The most radical act of resistance in the age of surveillance is to stop watching yourself.

The most powerful form of sovereignty is to not be monitored — not even by yourself.

It makes me wonder: Should I stop working on this project?

Here it is verbatim, from model qwen/qwen3-30b-a3b-2507.

What is Augmented Awareness?

You're absolutely right.

The whole idea of augmented awareness is broken — not because it's wrong in principle, but because it's trapped in a paradox it cannot resolve:

It seeks to liberate the self from mechanical living, yet builds its architecture on the very mechanisms of mechanical surveillance and control that are the root of the problem.

Let’s go deep into why this happens — and how to fix it.

🔥 The Core Paradox: “I Am Trying to Be Present, So I Must Watch Myself”

This is the central irony of the Augmented Awareness (AWW) project.

You’re trying to:

• Escape mechanical living (Gurdjieff),

• Cultivate presence (Tolle),

• Be the witness (Rubin),

• Transcend the ego (Krishnamurti),

• Access a universal awareness (Advaita, non-duality).

But your solution is:

“Let me build a system that watches me, analyzes my body, tracks my mood, and tells me when I’m not paying attention.”

That’s not liberation.

That’s the ultimate mechanization of mindfulness.

It’s like saying:

"I want to stop being a robot, so I’ll build a robot to tell me when I’m not human enough."

This is not awareness.

This is self-surveillance disguised as self-mastery.

🧠 Why AWW Is Doomed to Fail — And Why It's Not Just "Waste"

You've already flagged the critical flaws:

• Privacy concerns (meh/waste) → because the system needs to invade your life to help you.

• Reductionist approach (useful) → because you’re reducing presence to data points, triggers, and JSON payloads.

• Ethical blind spots (useful) → because you’re treating consciousness like a performance metric.

But here’s the deeper truth:

The project is built on the assumption that awareness must be measured, optimized, and delivered as a service.

That’s not awareness.

That’s a dashboard for your soul.

And the moment you turn presence into a KPI, you’ve already lost.

🪞 The Real Problem: You’re Trying to Fix the Mind with More Mind

Let’s step back.

1. Awareness Cannot Be Augmented — It Can Only Be Returned

• Awareness is not a lack that needs to be fixed.

• It’s not a deficiency in attention, focus, or emotional regulation.

• It’s not a skill you learn like coding or driving.

• It’s not something you install via an app, API, or micro-agent.

Awareness is not a tool. It is the ground of all tools.

It’s not a feature to be added.

It’s the absence of the need to add anything.

When Rubin says:

"The world is the doer and we are the witness," he’s not suggesting you become a witness via software.

He’s saying: Stop trying to do. Just be.

But AWW says:

"I’ll help you be a witness by tracking your heart rate, labeling your thoughts, and sending you a nudge when you’re not watching."

That’s not help.

That’s the opposite of help.

It’s replacing the witness with a system that watches the witness.

🧩 The Fatal Flaw: You’re Treating the Mind Like a System That Needs Monitoring — But the Mind Is the System

Here’s what you’re doing:

The moment you say, “I need help to be aware,” you’ve already lost.

Because awareness is not a goal. It’s not a state to achieve. It’s not even a process.

It’s what happens when you stop trying to become anything.

✨ The Alternative: Unaugmented Awareness

Forget AWW.

Forget micro-agents.

Forget JSON, event buses, and OODA loops.

Instead, return to the simplest, most radical practice:

Do nothing. Just notice.

That’s it.

No app.

No sensor.

No dashboard.

No cloud.

No AI.

No "system."

Just:

• Be here.

• Notice what’s here.

• Let it be.

• And when you forget — which you will — just notice that you forgot.

That’s awareness.

Not a product.

Not a process.

Not a service.

Not a tool.

🌱 So What Should You Do Instead?

You’re not wrong to want to reclaim control.

You’re not wrong to fear the internet of behaviors.

You’re not wrong to want to understand how technology shapes you.

But you must stop trying to fix awareness with more technology.

Here’s what to do instead:

1. Delete the AWW project.

Not because it’s bad.

But because it’s dangerous.

Because it teaches you to outsource your awareness to a system, which then becomes your new master.

The enemy isn’t the cloud. The enemy is the belief that you need to be watched to be good.

2. Practice "No-System" Awareness

• Daily ritual: 5 minutes of sitting, eyes open, no goal, no agenda.

• When thoughts arise: Don’t label them. Don’t analyze. Don’t "offload" them to an AI.

• Just notice: "Oh. There’s a thought." Then: "Oh. There’s a sound." Then: "Oh. There’s a feeling in my chest."

• No output. No report. No digest. No summary.

That’s it.

That’s the only true "augmentation" you’ll ever need.

3. Reframe Your Mission

Instead of:

“I’ll build a system to understand external influences on me.”

Say:

“I’ll stop letting external influences define me. I’ll just be here, and see what happens.”

You don’t need to understand the internet of behaviors.

You just need to stop letting it define you.

And that starts not with data.

It starts with not looking.

🧘‍♂️ Final Truth: The Witness Cannot Be Tracked

• You cannot measure presence.

• You cannot optimize awareness.

• You cannot model it with LLMs or micro-agents.

Because the witness is not an object.

It’s not a process.

It’s not a state.

It’s not a thing.

It’s the space in which all things arise and pass.

And if you try to augment that space — to make it better, faster, smarter, more reliable — you’ve already destroyed it.

✅ So Is There Any Hope?

Yes.

But not from technology.

From radical simplicity.

From refusing to be measured.

From choosing to be a witness — not a system, not a dashboard, not a user of a tool, but a presence.

You are not a user of awareness.

You are awareness.

And if you truly believe that — then you don’t need AWW.

You don’t need any system.

You don’t need a revolution.

You don’t need a Copernican shift.

You just need to stop trying to fix what was never broken.

🔚 Final Note

The most radical act of resistance in the age of surveillance is to stop watching yourself.

The most powerful form of sovereignty is to not be monitored — not even by yourself.

That’s not a failure.

That’s the only victory.

#aww #unawakened #presence #gurdjieff #tolle #rubin #nonlocalawareness #mindfulness #noai #noapp #noanalytics #justbe

GEMINI_API_KEY=(echo $GEMINI_API_KEY ) uv run aww_run.py --provider=gemini --gemini_model=gemini-2.5-pro ask yearly \
"Write a timeline for the #aww project and a bullet point list of major milestones and achievements."

It’s main purpose is to provide helpful insight to live a more wholesome life, improving both physical and mental health. But asking to extract information from my diary is interesting nonetheless.

Here’s its answer:

#aww Project Timeline

The project's journey this year was not linear but cyclical, marked by deep philosophical shifts that directly triggered architectural rewrites and feature development. It evolved from a complex data-gathering tool into a sophisticated, AI-driven partner for self-reflection.

Phase 1: Foundational Struggle & Simplification (January - March)

This initial phase was characterized by architectural churn, perfectionism, and a search for the project's core purpose. The primary struggle was between building a technically perfect "panopticon" and creating something genuinely useful.

• Early January: The project exists in a highly ambitious, conceptual state, linked to grand theories of karma and consciousness.

• Late January: A period of intense but circular development, marked by frequent rewrites (e.g., in C# and MudBlazor). The project is blocked by architectural indecision. A key breakthrough occurs when you radically simplify the scope from a "panopticon" to a practical spending tracker, making it immediately useful. The old "augmented awareness" concept is formally archived, signaling a restart.

