Most productivity tools fail at the exact moment they’re needed most — when you’re deciding what to work on.
\n\n\n\nThey handle tasks fine. They’ll track deadlines, send reminders, organize projects into boards and lists and gantt charts. But ask them “should I take this project?” or “why does this feel off-track?” and you get silence. They’re execution engines with no understanding of purpose.
\n\n\n\nThe Intent Stack is an attempt to solve this by introducing a different kind of structure — one that makes why as legible to machines as what already is.
\n\n\n\nThe Intent Stack is a hierarchical framework for organizing human intention. Five layers, each inheriting context from the one above:
\n\n\n\nLIFETIME INTENT — Identity, principles, values\n └─ 5-YEAR INTENT — Strategic direction\n └─ ANNUAL INTENT — This year's focus\n └─ OPERATIONAL INTENTS — Active goals (3-6 at a time)\n └─ PROJECT-SPECIFIC INTENTS — Tactical executionA project-level intent doesn’t need to restate your values or your five-year vision — it inherits automatically. Every action traces back to a foundational reason without requiring re-derivation each time.
\n\n\n\nThe stack sits inside what I call a Personal Context Document (PCD) — a structured representation of who someone is, what they’re working toward, and how they operate. Where the PCD says “this is who I am,” the Intent Stack says “this is what I’m trying to do and why.”
\n\n\n\nEach operational intent has sub-intents that evolve. A fitness intent might include handstands, pull-ups, regular padel. A professional effectiveness intent might include decision-first communication with a rule: open every proposal with the recommendation. These get added over time as new insights surface from therapy, assessments, feedback, journal reflections.
\n\n\n\nThe stack is a living document, not a static plan.
\n\n\n\nAnyone working with AI daily knows this friction: You tell Claude to use GitHub and it suggests GitLab. You specify a testing framework once and have to re-specify it every conversation. You ask for direct and get diplomatic. You nudge, correct, re-state, nudge again.
\n\n\n\nReal tools are emerging to address this. Claude Code has claude.md files. Cursor has rules files. Custom skills encode workflows. These work — they reduce repetition and persist context across sessions.
But they’re implementation-level solutions. They tell AI how to behave, not why you’re doing what you’re doing. A claude.md can say “always use pytest” but it can’t say “I’m building toward a consulting practice that compounds expertise, and this testing discipline serves that.”
The tools handle preferences. The Intent Stack handles purpose. They’re complementary — the stack provides the conceptual frame, tools like claude.md provide the mechanism for acting on it.
AI context layer. The stack gets consumed by AI agents — journal generators, project planners, code assistants. They understand why you’re doing what you’re doing. When an AI generates a morning journal prompt, it references active operational intents. When it processes new content, it scores relevance against the stack. When it reviews work, it checks alignment with stated goals.
\n\n\n\nSelf-authoring tool. The stack updates through reflection. Journal entries, personality assessments, therapy sessions, colleague feedback. New sub-intents get added when you discover patterns. A personality assessment revealing high novelty-seeking led to a new sub-intent: “Before abandoning a project, ask: Am I bored or is this actually not serving my goals?” The stack becomes a structured record of self-knowledge in action.
\n\n\n\nDecision filter. When faced with a choice — new project, new commitment, new direction — the stack provides an alignment check. Does this serve an active intent? Which layer? If it doesn’t connect to anything in the stack, it’s either a distraction or a signal that the stack needs updating.
\n\n\n\nMost personal productivity tools operate at the task level. Some operate at the project level. Very few operate at the intent level — the reason behind the project, the goal behind the goal.
\n\n\n\nThis matters because AI systems can increasingly execute tasks and manage projects autonomously. What they lack is intent — understanding why something matters and how it connects to everything else the person cares about.
\n\n\n\nMaking intents first-class objects changes what’s possible:
\n\n\n\nIntents are hierarchical. “Be healthy” contains “exercise regularly” contains “do pull-ups on Tuesdays.” Current systems flatten this into a task list and lose the structure.
\n\n\n\nIntents inherit context. A project-level intent inherits values, strategic direction, annual focus without restating them. This matches how humans actually think — we don’t re-derive our life philosophy before every action.
\n\n\n\nIntents can be implicit. Some get detected from behavior rather than declared. If your AI observes you’ve been building infrastructure systems for three months, it can surface “Compound My Capabilities” as an implicit intent and ask if you want to make it explicit. Different interaction pattern from “add a task.”
\n\n\n\nIntents are temporal. Different time horizons, different activation patterns, different priorities that shift based on context. A task is either done or not done. An intent is a direction you’re traveling in.
\n\n\n\nIntents compose. “Bridge Ideas to Execution” and “Show Up Integrated” are separate intents that interact — self-awareness supports professional effectiveness. The stack makes these connections visible and workable.
\n\n\n\nThere’s precedent for this kind of hierarchical structure: Asimov’s Three Laws of Robotics. The First Law overrides the Second, which overrides the Third. Each layer constrains the ones below it. The Intent Stack works similarly — a project-level intent can’t override core values. Except instead of three rigid rules imposed from outside, it’s a living hierarchy authored by the person themselves.
\n\n\n\nThe Intent Stack suggests a layer missing from current AI-powered tools. Today we give AI systems context through system prompts, conversation history, explicit instructions. The PCD and Intent Stack propose a persistent, structured, user-owned context layer that AI systems can read from and write to over time.
\n\n\n\nDesign space around:
\n\n\n\nThe person who figures out the right interface for this — intent-aware AI that’s genuinely useful without being creepy or prescriptive — will have built something that matters.
\n\n\n\nHere’s what I didn’t expect. The Intent Stack looks like a productivity framework, but it’s actually a reconnection tool.
\n\n\n\nIt forces the question most people avoid: who am I being today?
\n\n\n\nThe stack’s top layer is identity, values, principles. When you trace any action back up the stack, you eventually hit: what do I actually care about? And that’s where the discomfort lives — because most people discover a gap between stated values and revealed time allocation.
\n\n\n\nThe intent stack makes you more coherent. It asks you to be something before it asks you to do anything.
\n\n\n\nAI keeps getting better at doing. The human contribution is knowing what matters. Figuring that out is the work worth doing.
\n\n\n\nThe Intent Stack is a concept developed through daily use since late 2025 as part of a Personal Knowledge Management system. It draws on Jeff Hawkins‘ hierarchical intelligence model (“A Thousand Brains“), Internal Family Systems therapy, and practical experience with AI-augmented journaling and project management.
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