person to person
type: CreativeWork
description: When a new human joined a team, you didn't write everything down: intent was picked up over time through hallway conversations, code review comments, and 'we don't do it that way because of an incident in 2023.' The four-year engineer was the intent documentation — expensive and lossy, but it worked.
position: 1
is part of: Agents Make the Unwritten Cost Compound Much Faster

Agents break the tacit-transfer model
type: CreativeWork
description: Bringing agents onto a team doubles its size overnight with junior people who have no long-term memory. An agent starts most sessions cold and carries none of the tacit intent humans built up over years. Whatever you haven't externalized into an artifact it can read, it doesn't have.
position: 2
is part of: Agents Make the Unwritten Cost Compound Much Faster

The economics of not writing things down changed
type: CreativeWork
description: Unexternalized intent used to cost you once in a while, at onboarding or after someone left. Now you pay it every session, multiplied by every agent you run.
position: 3
is part of: Agents Make the Unwritten Cost Compound Much Faster

The twenty agents you're so excited to parallelize
type: CreativeWork
description: Each one is a teammate who has never met you, can't read your mind, and will fill any gap in your intent with a plausible guess. The orchestration tax is partly an intent-debt tax: much of what makes managing many agents exhausting is resupplying the intent you never wrote down.
position: 4
is part of: Agents Make the Unwritten Cost Compound Much Faster

Orchestration tax is partly intent-debt tax
type: CreativeWork
description: Much of what makes managing many agents exhausting is resupplying the intent you never wrote down — the orchestration tax Osmani wrote about is partly an intent-debt tax.
position: 5
is part of: Agents Make the Unwritten Cost Compound Much Faster

The Other Half of the Comprehension Debt Argument
type: CreativeWork
abstract: Detailed specs aren't a complete answer — a spec detailed enough to be the program is the program in a slower language. Intent debt is the complementary truth: being unable to capture all intent is no license to capture none of it. Code is the answer; the intent was the question it was meant to solve.
position: 4
is part of: The Intent Debt
has part: Specs are not a complete answer
has part: No license to capture none of it
has part: Record the load-bearing why
has part: Code is the answer; intent was the question

Specs are not a complete answer
type: CreativeWork
description: Translating a spec into working code involves a huge number of implicit decisions no spec ever captures, and a spec detailed enough to be the program is the program in a slower language.
position: 1
is part of: The Other Half of the Comprehension Debt Argument

No license to capture none of it
type: CreativeWork
description: Being unable to capture all intent is no license to capture none of it. The implicit decisions an agent now makes on your behalf, the ones a spec will never enumerate, are the decisions whose rationale evaporates if you don't record at least the load-bearing ones.
position: 2
is part of: The Other Half of the Comprehension Debt Argument

Record the load-bearing why
type: CreativeWork
description: You do have to write down the why behind the choices that would be expensive to get wrong, because nobody will reconstruct those later.
position: 3
is part of: The Other Half of the Comprehension Debt Argument

Code is the answer; intent was the question
type: CreativeWork
description: Comprehension debt warns you not to trust that code is correct because it exists. Intent debt warns you not to trust that the reason survives because the code does. AI is brilliant at producing answers to questions you forgot to write down.
position: 4
is part of: The Other Half of the Comprehension Debt Argument

What High Intent Debt Looks Like
type: CreativeWork
abstract: Intent debt rarely shows up as friction; it shows up as a particular kind of helplessness: a guard clause deleted and no one can say whether it was load-bearing, a refactor that changed behavior the tests never encoded, a queue where the honest answer is 'an agent suggested it and it seemed fine.'
position: 5
is part of: The Intent Debt
has part: The deleted guard clause
has part: The refactor that changed behavior
has part: Why do these services talk over a queue?
has part: Cognitive surrender, at team scale

The deleted guard clause
type: CreativeWork
description: An agent 'fixes' a bug by deleting a guard clause, and nobody can say whether that guard was load-bearing or leftover, because no doc or commit message ever recorded why it was there.
position: 1
is part of: What High Intent Debt Looks Like

The refactor that changed behavior
type: CreativeWork
description: A refactor changes a behavior users depend on. The review passed because the diff looked clean and the tests were green, but the tests only encoded the previous behavior, never the intent.
position: 2
is part of: What High Intent Debt Looks Like

Why do these services talk over a queue?
type: CreativeWork
description: You ask why two services talk over a queue instead of a direct call, and the honest answer is 'an agent suggested it and it seemed fine.' That answer is intent debt, already accruing interest.
position: 3
is part of: What High Intent Debt Looks Like

Cognitive surrender, at team scale
type: CreativeWork
description: Cognitive surrender is defending a design choice you can't reconstruct — your own posture in the moment. Intent debt is what a hundred of those moments leave in the repo for the next person and the next agent to inherit.
position: 4
is part of: What High Intent Debt Looks Like

Paying It Down: Externalize Intent as a First-Class Artifact
type: CreativeWork
abstract: Almost everything Osmani has been writing about for months turns out to be intent-debt management. The move is the same each time: take the intent out of your head and put it somewhere an agent can read — a spec for intent, AGENTS.md as an intent ledger, lightweight decision logs, and a learning loop that writes intent back down.
position: 6
is part of: The Intent Debt
has part: Write the spec for the intent, not the implementation
has part: Treat AGENTS.md as your intent ledger, not your config
has part: Capture decisions where they happen
has part: Make the learning loop write intent back down