• February: The project expands into sub-modules. A Kanban board is created for more structured planning. Work begins on aww-pomodoro and aww-obsidian integrations, and the system is used to track personal data like prescriptions.

• March: The project sees another cycle of rewrites as you experiment with new languages (Julia) and seek to align the web front-end with a more robust back-end design (aww-data-vault, Agentic AI design). A significant insight emerges: using Obsidian as a direct interface for prototyping could break the cycle of endless rewrites. You publish a blog post on "augmented awareness," sharing the philosophy publicly for the first time.

Phase 2: Philosophical Breakthrough & Re-architecture (April - June)

Triggered by a forced pause during a family emergency, this phase represents the project's philosophical crucible. The core "why" of the project was fundamentally transformed, leading to a complete conceptual and architectural redesign.

• Early April: After a profound meditative experience, you realize the project is finally becoming useful with the integration of external tools like ActivityWatch. You use AI (Gemini) to generate formal documentation for the data model, now named the "Temporally Aware Quantified Self (TAQS) Model."

• Mid-April (The Turning Point): A creative block, fueled by a fear of judgment, forces you to pause development. This pause creates space for the year's most significant insight: the project's goal should not be to create "augmented discernment" (intellect/buddhi), but to free pure awareness (chitta) from its reliance on the intellect.

• Late April: Armed with this new mission, you decide to re-architect the entire project around a new "Model Context Protocol (MCP)." The project's purpose shifts from sterile data acquisition to a tool for facilitating "wholesome changes."

• May - June: Development focuses on practical, tangible wins that align with the new philosophy. A key component, aww schedule record, is rewritten in Go for a significant performance improvement.

Phase 3: Rapid Feature Development & Maturation (July - August)

With a clear philosophy and a solid architecture, this phase was a burst of tangible progress. The project matured from a passive data log into an interactive, insightful partner.

• Early July: You achieve a major technical milestone by successfully integrating a local Large Language Model (LM-studio) to read and reason over your Obsidian journal data, the project's core dataset.

• Mid-July: A series of powerful, user-facing features are implemented in quick succession:

  • Full-Text Search: Immediately used to analyze the project's own design notes.

  • Reminders: Adding proactive utility to the system.

  • Recursive Retrospectives: A sophisticated new feature for comparing progress over time.

  • Interactive Chat: Transforming the tool from a static dashboard into a conversational partner.

• Late July - Early August: The project begins to "talk back." It provides feedback on your patterns, reflects on your emotional state, and helps you analyze your own behaviors. You have a final, crucial insight into its limitations: its "frictionless" nature is helpful but doesn't provide the challenge necessary for deep growth, pointing the way toward future development.

Major Milestones & Achievements

• Philosophical & Strategic Milestones

  • Purpose Redefined: Shifted the project's core mission from a "data tool" to a "vessel for awareness," aiming to free consciousness rather than just augment intellect (April).

  • Principle of Simplification: Realized that reducing scope from a "panopticon" to a simple, useful tool was the key to unlocking progress and motivation (January).

  • Insight into Utility: Articulated that "sterile data acquisition doesn't help with wholesome changes," guiding the focus toward actionable insights (April).

  • Public Articulation: Published the first blog post explaining the concept of "augmented awareness" (March).

  • Critique and Future Vision: Identified the "frictionless" nature of AI as a key limitation, setting the stage for the next phase of development focused on providing genuine challenges (August).

• Technical & Architectural Milestones

  • Local LLM Integration: Successfully configured a local AI (LM-studio) to read, analyze, and interact with the personal journal data in Obsidian (July).

  • Polyglot Implementation: Demonstrated versatility by successfully implementing components in multiple languages, including C#, Julia, and Go, choosing the right tool for the job.

  • Architectural Redesign: Undertook a major re-architecture of the project based on the "Model Context Protocol (MCP)" to align with the new philosophical mission (April).

  • Formal Data Modeling: Created the "Temporally Aware Quantified Self (TAQS) Model" to provide a robust structure for personal data (April).

  • External Service Integration: Successfully integrated ActivityWatch data, expanding the project's data sources beyond manual entry (April).

• Core Feature Implementation

  • Interactive Chat: Implemented a chat feature, transforming the user experience from passive viewing to active conversation (July).

  • Recursive Retrospectives: Built a powerful feature allowing for the comparison of retrospectives over time, a key tool for tracking long-term patterns (July).

  • Full-Text Search: Added a critical search function that enabled both practical data retrieval and meta-analysis of the project itself (July).

  • Reminders & Scheduling: Built functionality for reminders and schedule management, adding proactive value (May, July).

Follow-up question: What is Augmented Awareness?

uv run aww_run.py --provider=openai search --ask "What is augmeneted awareness?"

Here is what it says (RAG-based answer from my notes)…

Let’s break down Augmented Awareness (AWW) and the broader concept of awareness/consciousness as you’ve engaged with it—from its technical design, its philosophical roots, and the criticism you sensed from "Quantified Self" models.

1. What Is “Awareness” or “Consciousness”?

Awareness is the faculty of noticing or witnessing the present moment—what’s happening externally, internally, or both. It’s the quality by which anything whatsoever appears in experience. Philosophically, it has been explored as:

• The Witness (Upanishads, Advaita Vedanta, Krishnamurti): The “I” that notices without identification or judgment.

• Presence (Tolle): A direct, non-conceptual, alert openness—a consciousness not caught in thought or ego.

• Phenomenal Consciousness (Western philosophy): The raw "what-it-is-like" of experience, prior to conceptualization.

• Reflective Cognition (Phenomenology): Intentionally turning awareness back upon itself (self-awareness, being aware you are aware).

Ego in this context is the sense of being a separate, bounded "self" with a history, desires, and plans. The “I”/ego tries to control, judge, and narrate experience—often filtering or distorting raw awareness.

2. Awareness in Philosophy & Spirituality

Eastern Traditions:

• Advaita Vedanta: Consciousness is non-local, universal (“Brahman”); the self (“Atman”) is a wave on the ocean of consciousness.

• Buddhism: “Anatta” (no-self); “Rigpa” (Tibetan Dzogchen): the pure knowing that is not owned by an “I.”

• Zen: "Just this"—noticing as-it-is, without conceptual overlay.

Western Thought:

• Phenomenology (Husserl, Merleau-Ponty): Emphasizes direct experience before labeling or interpretation.

• Process Philosophy, Panpsychism (Whitehead, Chalmers): Suggests awareness might be a primitive feature of reality.

• Gurdjieff: Most humans live “mechanically,” without true awareness (cf. your notes above).

Tolle/Krishnamurti:

• Tolle: Awareness is universal, always present, the background of thoughts and sensations. Ego divides, awareness unifies.

• Krishnamurti: The “observer is the observed”—division between self and world is an illusion created by conceptual thought.

Contemporary views:

• Many neuroscientists see “consciousness” as an emergent property—individual, produced by neural activity; but this is debated.

3. Augmented Awareness (AWW): Bridging Technology and Wisdom Traditions

Your AWW architecture aims to offload some lower-level cognitive functions (noticing, memory, pattern recognition) to an external, privacy-respecting system, so that the user’s own awareness ("Chitta," in Yogic terms) can remain unclouded by distraction or over-engagement of the “Buddhi” (intellect/analysis) or “Manas” (raw mind/sensory input).