Write the spec for the intent, not the implementation
type: CreativeWork
description: A good spec captures the goals, the constraints, the nonnegotiables, and an explicit definition of done — fast, accessible, secure, delightful, beyond 'functionally correct.' The spec carries the intent the code can't carry on its own.
position: 1
is part of: Paying It Down: Externalize Intent as a First-Class Artifact

Treat AGENTS.md as your intent ledger, not your config
type: CreativeWork
description: An auto-generated file describes what the code is. An intent file describes what the team means: the conventions, the 'we don't do it this way because,' the constraints invisible in any single file. Agents can't infer that, and they need it most.
position: 2
is part of: Paying It Down: Externalize Intent as a First-Class Artifact

Capture decisions where they happen
type: CreativeWork
description: Lightweight decision logs (ADRs) are pure intent-debt paydown. Recording why at the moment you decide costs almost nothing; reconstructing it eight months later, after the person who knew why has moved teams, costs a fortune. Agents have made logging cheaper than ever, so the old excuse is gone.
position: 3
is part of: Paying It Down: Externalize Intent as a First-Class Artifact

Make the learning loop write intent back down
type: CreativeWork
description: Self-improving agents update a learnings file at the end of a session. The same loop is an intent-debt pump running in reverse: every mistake whose root cause you've recorded, every 'we tried X and it didn't work because Y,' is intent that would otherwise have lived only in your memory of a bad afternoon.
position: 4
is part of: Paying It Down: Externalize Intent as a First-Class Artifact

Where the Value Moved
type: CreativeWork
abstract: For a long time the scarce, valuable thing in software was the ability to produce a correct implementation; code was expensive, so we optimized for writing it. AI made code cheap and comprehension recoverable. Intent — the goals, constraints, and reasons — is the one input that still has to originate with a human, and the one we're worst at externalizing.
position: 7
is part of: The Intent Debt
has part: Code used to be the scarce asset
has part: Intent is the one input that still originates with a human
has part: Write down the why

Code used to be the scarce asset
type: CreativeWork
description: For a long time, the scarce, valuable thing in software was the ability to produce a correct implementation. Code was expensive, so we optimized for writing it.
position: 1
is part of: Where the Value Moved

Intent is the one input that still originates with a human
type: CreativeWork
description: AI made code cheap, and comprehension is recoverable. Intent, the goals and constraints and reasons, is the one input that still has to originate with a human — and the one we're worst at externalizing, because for decades we got away with carrying it in our heads.
position: 2
is part of: Where the Value Moved

Write down the why
type: CreativeWork
description: Technical debt makes your system hard to change. Cognitive debt makes it hard to understand. Intent debt makes it hard to know whether the system still does what you wanted, and it's the only one of the three your agents can't pay back for you. Write down the why, because it's becoming the most valuable thing you can leave in the repo.
position: 3
is part of: Where the Value Moved

The Mesh: Externalized Intent in the OpenLink Data Space
type: CreativeWork
abstract: Addy Osmani's paydown practices are not abstract: this collection meshes them with three supplementary sources that operationalize externalized intent. The agent-rdf-memory skill is the AGENTS.md-as-intent-ledger practice made concrete — a queryable RDF behavioral contract an agent must read before every task. Idehen's Agent Skills, Filesystems, and Context Graphs provides the convergence architecture: skills encapsulate intent, filesystems carry artifacts, and context graphs materialize meaning. And The File Create, Save, and Share Paradigm — Revisited supplies the distribution layer: WebDAV and Briefcase publishing intent artifacts where humans and agents can both read them.
author: kg-generator
accountable person: Kingsley Uyi Idehen
position: 8
is part of: The Intent Debt
has part: Agent RDF Memory: intent as a queryable artifact
has part: Agent Skills: intent encapsulated as capability
has part: Filesystems: the lowest-friction intent artifact layer
has part: Context Graphs: meaning as a materialized view
has part: The retrieval protocol: intent read before action
has part: Synthesis: intent debt is the artifact-side debt
was generated by: kg-generator
was generated by: rdf-infographic-skill
was generated by: DeepSeek V4 Flash

Agent RDF Memory: intent as a queryable artifact
type: CreativeWork
type: Externalization Mechanism
description: The agent-rdf-memory skill and store externalize an agent's behavioral contract as RDF-Turtle: preferences.ttl is a hub-and-spoke schema:HowTo of 200+ HowToStep rules (the operationalized intent ledger), core.ttl pins identity, sessions/ records episodic decisions per day and agent, howto/ carries full specifications, entities/ is the registry, and a mandatory retrieval protocol makes the agent read that intent before every task. This is 'treat AGENTS.md as your intent ledger' executed as infrastructure.
position: 1
is part of: The Mesh: Externalized Intent in the OpenLink Data Space
externalized via: agent-rdf-memory

Agent Skills: intent encapsulated as capability
type: CreativeWork
type: Externalization Mechanism
description: From Idehen's Agent Skills, Filesystems, and Context Graphs: a skill reframes software functionality as a reusable, composable capability that encapsulates intent, constraints, access to data/information/knowledge, and a repeatable workflow pattern. OPAL lowers the creation barrier so domain experts declare skills in Markdown rather than code — skills are declared, not engineered — shifting value from application ownership toward expertise, verification, and trust.
position: 2
is part of: The Mesh: Externalized Intent in the OpenLink Data Space
externalized via: OPAL (OpenLink AI Layer)