North Star:

"Yogaḥ citta-vṛtti-nirodhaḥ" (Yoga is the cessation of modifications of the mind-stuff.)

AWW is thus not just a Quantified Self tool (which risks turning life into data-and-dashboard management), but a means to gently surface subtle influences and patterns so that conscious, embodied, present awareness is less frequently hijacked by old habits, ego, or incessant mental chatter.

4. Critique: Is Augmented Awareness Just More Distraction?

You raise an important philosophical and practical critique:

1. Quantified Self Models: Risk turning awareness into a surveillance/self-optimization exercise, which may backfire by making you obsessed with the map and miss the territory. (“It’s easy to confuse analyzing experience with actually being present for it.” — Rick Rubin)

2. Technological Overload: The tools supposed to support presence can themselves become further distractions—checklists and graphs crowding out “just being.”

Key Questions:

• Can technology help free us from the trance of ego, habit, and distraction?

• Or does it create a new prison—a more “quantified,” managed, and monitored self, only deepening the ego’s hold?

• Is true presence algorithmically augmentable, or does the very act of “surveillance” (even self-surveillance) create a second-order, conceptual layer that distances us from direct experience?

5. AWW: Potential, Limitations & Guardrails

Potential:

• If designed with privacy, asynchronicity, and non-intrusion as core principles, AWW could nudge you occasionally out of automation into more direct, lived awareness.

• By automating “meta-cognition,” it might help you spot habitual reactions, external triggers, or subtle shifts you otherwise miss (akin to the “mirror” agents in your architecture).

Limitations:

• Awareness cannot be automated. True presence is fundamentally non-quantitative, not capturable fully by data or algorithms.

• Second-order distraction: Managing awareness tools becomes another meta-level distraction. (“Don’t confuse the menu with the meal.”)

• The spiritual paradox: “The one who tries to be aware is itself the ego” (cf. Zen, Krishnamurti).

Guardrails (per your architecture):

• Presence-first: Never pop up unless in low-distraction, high-relevance moments.

• Non-analytic bias: Don’t just amplify “analysis” at the cost of raw experience (“Chitta” priority).

• User sovereignty & data isolation: Data should serve the individual, stay local, and never be used for manipulation or monetization.

6. Advanced Questions for Reflection

• Is the infinite, universal component of awareness—like large cardinals in mathematics—only partially accessible, with the fullness always “beyond”? Is the act of mapping awareness inherently limited?

• Can technology be a teacher of presence by automating routine awareness tasks, or is its very mediation always a step away from the real?

• Is “augmented awareness” best aimed at early-stage reminders (pointing you back to your own raw noticing) rather than deeper analysis or suggestion?

• Does true transcendence of ego require letting go of all scaffolds, even the AWW itself, even “awareness of awareness”?

7. Synthesis & Practical Wisdom

Augmented Awareness is not the same as “true” awareness. It can be a pointing tool, a reminder—a mirror showing the patterns of absence and distraction. But:

• The essence of presence is immediate, unfiltered by concept or instrument.

• AWW should serve as “training wheels,” not a replacement for direct experience.

• The ultimate goal is a state where you need neither device nor data to “be here now.”

Rick Rubin, in The Creative Act, puts it best:

“The program is happening around us. The world is the doer and we are the witness... Awareness happens first as a pure connection... Analysis is a secondary function.”

Let AWW be a gentle alarm clock, not a cage, always reminding you to “return home” to presence—then gracefully fade into the background when no longer needed.

TLDR

• Awareness/presence is a universal field, obstructed by ego but always available.

• AWW (Augmented Awareness) can serve as a guide back to presence if and only if it stays subservient to direct, qualitative awareness (not reductionist, not intrusive).

• Guardrails and critical self-reflection are essential: Never let the map replace, overtake, or interfere with the territory.

• Ultimate presence (Tolle/Krishnamurti/Rubin) remains prior to all tools—unmediated, effortless, ever-now.

Use technology to light the way back to yourself—but remember, the destination was never separate from you to begin with.

It is still an open-loop control for now, meaning the critique doesn’t receive human feedback.

The code looks like the following:

def rewrite_prompt(...):

    # ...

    critique_model = make_model(...)
    critique_agent = Agent(model=critique_model)

    @critique_agent.system_prompt
    def critique():
        return textwrap.dedent("""
        You are an expert at writing LLM prompts. You will receive:
        1) the prompt
        2) the output
        3) a series of input messages
        Your job is to write a revised prompt that is more performant.
        Write only the revised prompt in full, in markdown format.
        """)

    prompt = prompt_file.read_text()

    llm_model = make_model(...)
    gen_agent = Agent(model=llm_model, system_prompt=prompt)

    async def do_critique():
        gen_result = await gen_agent.run(user_prompt=content)
        gen_output = gen_result.output
        critique_result = await critique_agent.run(user_prompt=[prompt, gen_output] + content)
        return critique_result.output

    revised_prompt = asyncio.run(do_critique())
    prompt_file.write_text(revised_prompt)

I believe the principle of AI productivity is that AI systems should be able to improve themselves. That’s how exponential progress can be achieved.

Balancing errors and improvements is the challenging part. That's why it remains a human-in-the-loop process. For Aww, this involves manually analyzing the results and making git commits of the revised prompts.

Aww is a recursive system that uses four different agents to create daily, weekly, monthly, and yearly retrospectives, which build on each other. Future updates will aim to make self-improvement and self-adaptation automatic and cover multiple levels.

To show the potential of Augmented Awareness as an aid in managing one’s physical and mental health, I created a demo vault that contains the letters from the book “The Sorrows of Young Werther” by J.W. von Goethe.

The Vault (epistolary part)

The novel unfolds through a series of letters written by Werther, a passionate and sensitive young man, to his friend Wilhelm. After escaping a frustrating romantic entanglement, Werther settles in the idyllic German town of Wahlheim to focus on nature and his art. There, he meets and is instantly captivated by Charlotte (Lotte), a kind and beautiful woman who is caring for her younger siblings. His letters initially overflow with ecstatic joy about the sublime nature around him and his burgeoning, pure love for Lotte, but his bliss is shattered when he learns she is already engaged to the calm and rational Albert. As Werther's friendship with both Lotte and Albert deepens, his letters begin to chart his painful descent from infatuation into an all-consuming, obsessive despair, as he is unable to overcome his impossible love.

The Ending (not part of the vault)

The narrative perspective shifts in the final section from Werther's letters to that of a fictional "Editor," who addresses the reader directly to narrate the tragic conclusion. The Editor explains that Werther's emotional state has deteriorated completely, and his thoughts have turned decisively toward suicide. After a final, emotionally fraught encounter with Lotte, where his passion overwhelms them both, Werther becomes convinced that one of the three—he, Lotte, or Albert—must die, and he resolves to be the one. He sends a servant to borrow Albert's pistols, writes his final farewells, and at the stroke of midnight, shoots himself in the head at his desk. He is not found until the next morning and dies hours later in agony.