Filesystems: the lowest-friction intent artifact layer
type: CreativeWork
type: Externalization Mechanism
description: Filesystems re-emerge not because they are simplistic but because they are universally understood: a stable abstraction, human- and machine-friendly access, natural scoping of context, and compatibility with decades of tooling. Inputs look like documents, outputs look like documents, and intermediate results can be persisted, inspected, and reused. Modern systems treat filesystems as interfaces, not primitive storage — the create-save-share paradigm revisited via WebDAV.
position: 3
is part of: The Mesh: Externalized Intent in the OpenLink Data Space
externalized via: webdav

Context Graphs: meaning as a materialized view
type: CreativeWork
type: Externalization Mechanism
description: A context graph is a materialized view over data, information, and knowledge, scoped to a particular task or intent: entity-relationship graphs constructed using standardized identifiers, derived using declarative constraints, manifested in consumable forms — often as files. Declarative query languages already solve constraint definition, scope control, and result materialization; what changed is that AI agents can now use these graphs directly rather than merely store them. The externalized why becomes queryable.
position: 4
is part of: The Mesh: Externalized Intent in the OpenLink Data Space

The retrieval protocol: intent read before action
type: CreativeWork
type: Externalization Mechanism
description: The agent-rdf-memory mandatory sequence — list the store, read core.ttl, preferences.ttl, index.ttl, ontology.ttl, then follow rdfs:seeAlso references — is the operationalized version of Osmani's 'treat AGENTS.md as your intent ledger': intent is read, not guessed, before any task executes, and written back after meaningful work.
position: 5
is part of: The Mesh: Externalized Intent in the OpenLink Data Space
externalized via: agent-rdf-memory

Synthesis: intent debt is the artifact-side debt
type: CreativeWork
description: The Triple Debt Model maps cleanly onto the convergence architecture: technical debt lives in code, cognitive debt lives in people, intent debt lives in artifacts — and Agent Skills, Filesystems, and Context Graphs are artifact infrastructure that pays intent debt down structurally. A skill packages the why of a workflow; a filesystem carries the written-down rationale; a context graph materializes it as queryable meaning. Write the why once, and it compounds for every agent that reads it.
position: 6
is part of: The Mesh: Externalized Intent in the OpenLink Data Space

Related Reading
type: CreativeWork
abstract: The article's inline references — Osmani's companion posts — plus the two supplementary Idehen articles and the Triple Debt Model paper that anchor this mesh.
position: 9
is part of: The Intent Debt
has part: Comprehension Debt
has part: The Orchestration Tax
has part: Cognitive Surrender
has part: A Good Spec
has part: Stop Using /init: AGENTS.md
has part: Automated Decision Logs
has part: Self-Improving Agents
has part: Agent Skills, Filesystems, and Context Graphs: Collapsing Software Complexity at the Root
has part: The File Create, Save, and Share Paradigm — Revisited
has part: The Triple Debt Model

Comprehension Debt
type: NewsArticle
description: Addy Osmani's companion post on comprehension debt — the erosion of shared understanding — which intent debt sharpens and complements.
position: 1
is part of: Related Reading
author: Addy Osmani

The Orchestration Tax
type: NewsArticle
description: Addy Osmani's post on the cost of managing many agents — partly an intent-debt tax, since much of the exhaustion is resupplying intent that was never written down.
position: 2
is part of: Related Reading
author: Addy Osmani

Cognitive Surrender
type: NewsArticle
description: Addy Osmani's post on defending design choices you can't reconstruct — the personal-posture version of the same hole that intent debt leaves at team scale.
position: 3
is part of: Related Reading
author: Addy Osmani

A Good Spec
type: NewsArticle
description: Addy Osmani's post on writing specs that capture goals, constraints, nonnegotiables, and an explicit definition of done — the spec for intent, not the implementation.
position: 4
is part of: Related Reading
author: Addy Osmani

Stop Using /init: AGENTS.md
type: NewsArticle
description: Addy Osmani's post arguing that AGENTS.md should be an intent file — what the team means — not an auto-generated description of what the code is.
position: 5
is part of: Related Reading
author: Addy Osmani

Automated Decision Logs
type: NewsArticle
description: Addy Osmani's post on lightweight ADRs as pure intent-debt paydown — recording why at the moment you decide, made cheaper than ever by agents.
position: 6
is part of: Related Reading
author: Addy Osmani

Self-Improving Agents
type: NewsArticle
description: Addy Osmani's post on agents that update a learnings file at the end of a session — a learning loop that writes intent back down.
position: 7
is part of: Related Reading
author: Addy Osmani

Agent Skills, Filesystems, and Context Graphs: Collapsing Software Complexity at the Root
type: NewsArticle
name: Agent Skills, Filesystems, and Context Graphs
description: Kingsley Uyi Idehen's thesis (LinkedIn Pulse, 2026-01-18): the real breakthroughs come not from new application categories but from a convergence of Agent Skills, Filesystems, and Context Graphs — structurally addressing the translation tax of accidental complexity. OPAL lowers the skill-creation barrier; Virtuoso exposes DBMS capabilities through a WebDAV filesystem interface; the future of software is context-centric.
author: Kingsley Uyi Idehen
publisher: AI & Data Driven Enterprise
date published: 2026-01-18T00:00:00Z
position: 8
is part of: Related Reading
comment: commentKarpagam
comment: commentDinis
comment: commentKingsleyNotebookLM

The File Create, Save, and Share Paradigm — Revisited
type: NewsArticle
description: Kingsley Uyi Idehen's essay (LinkedIn Pulse, 2025-07-19): before HTTP, data was held captive in application-specific documents; URIs, HTTP, HTML, and RDF liberated it. The create-save-share paradigm — modernized with Virtuoso's Briefcase and WebDAV — lets authors write with AI tools, save to public folders, syndicate via RSS/Atom/OPML, add metadata, and control access, reviving decentralized standards-based publishing.
author: Kingsley Uyi Idehen
publisher: AI & Data Driven Enterprise
date published: 2025-07-19T00:00:00Z
position: 9
is part of: Related Reading

The Triple Debt Model
type: ScholarlyArticle
name: The Triple Debt Model (Margaret-Anne Storey et al.)
description: The paper behind the three models of software health — technical, cognitive, and intent debt — that The Intent Debt builds on.
author: Margaret-Anne Storey
position: 10
is part of: Related Reading

commentKarpagam
type: Comment
text: Beyond the 'context graph' (memory), we need brain, CNS, hand and legs — a five-pillar architecture in production: memory (context of decisions made), brain/inference (from storing data to active reasoning), nervous system/dataflows (orchestrating across siloed systems), hands/engagement (rendering insights where work happens), and legs/governance (the unsexy RBAC, security, and reliability layer that lets the system stand).
author: Karpagam Narayanan
about: Agent Skills, Filesystems, and Context Graphs: Collapsing Software Complexity at the Root

commentDinis
type: Comment
text: This looks very aligned with how I'm also working — can you share that NotebookLM PDF separately?
author: Dinis Cruz
about: Agent Skills, Filesystems, and Context Graphs: Collapsing Software Complexity at the Root

commentKingsleyNotebookLM
type: Comment
text: I clearly forgot to share the NotebookLM PDF. Here's the link: https://www.openlinksw.com/data/pdf/Agents_Files_Context_Structural_Convergence.pdf
author: Kingsley Uyi Idehen
about: Agent Skills, Filesystems, and Context Graphs: Collapsing Software Complexity at the Root

Addy Osmani
type: Person
description: Former engineering leader at Google, bestselling Amazon author, award-winning engineer and international speaker. Author of The Intent Debt; writes about software engineering, motivation, and leadership.
works for: Google

Kingsley Uyi Idehen
type: Person
description: Founder & CEO of OpenLink Software; creator of Virtuoso; Semantic Web pioneer. Author of Agent Skills, Filesystems, and Context Graphs and The File Create, Save, and Share Paradigm — Revisited.
works for: OpenLink Software

Margaret-Anne Storey
type: Person
description: Professor of Computer Science at the University of Victoria and Canada Research Chair; software engineering researcher and author of the Triple Debt Model.
works for: University of Victoria

Tim Berners-Lee
type: Person
description: Inventor of the World Wide Web — URIs, URLs, HTTP, and HTML — and co-director of the World Wide Web Consortium; his Web foundations underpin the create-save-share paradigm revisited in the supplementary sources.
works for: World Wide Web Consortium

Dave Winer
type: Person
description: Software developer and blogging pioneer; creator of Radio UserLand and the OPML format; his work made the create-save-share paradigm accessible to authors.

Karpagam Narayanan
type: Person
description: Commenter on the Agent Skills, Filesystems, and Context Graphs article; proposes a five-pillar production agent architecture (memory, inference, dataflows, engagement, governance).

Dinis Cruz
type: Person
description: Commenter on the Agent Skills, Filesystems, and Context Graphs article; independent application security researcher who found the structural-convergence approach aligned with his own work.

O'Reilly Media
type: Organization
description: Technology learning company publishing books, courses, and the O'Reilly Radar publication; parent of the O'Reilly Radar Substack.

O'Reilly Radar
type: Organization
description: O'Reilly's publication on the trends shaping tech, hosted on Substack; publisher of The Intent Debt.
sub organization of: O'Reilly Media

AI & Data Driven Enterprise
type: Organization
description: LinkedIn publication page by Kingsley Uyi Idehen (4,006 followers) hosting his Pulse articles, including Agent Skills, Filesystems, and Context Graphs and The File Create, Save, and Share Paradigm — Revisited.

OpenLink Software
type: Organization
description: Developer of Virtuoso, OPAL, and the ai-agent-skills repository; founded by Kingsley Uyi Idehen.

Google
type: Organization
description: Technology company; Addy Osmani's former employer as an engineering leader.

University of Victoria
type: Organization
description: Canadian university where Margaret-Anne Storey is a professor of computer science and Canada Research Chair.

World Wide Web Consortium
type: Organization
description: International standards organization for the Web, co-directed by Tim Berners-Lee.

Anthropic
type: Organization
description: AI safety and research company; maker of the Claude AI assistant mentioned in The File Create, Save, and Share Paradigm — Revisited.

OpenAI
type: Organization
description: AI research and deployment company; maker of ChatGPT, mentioned in The File Create, Save, and Share Paradigm — Revisited.

LinkedIn
type: Organization
description: Professional networking platform whose Pulse publishing surface hosts the two supplementary Idehen articles.

OPAL (OpenLink AI Layer)
type: SoftwareApplication
description: OpenLink AI Layer: simplifies Agent and Agent Skill creation by letting domain experts work in Markdown rather than code-heavy frameworks. Skills are declared, not engineered; intent, data access, and constraints live together; deployment becomes configuration-driven; skills stay loosely coupled to underlying data spaces; MCP/A2A compliant.