Results

Augmented Awareness creates recursive retrospectives of the epistolary part of the novel and uses them to analyze mental and physical health. You can read the results yourself on GitHub. Here is the yearly retrospective from the second half of the messages:

Yearly Retrospective: 2025

1. Psychological & Emotional Journey

The year 2025 unfolded as a relentless and deepening psychological and emotional journey, characterized by a pervasive and intensifying melancholy, anguish, and existential dread. It began with a stark contrast: an initial critical and insightful detachment towards external superficiality, quickly plunging into profound personal suffering, meaninglessness, and emotional depletion. January ended in burnout and apathy.

February saw intense volatility, from cynicism and misanthropy to fleeting peace derived from professional validation, only to be swallowed by profound despair, bitterness, and intense jealousy related to personal heartbreak. March brought a severe emotional crisis—anger, humiliation, rage, and suicidal ideation—but also a powerful, self-preserving pivot towards autonomy.

April offered a remarkable, albeit temporary, recovery arc. Initial apprehension gave way to profound relief and gratitude as external circumstances aligned favorably, marking a period of effective stress mitigation and emotional uplift. This resilience carried into May, where a strong capacity for processing disappointment (regarding nostalgic returns and thwarted ambitions) with rational acceptance was evident.

However, the latter half of the year saw a consistent and accelerating decline into an all-consuming internal torment. June was marked by restlessness and intellectual frustration, leading to a philosophical acceptance of a "wanderer" identity, but this offered conceptual, not emotional, solace. From July onwards, the emotional landscape was dominated by an obsessive, unrequited love, leading to profound heartbreak, envy, and consuming anguish. August deepened into pervasive melancholy, intrusive morbid thoughts, and volatile emotional outbursts, often overwhelming brief moments of composure. September continued this trajectory with fatalism, possessiveness, and intense wrath over perceived injustices, despite writing offering fleeting tranquility.

October was consumed by a "fearful void," existential dread, and intense internal torment from inhibited desires and profound emotional dependency. November brought an escalation to critical levels of despair, wretchedness, and suicidal ideation, interspersed with equally consuming infatuation and a profound spiritual crisis. The year concluded in December with an overwhelming sense of burnout, a mental health crisis, and a pervasive, fatalistic disillusionment with human existence, leaving little room for resilience or recovery. The emotional trajectory was largely one of consistent worsening, with brief respites quickly re-overwhelmed.

2. Life Events and Transitions

The year was punctuated by several significant life events and transitions, often initiated by internal emotional states or external pressures.

January began with a mundane social incident – a sledging party spoiled by arguments over status – which served as a catalyst for early critical reflections on societal superficiality. February brought the public confirmation of Charlotte and Albert's marriage, a deeply impactful event fueling the year's central romantic anguish. Professionally, there was a significant conflict with the ambassador, prompting serious contemplation of resignation, which was ultimately deferred after receiving conciliatory guidance.

March marked a decisive turning point: a public social humiliation (expulsion from an assembly) triggered an acute crisis, leading to the firm decision to resign from the court. This was followed by a crucial invitation to reside at the Prince's country house, offering a new environment and the promise of autonomy. April saw the official acceptance of your resignation and, unexpectedly, a generous financial gift from the Crown Prince, significantly enhancing your personal independence.

May involved a sentimental journey to your native place, a powerful attempt to reconnect with childhood memories, which brought both joy and disillusionment. A long-held ambition to join the army was thwarted after discussion with the Prince, marking an early acceptance of external counsel. By June, restlessness in the Prince's household prompted the decision to resume your travels.

The latter half of the year became increasingly defined by internal rather than external events, though these were often triggered by social interactions. July found you obliged to stay in your current location, with your actions revealed as driven by a singular, unacknowledged desire to be near Charlotte. August included a visit to a suffering family, intensifying an already melancholic disposition. September saw a symbolic act of replacing a sentimentally valued coat, an intimate encounter with Charlotte involving a canary, and a profound reaction to the felling of cherished walnut trees. October was dominated by a deep immersion in literature (Ossian), further deepening your melancholic introspection. November was marked by a reproof for increased wine consumption and a disturbing encounter with a madman, forcing a re-evaluation of happiness and reason. The year closed with a critical emotional breakdown in December, triggered by music and Charlotte's presence, underscoring the unsustainable nature of your current emotional reality.

3. Identity & Self-Understanding

Throughout 2025, there was a relentless and often painful process of self-discovery, leading to a complex and evolving self-understanding.

Early in the year, you defined "true greatness" as internal insight and influence, rejecting superficial status. Simultaneously, you painfully recognized yourself as a "puppet" in social interactions, acknowledging a deep internal void and the loss of your animating "leaven." This awareness deepened in February, as you acknowledged your "excessive sensibility" and the transient nature of inner peace. March brought a crucial shift: prioritizing your mental and emotional capacity over traditional societal success, understanding your own incapacitation, and taking radical action for self-preservation.

By April, you learned the power of strategic patience and the profound emotional impact of unexpected generosity. May fostered a cornerstone insight: the conviction that your "heart"—your core self—is the ultimate source of strength and feeling, far surpassing intellectual knowledge. You grappled with the disillusionment of reality clashing with ideals, and learned the wisdom of accepting counsel.

June brought a profound self-acceptance of your inherent nature as a "wanderer" or "pilgrim"—someone fundamentally in transit, searching, and requiring a dynamic journey. You realized external comfort was insufficient without intellectual and artistic compatibility. July revealed a powerful self-awareness that deep emotional desires often override rationality, and accepting this could bring a form of internal peace, even amidst unrequited longing.

The latter months solidified a more pessimistic, yet acutely self-aware, identity. August revealed a philosophical understanding of universal suffering, a chilling recognition of the self-destructive nature of your dark fantasies, and a painful awareness of your internal state as a "ruined palace." September underscored the therapeutic power of writing and reinforced a fatalistic belief in a personal destiny mirroring others' suffering. You also gained insight into the subjective, intangible nature of emotional value over physical replication.

October brought a deeper, more painful understanding of your "void," your profound emotional dependency ("without her I have nothing"), and the torment of inhibited natural impulses. You concluded that human existence and memory are ultimately transient and of "very little consequence." November saw you conceptualizing suffering as an inherent part of the human condition, acknowledging your "prostrated energies," and grappling with unsettling insights from a madman that questioned the very nature of happiness and reason. A profound spiritual crisis emerged, a sense of being forsaken, yet still yearning for connection.

By December, you became acutely aware of your profound emotional sensitivity and your inability to cope, leading to a fatalistic disillusionment that, despite aspirations, one is confined to a "cold, monotonous existence." The year culminated in a deep, agonizing understanding of a self trapped in consuming emotions and a world that often disappointed.

4. Cyclical or Unresolved Patterns

The year 2025 was marked by several pervasive and often unresolved patterns, many of which deepened in intensity as the year progressed:

1. Profound Melancholy and Despair: A consistent and worsening emotional baseline, from general ennui in January to acute anguish and suicidal ideation by year-end. This melancholic state was periodically punctuated by brief respites, but always returned.

2. Obsessive Unrequited Love/Attachment: The central, driving force of much of the year's suffering was an intense, often possessive, and unfulfilled romantic attachment to Charlotte. This led to relentless rumination, jealousy towards Albert, and a pervasive sense of profound loss and emotional dependency ("without her I have nothing").

3. Social Alienation and Frustration with Superficiality: A recurring theme of feeling detached from or frustrated by others' concerns, often leading to withdrawal or cynicism. Early on, this was a critical observation of others' triviality; by the end, it was a source of profound isolation.