Virtuoso
type: SoftwareApplication
description: OpenLink's multi-model DBMS (SQL, SPARQL, GraphQL, RDF quad store, WebDAV filesystem). Extends its model by transparently exposing DBMS capabilities through a filesystem interface via WebDAV: SQL and SPARQL query results materialized as files, context graphs as directories and documents.

ChatGPT
type: SoftwareApplication
description: OpenAI's AI assistant; cited in The File Create, Save, and Share Paradigm — Revisited as one of the modern writing tools that make content creation faster while ownership and distribution remain open questions.

Claude
type: SoftwareApplication
description: Anthropic's AI assistant; cited in The File Create, Save, and Share Paradigm — Revisited as a modern writing tool for Web-style publishing.
author: Anthropic

Gemini
type: SoftwareApplication
description: Google's AI assistant; cited in The File Create, Save, and Share Paradigm — Revisited as a modern writing tool for Web-style publishing.

Radio UserLand
type: SoftwareApplication
description: Dave Winer's blogging tool that enabled authors to publish HTML documents and syndicate content easily via RSS, Atom, and OPML, fostering an open ecosystem of publication and subscription.
author: Dave Winer

agent-rdf-memory
type: SoftwareApplication
type: Externalization Mechanism
description: OpenLink's Agent RDF Memory skill: a queryable behavioral contract for AI agents encoded as RDF-Turtle — core.ttl (identity and output routing), preferences.ttl (hub-and-spoke schema:HowTo of 200+ HowToStep rules), index.ttl (session index), sessions/ (episodic memory), howto/ (specifications), entities/ (registry), and a mandatory retrieval protocol. The operationalized intent ledger.
is part of: ai-agent-skills
has part: preferences.ttl
has part: core.ttl
has part: index.ttl
has part: sessions/
has part: howto/
has part: entities/
has part: ontology.ttl
has part: agent-rdf-memory/AGENTS.md

preferences.ttl
type: CreativeWork
description: The queryable behavioral contract hub: a schema:HowTo (agentBehaviorGuide) with schema:hasPart sub-HowTos and 200+ schema:HowToStep entries — the standing rules an agent must follow, i.e., the intent ledger made queryable.
is part of: agent-rdf-memory

core.ttl
type: CreativeWork
description: Long-term knowledge: user identity, agent identity template, and output-path routing for generated artifacts.
is part of: agent-rdf-memory

index.ttl
type: CreativeWork
description: Summary index of sessions and files — a schema:ItemList of schema:ListItem entries pointing at every session file.
is part of: agent-rdf-memory

sessions/
type: CreativeWork
description: Episodic memory: one Turtle file per day, LLM, and agent environment, recording prompts, tasks, artifacts, decisions, and lessons — the decision log at infrastructure scale.
is part of: agent-rdf-memory

howto/
type: CreativeWork
description: Companion specification files, one per sub-HowTo, carrying the full rationale, code, gates, and incident notes referenced by preferences.ttl steps.
is part of: agent-rdf-memory

entities/
type: CreativeWork
description: Registry of people, organizations, tools, and concepts with canonical IRIs — the shared identity layer of the memory store.
is part of: agent-rdf-memory

ontology.ttl
type: CreativeWork
description: Custom vocabulary: prompt-intent classes, retrieval policies, and ontology-routed context-selection rules.
is part of: agent-rdf-memory

agent-rdf-memory/AGENTS.md
type: CreativeWork
description: The prose entry point of the memory protocol: mandatory retrieval sequence, folder structure, session naming, storage rules, and enforcement — the intent ledger read before every task.
is part of: agent-rdf-memory

Frequently Asked Questions
type: FAQPage
description: Fifteen questions about intent debt and its mesh with agent-rdf-memory, Agent Skills, Filesystems, and Context Graphs.
position: 10
is part of: The Intent Debt
main entity: What is intent debt?
main entity: How does intent debt differ from technical and cognitive debt?
main entity: Why can't AI agents pay down intent debt?
main entity: Why do agents make the cost of unwritten intent compound?
main entity: What does high intent debt look like in practice?
main entity: What is the paydown for intent debt?
main entity: What is the difference between a spec for intent and a spec for implementation?
main entity: Why should AGENTS.md be treated as an intent ledger?
main entity: What role do decision logs (ADRs) play in paying down intent debt?
main entity: How does agent-rdf-memory externalize agent intent?
main entity: How do Agent Skills relate to intent debt?
main entity: How do filesystems and WebDAV help externalize intent?
main entity: What is a context graph and how does it relate to externalized intent?
main entity: How does the create-save-share paradigm apply to intent artifacts?
main entity: Is intent debt the same as cognitive debt?
has part: What is intent debt?
has part: How does intent debt differ from technical and cognitive debt?
has part: Why can't AI agents pay down intent debt?
has part: Why do agents make the cost of unwritten intent compound?
has part: What does high intent debt look like in practice?
has part: What is the paydown for intent debt?
has part: What is the difference between a spec for intent and a spec for implementation?
has part: Why should AGENTS.md be treated as an intent ledger?
has part: What role do decision logs (ADRs) play in paying down intent debt?
has part: How does agent-rdf-memory externalize agent intent?
has part: How do Agent Skills relate to intent debt?
has part: How do filesystems and WebDAV help externalize intent?
has part: What is a context graph and how does it relate to externalized intent?
has part: How does the create-save-share paradigm apply to intent artifacts?
has part: Is intent debt the same as cognitive debt?