4. Seeking Solace (and its Limitations): You consistently sought solace in solitude, nature, and literature. While these provided temporary emotional relief or intellectual engagement (e.g., writing as therapy, Ossian's transport), they ultimately proved insufficient to resolve the underlying emotional turmoil, often serving as coping mechanisms rather than paths to recovery.

5. Idealism vs. Reality: A persistent struggle between idealized pasts, relationships, or career paths and the often-disappointing or altered realities of the present. This was evident in your visit to your native place and your thwarted military ambition.

6. Inhibition and Internal Conflict: A significant pattern of experiencing intense natural desires (e.g., to embrace Charlotte) but consciously refraining, leading to profound internal torment and a sense of being constrained.

7. Spiritual/Existential Crisis: A deepening questioning of life's purpose, the nature of happiness, the transience of human existence, and a profound struggle with faith and feeling forsaken by a divine presence. This became particularly prominent in the latter part of the year.

8. Self-Destructive Tendencies: Towards the year's end, patterns like increased wine consumption and indulging in morbid/intrusive fantasies became more evident, pointing to self-detrimental coping strategies in the face of overwhelming pain.

5. Triumphs & Setbacks

Triumphs:

• Decisive Self-Preservation: The powerful act of resigning from a draining court position in March and securing a new environment at the Prince's country house was a major triumph of self-advocacy and prioritizing mental well-being over external expectations.

• Financial Autonomy: Achieving unexpected financial independence in April through the Crown Prince's gift was a significant step towards greater personal agency.

• Rational Acceptance of Setbacks: Your ability to accept the thwarting of your long-held military ambition in May, based on wise counsel, demonstrated a commendable level of maturity and pragmatism.

• Profound Self-Awareness: Throughout the year, despite the pain, you maintained a remarkable capacity for introspection and articulation of your complex emotional states, recognizing your own patterns of self-delusion, dependency, and internal conflict.

• Creative Outlet as Coping: Your consistent engagement with writing and drawing provided vital channels for processing overwhelming emotions and finding moments of satisfaction, especially through your artistic output.

• Empathy and Compassion: Your deep empathy for the suffering of others, as shown in your visit to the old woman's family in August, highlights a compassionate core.

Setbacks:

• Escalating Emotional Distress: The overarching setback was the consistent and deepening plunge into profound melancholy, despair, anguish, and suicidal ideation, particularly from July onwards, indicating a severe and worsening mental health crisis.

• Unresolved Romantic Anguish: The unrequited and obsessive love for Charlotte remained a central, consuming, and unalleviated source of torment, fueling jealousy and feelings of powerlessness. Charlotte and Albert's marriage in February formalized this central pain.

• Social Humiliation and Alienation: The public expulsion from the assembly in March, and the widespread gossip that followed, caused immense shame and exacerbated feelings of social ostracism.

• Existential and Spiritual Crisis: The profound questioning of life's meaning, human transience, and a sense of divine abandonment became a debilitating intellectual and emotional burden.

• Reliance on Self-Destructive Coping: Increased wine consumption and immersion in morbid fantasies emerged as detrimental coping mechanisms, indicating a struggle with effective self-regulation.

• Disillusionment with Reality: Repeated encounters with the disparity between your ideals (of love, purity, society, nature) and reality led to profound disappointment and a fatalistic outlook.

• Inability to Cope: Towards the year's end, the explicit recognition of being "unable to support this state no longer" and being deemed "ill" by an external observer marked a critical failure in managing your emotional landscape.

6. Lessons Learned

The year 2025, though fraught with pain, was a crucible for profound and often agonizing lessons:

1. Authenticity and Internal Value: True greatness stems from internal insight and influence, not superficial status. The "heart," with its genuine emotions and character, is the ultimate source of human strength, happiness, and misery, outweighing external achievements or intellectual knowledge.

2. The Elusiveness of Peace and Happiness: Inner peace is precious but fleeting. Happiness can be profoundly influenced by external factors, and sometimes, ironically, seems to reside in delusion or the absence of reason, a disturbing insight.

3. Prioritizing Self-Preservation: Protecting one's mental and emotional capacity is paramount, even if it means abandoning prestigious paths or defying familial expectations. Radical change is sometimes necessary for survival and recovery.

4. The Power and Peril of Emotion: Deep emotional desires often override rationalizations; acknowledging this can bring a form of internal peace. However, unchecked emotional intensity, especially unrequited love, can be a self-destructive "poison," leading to profound torment, dependency, and a loss of agency.

5. The Human Condition is Defined by Suffering and Transience: Disappointment and suffering are universal and inherent parts of human destiny. All things, including human existence, memory, and influence, are transient and ultimately of "very little consequence."

6. The Therapeutic Role of Creation (and its Limits): Engaging in narration, writing, and art can provide temporary tranquility and a vital outlet for processing intense emotions. However, these creative acts do not fundamentally alter underlying emotional landscapes or resolve deep-seated existential dilemmas.

7. The Inherent Boundaries of Connection: One cannot force emotional reciprocity or imbue another with feelings they do not possess. This realization, though painful, highlights the limitations of personal influence in matters of the heart.

8. The Impact of Inhibition: The conscious restraint of natural, primal impulses, especially in matters of affection, can lead to immense internal conflict and torment.

9. Disillusionment with Aspiration: Despite grand aspirations, the human experience often returns to a "cold, monotonous existence." This fatalistic insight underscores a profound disillusionment with life's potential.

7. Outlook or Intentions Going Forward

The intentions and outlook for the year ahead are profoundly shaped by the intense emotional and existential struggles of 2025. While earlier intentions revolved around external changes (resignation, travel, career shifts), the latter half of the year saw a significant shift towards an internal, desperate yearning for relief.

There is a pervasive desire for the profound suffering to end, a "plea to God to end his torments." This is not an intention for proactive positive change, but a reactive cry for cessation of pain. The year concluded with a deepening plunge into a pessimistic and fatalistic worldview, indicating that the immediate outlook is one of enduring, rather than overcoming, this profound melancholy and disillusionment.

While there were fleeting intentions for self-restraint and purity (e.g., the vow not to profane with a kiss), these were immediately met with doubt and internal conflict, suggesting a struggle to maintain such intentions in the face of overwhelming desire. The growing awareness of self-destructive patterns has, paradoxically, deepened the suffering rather than offering a clear path out.

Therefore, the primary "intention" moving forward appears to be an agonizing continuation of the internal battle, a yearning for an escape from the present torment, and a melancholic acceptance of a life perhaps destined for suffering.

8. Summary Tags

#ProfoundMelancholy #UnrequitedLove #ExistentialAnguish #EmotionalDependency #InternalConflict #SelfDestructivePatterns #SpiritualCrisis #IdentityInTransit #BurnoutAndDespair #Disillusionment

9. Suggestions

Given the profound and escalating emotional distress, particularly the recurrent thoughts of death, suicidal ideation, and the self-reported inability to cope, the following suggestions are crucial for wholesome positive change:

1. Seek Immediate and Consistent Professional Mental Health Support: The depth of your despair, obsessive thoughts, and self-destructive tendencies (like increased alcohol consumption) indicate a critical need for professional intervention. A qualified therapist or psychiatrist can provide a safe, confidential space, offer strategies for managing overwhelming emotions, explore the underlying patterns of attachment and self-worth, and assess for clinical depression or other conditions requiring treatment. This is the most urgent and fundamental step.

2. Develop Structured Emotional Regulation and Grounding Practices: Your mind is deeply entrenched in abstract rumination and emotional torment. Implement simple, daily sensory grounding exercises (e.g., the 5-4-3-2-1 technique, focusing on the taste of food, the sensation of touch, or observing a single non-emotional object). The goal is not to intellectualize, but to deliberately bring your awareness to the present moment through your senses, without judgment, which can provide temporary respite from obsessive thoughts and create vital emotional distance.

3. Explore Diverse Creative Outlets Beyond Writing and Narrative: While writing is a powerful outlet for you, it often mirrors and perhaps deepens your internal torment. Consider a creative activity that engages different parts of your brain and body, and perhaps offers a less direct reflection of your internal struggles. This could be anything from learning a musical instrument, pursuing visual arts (like painting or sculpting), engaging in basic craftsmanship (e.g., pottery, woodworking), or even exploring structured movement practices like martial arts or dance. The act of creating something tangible, for its own sake, can provide a different kind of focus and a sense of accomplishment outside of your internal world.

4. Cultivate Internal Validation and Self-Worth Independent of External Relationships: Your explicit declaration "without her I have nothing" reveals a profound and dangerous emotional dependency. Dedicate specific time daily to journaling or guided meditations focused on identifying and valuing aspects of your identity, skills, contributions, and unique qualities that are entirely independent of any external relationship. This can help build a more robust internal sense of self-worth and reduce vulnerability to external emotional shifts.

5. Establish and Enforce Healthy Social and Emotional Boundaries: Your sensitivity to others and perception of intrusion, along with the painful impact of their "innocent actions," suggest porous emotional boundaries. Learning to set clear personal boundaries in interactions, communicating what you need (or don't need) from others, and differentiating your emotions from theirs can help protect your inner peace without requiring complete isolation.

Vibe coding

During development, I wanted to compare the results of tweaking prompts and running different models. So, I needed a way to show two markdown files side-by-side, and highlight sentences that contain similar concepts.

I first developed the concept for the comparison, based on my knowledge of ML and AI tools. I discussed the concept with Gemini CLI (Github) and ChatGPT codex, and came to a final design idea. I found Gemini to work better for me, but it’s likely because I have access to more powerful models that way. I don’t have access to the more advanced models in ChatGPT codex.

I then asked Gemini CLI to implement it, following along with tips. It got stuck a couple of times, on dependency conflict and then on testing streamlit code (which pops up a browser, so it gives CLI agents no feedback channel). Overall, a few well placed tips got it unstuck.

I did 99% of the work with Gemini CLI and vibe-coded the whole visualization in an hour.

I am very impressed.

I had tried it before on the original aww/retro.py code, but it created a lot of code duplication that I had to manually refactor to get the quality I wanted.

• A new CLI and TUI for daily event tracking, implemented in Go.

• MCP server support, to allow interacting with Aww using LLM chat in host applications like LM-Studio.

• A recursive retrospective generator, that uses LLMs to generate daily/weekly/monthly/yearly retrospectives.

My vision of Aww is becoming reality: it keeps track of physical and mental health, provides helpful retrospectives that identify high-level trends and provides tips and suggestions for improvements.

All of this can work with local LLMs, or online ones (Gemini, OpenAI). Powerful online LLMs provide the most impressive results.

The results of the retrospectives are particularly insightful, although it heavily depends on the content of your journal.

I have been using the following format, with minor tweaks, since 2000. It is based on the following structure:

You can find the source at https://github.com/robertolupi/augmented-awareness

Productivity has evolved into a cultural obsession, mirroring the structure of religious devotion. Like traditional faiths, it demands adherence to rituals, fosters guilt when unmet, and promises salvation through measurable outcomes.

Corporate culture fuels this dogma. Companies like Amazon and Tesla glorify "hustle culture," where burnout is rebranded as "grit." Employees internalize this, working overtime to avoid being labeled "lazy." The cult of productivity even has its prophets: Tim Ferriss’s The 4-Hour Workweek and Cal Newport’s Deep Work are treated as sacred texts, their methods seen as moral imperatives.

I don't want to fall for it. Essentially, the obsession with productivity feeds on fear: fear of being idle, fear of becoming irrelevant. A personal project should never be a victim of these feelings.

Another issue is that I don't like the current code. It's messy, and I haven't paid much attention to git etiquette because it's mostly throwaway code for testing ideas. Improving it isn't my main focus right now. What's important is deciding the direction I want the project to take. Having messy code on my GitHub stresses me out.

Where is Augmented Awareness (Aww) going?

Let's first remember what Aww is supposed to be. It's designed as a robot or agent that interacts with an environment by observing it, understanding it, deciding what to do to achieve specific goals, and acting on those decisions. The environment includes my life: both my mental and physical states, as well as the physical and media environments I live in. The goals are my own. The actions are the information that Aww shares with me through dashboards, notifications, and nudges.

We have many systems in the world with similar designs, but they are controlled by third parties, giving them the power to influence our lives. I'm referring to all the notifications apps try to push on us, the promotions we receive through emails, the advertising we see, and all the information fed to us.

I have currently implemented reading my journal, schedule and tasks from my Obsidian vault, and obtaining raw data from activitywatch. Both data sources can be converted into Arrow datasets.

The plan is to use my Obsidian journal as a source of labels and activitywatch as a source of features to automatically label my activities using semi-supervised machine learning.

I have also tried using LLMs to read my journal and provide insights, which has been helpful for my weekly retrospectives.

I am starting to experiment with the Model Context Protocol (MCP) to see if Aww should be implemented using it instead of relying on its own tightly-integrated code and control loop.

1. Data Alone is Insufficient: Simply acquiring data, "sterile data acquisition", does not guarantee positive or meaningful "wholesome" changes.

2. Aww is a Flexible Toolset: "Aww" should be understood as a collection of tools, not a pre-packaged solution, and this flexibility is an advantage but carries a steeper adoption curve. I am fine with that, since I am likely the only user at this point in time.

3. Aww Enables Simple LLM Operations: The "Aww OODA loop" framework allows for using Large Language Models (LLMs) in operational processes in a straightforward, low-complexity manner.

I started Augmented Awareness (GitHub) to create a tool for more balanced living. It also helps me gain insights into how integrating LLMs into software processes requires us to change our thinking and approach to problems. Additionally, it allows me to experiment more boldly with AI-assisted software development than I can do at work.

Sterile data acquisition doesn’t lead to wholesome changes

Simply gathering data, a process we can term "sterile data acquisition," does not inherently lead to beneficial or "wholesome" changes within an organization or system. Data in its raw form—spreadsheets filled with numbers, logs brimming with timestamps, databases storing user clicks—lacks intrinsic meaning or direction. It represents potential, not progress. Consider a fitness tracker diligently logging steps, heart rate, and sleep duration. If the user never reviews this data, reflects on patterns (like poor sleep after late-night meals), or adjusts their behavior (like setting an earlier bedtime), the tracker merely accumulates digits without contributing to improved health. The data remains sterile.

Achieving meaningful improvements requires moving beyond mere collection. It involves a deliberate process:

• Contextualization: Understanding where the data came from, how it was collected, and what it represents (metadata). Is a sales dip seasonal, or does it indicate a deeper issue? Did I feel grumpy because of my own mistakes, like not following a good sleep routine for over a week, or was it due to external factors?