What is intent debt?
type: Question
accepted answer: a1
position: 1
is part of: Frequently Asked Questions

a1
type: Answer
text: Intent debt is the absence or erosion of the externalized rationale, goals, and constraints that explain why a system is the way it is. The key word is externalized: the why must be written down where a teammate, a future you, or an agent can read it, not held in your head. When intent debt runs high, the system drifts from what you meant it to do, and nobody can say when it diverged or why.
position: 1

How does intent debt differ from technical and cognitive debt?
type: Question
accepted answer: a2
position: 2
is part of: Frequently Asked Questions

a2
type: Answer
text: Technical debt lives in the code — implementation choices that make change harder. Cognitive debt lives in people — the gap between how much code exists and how much anyone understands. Intent debt lives in artifacts — the missing externalized why. The three are independent: you can have low technical debt and high intent debt, and each one bills you separately.
position: 2

Why can't AI agents pay down intent debt?
type: Question
accepted answer: a3
position: 3
is part of: Frequently Asked Questions

a3
type: Answer
text: An agent can refactor tangled code and restore comprehension by reading code back to you, but intent is the one input that has to originate with a human. A model can only infer a plausible rationale from the code — a guess about intent is not the intent — and a confident-sounding invented reason is worse than admitting it doesn't know. The why is the one thing it can only fabricate.
position: 3

Why do agents make the cost of unwritten intent compound?
type: Question
accepted answer: a4
position: 4
is part of: Frequently Asked Questions

a4
type: Answer
text: Teams used to absorb intent through hallway conversations, code review comments, and long tenure — the four-year engineer was the intent documentation. Agents start every session cold, carry none of that tacit intent, and fill any gap with a plausible guess. Unexternalized intent that once cost you once in a while now costs you every session, multiplied by every agent you run.
position: 4

What does high intent debt look like in practice?
type: Question
accepted answer: a5
position: 5
is part of: Frequently Asked Questions

a5
type: Answer
text: An agent 'fixes' a bug by deleting a guard clause and nobody can say whether it was load-bearing or leftover; a refactor changes behavior users depend on while tests only encoded the previous behavior, never the intent; and the honest answer to 'why do these services talk over a queue?' is 'an agent suggested it and it seemed fine.' Intent debt shows up as a particular kind of helplessness.
position: 5

What is the paydown for intent debt?
type: Question
accepted answer: a6
position: 6
is part of: Frequently Asked Questions

a6
type: Answer
text: Externalize intent as a first-class artifact: write the spec for the intent not the implementation, treat AGENTS.md as an intent ledger, capture decisions where they happen in lightweight ADRs, and make the learning loop write intent back down. Take the intent out of your head and put it somewhere an agent can read.
position: 6

What is the difference between a spec for intent and a spec for implementation?
type: Question
accepted answer: a7
position: 7
is part of: Frequently Asked Questions

a7
type: Answer
text: An implementation spec describes what the code does. A spec for intent captures the goals, the constraints, the nonnegotiables, and an explicit definition of done — fast, accessible, secure, delightful, beyond 'functionally correct.' The spec carries the intent the code can't carry on its own.
position: 7

Why should AGENTS.md be treated as an intent ledger?
type: Question
accepted answer: a8
position: 8
is part of: Frequently Asked Questions

a8
type: Answer
text: An auto-generated file describes what the code is. An intent file describes what the team means: the conventions, the 'we don't do it this way because' history, the constraints invisible in any single file. Agents can't infer those, and they need them most — so stop using /init and write the intent down.
position: 8

What role do decision logs (ADRs) play in paying down intent debt?
type: Question
accepted answer: a9
position: 9
is part of: Frequently Asked Questions

a9
type: Answer
text: Recording why at the moment you decide costs almost nothing; reconstructing it eight months later, after the person who knew why has moved teams, costs a fortune. Lightweight decision logs are pure intent-debt paydown, and agents have made logging cheaper than ever, so the old excuse is gone.
position: 9

How does agent-rdf-memory externalize agent intent?
type: Question
accepted answer: a10
position: 10
is part of: Frequently Asked Questions

a10
type: Answer
text: It encodes the behavioral contract as queryable RDF-Turtle: preferences.ttl is a hub-and-spoke schema:HowTo of 200+ HowToStep rules (the intent ledger), core.ttl pins identity and output routing, sessions/ records episodic decisions per day and agent, howto/ carries full specifications, entities/ is the registry — and a mandatory retrieval protocol makes the agent read that intent before every task. It is 'treat AGENTS.md as your intent ledger' executed as infrastructure.
position: 10

How do Agent Skills relate to intent debt?
type: Question
accepted answer: a11
position: 11
is part of: Frequently Asked Questions

a11
type: Answer
text: A skill reframes functionality as a reusable, composable capability that encapsulates intent, constraints, access to data/information/knowledge, and a repeatable workflow pattern. Packaging intent inside a skill is externalization: the why of a workflow becomes an artifact agents can discover, invoke, combine, and verify — instead of a plausible guess. OPAL lets domain experts declare those skills in Markdown.
position: 11

How do filesystems and WebDAV help externalize intent?
type: Question
accepted answer: a12
position: 12
is part of: Frequently Asked Questions

a12
type: Answer
text: Filesystems are the lowest-friction artifact layer: inputs look like documents, outputs look like documents, and intermediate results can be persisted, inspected, and reused. Virtuoso's WebDAV interface materializes SQL and SPARQL results and context graphs as files; the Briefcase adds create-save-share publishing with auto-generated RSS, Atom, and OPML feeds, optional metadata, and attribute-based access control — decentralized standards-based publishing without surrendering control.
position: 12

What is a context graph and how does it relate to externalized intent?
type: Question
accepted answer: a13
position: 13
is part of: Frequently Asked Questions

a13
type: Answer
text: A context graph is a materialized view over data, information, and knowledge, scoped to a particular task or intent: entity-relationship graphs constructed with standardized identifiers, derived using declarative constraints, and manifested in consumable forms — often as files. Declarative query languages already solve constraint definition, scope control, and result materialization; what changed is that agents can now use these graphs directly. It turns the externalized why into something queryable.
position: 13

How does the create-save-share paradigm apply to intent artifacts?
type: Question
accepted answer: a14
position: 14
is part of: Frequently Asked Questions

a14
type: Answer
text: Before HTTP, data was held captive in application-specific documents. URIs, HTTP, HTML, and RDF liberated it — unambiguous naming, negotiable content types, hypertext, and hyperdata. The create-save-share paradigm — writing into a public folder like /html/, syndicating via RSS, Atom, and OPML, adding metadata, controlling access — is the distribution layer that puts externalized intent where both humans and agents can read it.
position: 14

Is intent debt the same as cognitive debt?
type: Question
accepted answer: a15
position: 15
is part of: Frequently Asked Questions

a15
type: Answer
text: No — they are complementary truths. Cognitive (comprehension) debt is the erosion of shared understanding in people; intent debt is the absence of externalized rationale in artifacts. Comprehension debt warns you not to trust that code is correct because it exists; intent debt warns you not to trust that the reason survives because the code does. Code is the answer; the intent was the question it was meant to solve.
position: 15

Glossary of Terms
type: DefinedTermSet
description: Sixteen terms spanning the Triple Debt Model and the externalization mechanisms of the mesh.
position: 11
is part of: The Intent Debt
has defined term: Cognitive Debt
has defined term: Triple Debt Model
has defined term: Externalized Rationale
has defined term: Agent Skill
has defined term: Context Graph
has defined term: Materialized View
has defined term: Filesystem Interface
has defined term: WebDAV
has defined term: OPAL
has defined term: Architecture Decision Record
has defined term: Orchestration Tax
has defined term: Cognitive Surrender
has defined term: Intent Ledger
has defined term: Create-Save-Share Paradigm
has defined term: Definition of Done
has defined term: Self-Improving Agent
has part: Cognitive Debt
has part: Triple Debt Model
has part: Externalized Rationale
has part: Agent Skill
has part: Context Graph
has part: Materialized View
has part: Filesystem Interface
has part: WebDAV
has part: OPAL
has part: Architecture Decision Record
has part: Orchestration Tax
has part: Cognitive Surrender
has part: Intent Ledger
has part: Create-Save-Share Paradigm
has part: Definition of Done
has part: Self-Improving Agent

Cognitive Debt
type: DefinedTerm
description: Erosion of shared understanding — the gap between how much code exists and how much any human understands; also called comprehension debt.
in defined term set: Glossary of Terms

Triple Debt Model
type: DefinedTerm
description: Margaret-Anne Storey's framework of three independent models of software health: technical debt in code, cognitive debt in people, and intent debt in artifacts.
in defined term set: Glossary of Terms

Externalized Rationale
type: DefinedTerm
description: The goals, constraints, and reasons behind a system written down where a teammate, a future you, or an agent can read them — the opposite of intent held only in a human head.
in defined term set: Glossary of Terms

Agent Skill
type: DefinedTerm
description: A reusable, composable capability that encapsulates intent, constraints, access to data/information/knowledge, and a repeatable workflow pattern, discoverable and invocable by agents.
in defined term set: Glossary of Terms

Context Graph
type: DefinedTerm
description: A materialized view over data, information, and knowledge, scoped to a particular task or intent: an entity-relationship graph built with standardized identifiers, derived with declarative constraints, and manifested in consumable forms such as files.
in defined term set: Glossary of Terms

Materialized View
type: DefinedTerm
description: A precomputed, queryable result of a declarative specification — in the mesh, the pattern by which context graphs manifest meaning as consumable artifacts.
in defined term set: Glossary of Terms

Filesystem Interface
type: DefinedTerm
description: Treating a filesystem as an interface rather than primitive storage: inputs look like documents, outputs look like documents, and intermediate results can be persisted, inspected, and reused.
in defined term set: Glossary of Terms

WebDAV
type: DefinedTerm
description: Web Distributed Authoring and Versioning (RFC 4918): an HTTP extension that turns a server into an authorable filesystem, letting DBMSs expose SQL/SPARQL results and context graphs as files and folders.
in defined term set: Glossary of Terms

OPAL
type: DefinedTerm
description: OpenLink AI Layer: Markdown-driven Agent and Agent Skill definition in which skills are declared, not engineered — intent, data access, and constraints live together and deployment becomes configuration-driven.
in defined term set: Glossary of Terms

Architecture Decision Record
type: DefinedTerm
description: A lightweight, dated record of a decision and its rationale, captured where the decision happens — pure intent-debt paydown.
in defined term set: Glossary of Terms

Orchestration Tax
type: DefinedTerm
description: The cost of managing many agents — partly an intent-debt tax, since much of the exhaustion is resupplying the intent you never wrote down.
in defined term set: Glossary of Terms