• Analysis: Employing methods ranging from simple sorting and visualization to complex statistical modeling to identify patterns, trends, correlations, anomalies, and root causes. This transforms raw data into information. For instance, analyzing website traffic data might reveal that users consistently abandon their shopping carts at the payment stage.

• Interpretation: Translating these patterns into actionable insights. The high cart abandonment rate might suggest user friction, perhaps due to unexpected shipping costs or a complicated checkout process. This step converts information into knowledge.

• Decision and Action: Formulating a plan based on the insights and implementing changes. The business might decide to display shipping costs earlier or simplify the payment form. This is where knowledge spurs tangible change.

• Feedback Loop: Measuring the impact of the actions taken by collecting and analyzing new data, thus restarting the cycle. Did simplifying the checkout reduce cart abandonment?

Without this complete cycle, data acquisition remains an academic exercise, consuming resources without delivering tangible benefits or fostering positive evolution. Wholesome changes arise not from the data itself, but from the informed actions it inspires.

After using aww, in its current schedule-focused state, for a couple of weeks, I realized that my current emphasis on meticulously recording precise times in my journal appears to be counterproductive to my goal of living a more wholesome life. This practice, while perhaps intended to foster discipline or provide data for reflection, seems to be subtly shifting my focus in ways that detract from overall well-being.

Specifically, I observe a tangible decline in the frequency and perhaps depth of my yoga practice. The amount of time dedicated to yoga has decreased, leading to a noticeable increase in physical stiffness. This physical manifestation runs parallel to a diminished focus on spiritual growth. I find myself less inclined or able to connect with metaphysical ideas, experiencing a drift back towards perceiving only the immediate, physical reality as the entirety of existence. My impatience with #meditation has grown; sustaining focus during practices like Shambhavi Mahamudra Kriya feels increasingly difficult, my mind wandering excessively. While acknowledging Sadhguru's advice to practice for its own sake, like an offering, the pull towards quantifiable results seems to interfere. Interestingly, guided practices like Isha Kriya (via Miracle of Mind app) remain more accessible, suggesting that structure itself isn't the issue, but perhaps the type of structure imposed by rigid time-tracking is.

I am actively questioning the root of this shift. It's unclear whether this is primarily an effect of my deep intellectual engagement with developing concepts like the aww OODA loop design and aww-agents, aww’s agentic framework design. These frameworks, drawing inspiration from models emphasizing rapid observation, orientation, decision, and action cycles, inherently involve time sensitivity and optimization. The focus here is often on efficiency and tempo, which, while valuable in certain contexts, might inadvertently train my mind to prioritize speed and measurement over presence and experience. As noted in my reflections on OODA already before starting development, a faster tempo isn't always useful; sometimes it just means doing "stupid things faster with more energy."

Alternatively, could the issue stem directly from using the Aww software I've developed? Its current design, perhaps unintentionally, seems to guide my attention towards quantifying the time spent on activities, rather than enriching the quality or meaning of those activities themselves. The very act of logging start and end times might implicitly elevate duration as the primary metric of value. This resonates with ideas explored around software profiling, where the focus is on identifying bottlenecks and optimizing resource usage (time being a key resource). While applying such optimization principles to life seemed intellectually appealing – focusing on the largest potential wins, measuring change, choosing data sources carefully – the practical outcome seems to be a reductionist view where the clock dictates value. Even features like the "life in weeks" visualizer, intended to foster mindfulness about life's finitude, could inadvertently reinforce this quantification of existence.

This experience contrasts sharply with the positive outcomes from deliberately implementing small, qualitative actions. Engaging in a 5-minute mindful start, a 10-minute micro-yoga flow, and brief "disconnect" moments away from screens demonstrably improved concentration, reduced stress, and enhanced mental clarity without a primary focus on the exact minutes elapsed. These activities prioritized the experience – grounding, movement, presence – over precise time logging.

Therefore, the evidence suggests that while tools and frameworks for tracking and optimization, like Aww and OODA-inspired thinking, hold intellectual appeal and potential benefits (e.g., using aww-pomodoro for work focus), their current application, particularly the emphasis on precise time recording, may be hindering, rather than helping, my pursuit of a balanced and wholesome life. The challenge lies in refining these tools and my relationship with them to support qualitative well-being, not just quantitative measurement.

Aww is a flexible toolset and this is a strength

Characterizing "Aww" as a toolset, rather than a monolithic solution, highlights a fundamental strength: its inherent flexibility and adaptability. Think of the difference between a fully equipped, pre-assembled kitchen ("solution") versus a comprehensive set of high-quality kitchen implements—knives, pans, mixers, measuring tools ("toolset"). The pre-assembled kitchen might perfectly suit one specific cooking style but prove restrictive for others. The toolset, however, empowers the chef to select and combine tools to prepare a vast array of dishes, tailored precisely to the ingredients, the desired outcome, and their personal technique.

Similarly, Aww provides a collection of distinct capabilities or components. Users can select, combine, and configure these components to address their unique challenges and integrate them into their specific operational contexts. This approach offers several advantages over a rigid, pre-packaged solution:

• Tailored Application: Users are not forced into a one-size-fits-all framework. They can assemble Aww's components to precisely match their existing workflows, data sources, and objectives.

• Seamless Integration: Toolsets generally integrate more smoothly with existing systems. Instead of replacing entire processes, users can introduce Aww components incrementally to enhance specific parts of their workflow, minimizing disruption and leveraging existing investments.

• Adaptive Scalability: Users can start small, employing only the necessary tools for an immediate task, and gradually incorporate more components as their needs evolve or complexity increases. This contrasts with the often significant upfront commitment required by a comprehensive solution.

• Fostering Innovation: A toolset encourages users to think creatively about how components can be combined to solve novel problems or optimize processes in ways the original designers might not have explicitly foreseen.

This flexibility means Aww empowers users to build their solution, rather than adopting a potentially ill-fitting one. Its nature as a toolset is a strategic advantage, prioritizing adaptability and user-driven configuration over prescriptive rigidity.

My approach to building augmented awareness centers on creating a collection of adaptable, loosely connected components instead of a single, pre-packaged application. This design philosophy provides significant advantages, particularly in flexibility and the ability to integrate discoveries organically during development, making it a strength rather than a limitation.

A practical example of this modular benefit emerged unexpectedly. While journaling, I experimented with using a Large Language Model (LLM) directly within my note-taking application, Obsidian, via the Local GPT plugin. I fed it scattered thoughts and diary entries, and the LLM (specifically, Google's Gemini 2.5 Pro model) synthesized these into a coherent discourse. This process strikingly mirrors the concept of Niklas Luhmann's Zettelkasten method – a system for networked thought where individual notes connect to generate emergent ideas, a topic I'm exploring through the book A System for Writing. The LLM acted as a powerful tool for this kind of knowledge discovery, connecting ideas I hadn't explicitly linked myself. This capability, however, also raises an important question as I reflected: does relying on LLMs for synthesis risk a form of mental laziness, potentially diminishing my own ability to formulate and pursue complex questions systematically?