Cognitive Surrender
type: DefinedTerm
description: The personal posture of defending a design choice you can't reconstruct; intent debt is the team-scale, written-down version of the same hole.
in defined term set: Glossary of Terms

Intent Ledger
type: DefinedTerm
description: A durable, readable record of what a team means — conventions, constraints, and 'we don't do it this way because' history — such as an authored AGENTS.md or an RDF behavioral contract.
in defined term set: Glossary of Terms

Create-Save-Share Paradigm
type: DefinedTerm
description: The minimal publishing pattern of the early Web — create content, save it into a public folder, and share it via open syndication — modernized with WebDAV, Briefcase, and RSS/Atom/OPML feeds.
in defined term set: Glossary of Terms

Definition of Done
type: DefinedTerm
description: The explicit quality bar of a spec for intent — fast, accessible, secure, delightful, beyond 'functionally correct' — that carries intent the code cannot carry on its own.
in defined term set: Glossary of Terms

Self-Improving Agent
type: DefinedTerm
description: An agent that updates a learnings file at the end of a session — a learning loop that writes intent back down instead of leaving it in memory.
in defined term set: Glossary of Terms

Paying Down Intent Debt: Externalize Intent as a First-Class Artifact
type: HowTo
description: Seven steps — four from the article's paydown practices and three meshing in the supplementary OpenLink/agent-rdf-memory mechanisms — for moving intent out of human heads and into artifacts agents can read.
position: 12
is part of: The Intent Debt
step: Write the spec for the intent, not the implementation
step: Treat AGENTS.md as your intent ledger, not your config
step: Capture decisions where they happen with lightweight ADRs
step: Make the learning loop write intent back down
step: Externalize agent intent as queryable RDF (the agent-rdf-memory pattern)
step: Package intent, constraints, and workflows as Agent Skills
step: Publish intent artifacts through filesystem interfaces and feeds

Write the spec for the intent, not the implementation
type: HowToStep
text: Capture the goals, the constraints, the nonnegotiables, and an explicit definition of done — fast, accessible, secure, delightful, beyond 'functionally correct.' The spec carries the intent the code cannot carry on its own.
position: 1

Treat AGENTS.md as your intent ledger, not your config
type: HowToStep
text: Describe what the team means: the conventions, the 'we don't do it this way because' history, and the constraints invisible in any single file. Agents cannot infer these, and they need them most — stop using /init and author the intent file.
position: 2

Capture decisions where they happen with lightweight ADRs
type: HowToStep
text: Record why at the moment you decide: it costs almost nothing then, and reconstructing it eight months later — after the person who knew why has moved teams — costs a fortune. Agents have made logging cheaper than ever, so the old excuse is gone.
position: 3

Make the learning loop write intent back down
type: HowToStep
text: End sessions by updating a learnings file: every mistake whose root cause you record, every 'we tried X and it didn't work because Y,' is intent that would otherwise live only in your memory of a bad afternoon.
position: 4

Externalize agent intent as queryable RDF (the agent-rdf-memory pattern)
type: HowToStep
text: Encode the behavioral contract as RDF-Turtle: a preferences.ttl hub of schema:HowToStep rules, core.ttl identity, episodic session files, companion howto specifications, and an entity registry — with a retrieval protocol that makes the agent read intent before every task and write decisions back afterward.
position: 5

Package intent, constraints, and workflows as Agent Skills
type: HowToStep
text: Define skills as reusable capabilities that encapsulate intent, constraints, data access, and a repeatable workflow pattern — declared in Markdown via OPAL — so agents discover, invoke, combine, and verify what a team means instead of guessing.
position: 6

Publish intent artifacts through filesystem interfaces and feeds
type: HowToStep
text: Save outputs to structured public folders — WebDAV /html/, /screencasts/, /screenshots/ — that auto-generate RSS, Atom, and OPML feeds, carry optional metadata for discovery, and apply attribute-based access control, so externalized intent reaches humans and agents alike.
position: 7

Intent rules in the agent memory store
type: SoftwareSourceCode
programming language: SPARQL
text: PREFIX schema: <http://schema.org/> SELECT ?step ?name WHERE { ?howto schema:step ?step . ?step schema:name ?name . FILTER(CONTAINS(LCASE(?name), "intent") || CONTAINS(LCASE(?name), "agents.md") || CONTAINS(LCASE(?name), "decision")) } ORDER BY ?step
comment: Finds the behavioral-contract rules in preferences.ttl that operationalize intent externalization — the intent ledger made queryable.
target: sparql
code sample type: SPARQL SELECT

Session artifacts (episodic intent records)
type: SoftwareSourceCode
programming language: SPARQL
text: PREFIX schema: <http://schema.org/> SELECT ?session ?artifact ?format WHERE { ?session a schema:CreativeWork ; schema:result ?artifact . ?artifact schema:fileFormat ?format . } LIMIT 25
comment: Lists sessions and the RDF/HTML/MD artifacts they produced — the decision log at infrastructure scale, queryable across the session index.
target: sparql
code sample type: SPARQL SELECT

Debt kinds in this knowledge graph
type: SoftwareSourceCode
programming language: SPARQL
text: PREFIX : <https://oreillyradar.substack.com/p/the-intent-debt#> PREFIX schema: <http://schema.org/> SELECT ?debt ?name WHERE { ?debt a :DebtKind ; schema:name ?name . } ORDER BY ?debt
comment: Returns the three debt kinds of the Triple Debt Model as modeled in this collection.
target: sparql
code sample type: SPARQL SELECT