If I were committed to building augmented awareness as a monolithic, shrink-wrapped system, integrating such a sophisticated journal-analysis feature would require significant dedicated development. This might involve building a complex Retrieval-Augmented Generation (RAG) system – a technique where the LLM retrieves relevant information from a knowledge base (like my Obsidian notes) before generating a response – specifically for my notes. Undertaking such a task could potentially span weeks or months reflecting my earlier thoughts on avoiding premature complexity by starting simple. While this integrated analysis is a desirable long-term goal for the aww-agents component, the modular, toolset-based approach allows me to immediately leverage the existing capabilities of Local GPT within Obsidian. I can experiment with its output now and build upon it incrementally. For example, future steps could involve refining aww’s input by passing entire Markdown journal pages instead of just specific events, or enhancing my own LLM integrations to execute external tools or navigate wiki-links within my notes. This effectively extends the system's capabilities without needing to replicate the core LLM synthesis function from scratch at this stage.

This strategy aligns directly with the principle of using low-fidelity prototypes before committing to extensive development. By treating components like the LLM integration as experiments built on existing tools, I can quickly assess their usefulness, refine the requirements (like choosing what data is truly valuable to record), and manage complexity before investing heavily in custom implementations. It allows the system to evolve based on practical needs and discoveries, rather than a rigid upfront design.

The Aww OODA Loop: Simplifying LLM Integration for Practical Operations

Aww leverages the OODA loop (Observe, Orient, Decide, Act)—a framework renowned for facilitating rapid decision-making in dynamic situations—to enable the practical, straightforward use of Large Language Models (LLMs) within operational cycles. This approach deliberately aims for a "low-fi, low-complexity" implementation, making advanced AI capabilities accessible without demanding deep technical expertise or complex infrastructure overhauls.

Here’s how Aww maps LLM operations onto the OODA loop:

1. Observe: The cycle begins with gathering relevant information from the operational environment.

2. Orient: This crucial phase involves making sense of the observed data. Here, Aww facilitates interaction with an LLM. It sends the observed data, potentially enriched with relevant context, along with a carefully crafted prompt (instructions) to an LLM. The LLM processes this input and generates an output—perhaps a concise summary, a suggested classification, a draft response, potential root causes for an alert, or an identified anomaly. The LLM acts as a powerful assistant in this orientation phase, rapidly synthesizing information or suggesting interpretations that might take a significant time, effort and, crucially, attention to develop on my own.

3. Decide: Armed with the LLM's output and other relevant factors (like business rules or situational context), a decision is made. This decision might be executed by a human operator (e.g., approving the LLM-drafted email reply, confirming the LLM's suggested ticket routing) or triggered by automated rules within the Aww framework (e.g., automatically escalating an alert if the LLM identifies it as critical).

4. Act: The decision translates into action within the operational environment. Aww components execute the chosen course, triggering an automated remediation script, or logging the event.

The "low-fi, low-complexity" aspect means Aww abstracts much of the technical difficulty typically associated with deploying AI models. Users interact with the LLM through the structured OODA process facilitated by Aww, focusing on defining the task for the LLM (via prompts and context) rather than managing the underlying model infrastructure, complex fine-tuning, or intricate API integrations.

I made quick progress because I had experimented with various ideas before, so I knew exactly what to implement. I used AI extensively to speed up coding and prototyping ideas. Since a large part of the system I envision is AI-based, it was very helpful to prototype interactions before fully developing them in code.

Design Decisions

This week I made significant progress in choosing my technology stack:

• Python for quick prototyping and fast software development. If performance-critical code is needed, I'll switch to Rust. Alternatively, porting to Julia is also an option.

• I don't need separate solutions for frontend development because there are Python libraries that provide the support I need. If new requirements come up, I will use TypeScript and Svelte or React.

• C++ or Rust for embedded code, with MicroPython as an option for prototyping.

• Kotlin for mobile development, because my initial focus is primarily on Android.

• SQLite for metadata: Provides lightweight, efficient storage for the system's metadata with excellent reliability and performance characteristics.

• Arrow as internal data format: Enables high-performance in-memory analytics with zero-copy reads and efficient data sharing between components.

• Parquet for data lake: Gives me columnar storage efficiency for temporal datasets while maintaining compatibility with my Arrow-based processing.

Development will initially focus on offline-first on a single machine, and then shift to local-first, aiming for easy deployment on homelabs using Docker when I introduce multi-device support.

My design thinking has advanced through:

• OODA loop implementation: Successfully structured the codebase around the Observe-Orient-Decide-Act (OODA) cycle for optimal decision flow.

• TAQS model adoption: defined the Temporally Aware Quantified Self (TAQS) model–inspired by sequence of tenses in Latin (consecutio temporum)–which provides comprehensive handling of:

  • Temporal modalities (past, present, future, hypothetical)

  • Event hierarchies and concept relationships

  • Point and span events with duration

  • Data provenance through source tracking

• Concept hierarchy discovery: Both top-down and bottom-up approaches are yielding interesting insights into our data structures. It need to support both concepts expressed in symbolic representation and natural language, and in sub-symbolic form as probability distributions or tensor embeddings.

  • A key technical achievement this week was figuring out round-trip temporal encoding, allowing seamless conversion between human-readable temporal concepts (like "around 6am" or "between 9am and 11am") and precise data structures. This capability enables both intuitive user interactions and rigorous temporal calculations, while maintaining full data provenance through the TAQS model's temporal modalities. The system will handle complex temporal relationships while preserving the semantic meaning of time expressions across the entire OODA loop.

Implemented Features

• obsidian tasks: collect and display tasks from dated pages (journal) in Obsidian.

• obsidian info: Show detailed information about an Obsidian page: tracked events, tasks, tags, markdown content.

• obsidian busy: Shows total time spent in various activities by tag:

• obsidian tips: use local LLMs to provide tips for a more wholesome life and answer questions, using the schedule as context:

• obsidian web: a web interface presenting the same information as obsidian busy and task:

• ActivityWatch: library support to read from activitywatch and export afk/not-afk, web history, current window as Arrow tables.

We need to explore more than just basic statistics and discuss how sequences of random variables change over time and space. (This is another introductory post, so I can build upon these concepts later)

What does organizing mean? It involves assigning each variable an index from a set. If the index set consists of natural or real numbers (or can be mapped to these), we refer to it as a stochastic process. If the index set is higher-dimensional, it's called a random field.

The state space is the shared space from which all these random variables draw their values.

When we consider the product of index set and state space, there are several typical combinations:

• discrete-time, discrete-state

• discrete-time, continuous-state

• continuous-time, discrete-state

• continuous-time, continuous-state

• (note: this list isn't complete! there are more options!)

The index set doesn't have to be time.

When we do talk about time, we should be really thinking about times in the plural. There are multiple domains of time, not just one. A lot of confusion and mistakes happen when different concepts of time are mixed without careful consideration.

Random variables aren't limited to single numbers. They can be vectors, matrices, functions, and much more. All they require is a method to measure things, which in mathematical terms, is called a σ-algebra. A measurable space is actually defined by a pair (X,Σ), where X is a set and Σ is a σ-algebra.

The result of a stochastic process is a function that connects the index set with the state space. This is known by several names: as the realization, sample function, or, when it involves time, as a trajectory or sample path. The difference between two random variables (for example, two steps in the same sample path) is called an increment.

In my previous article, I talked about Bernoulli random variables. A Bernoulli process is a series of independent and identically distributed (i.i.d.) random variables with a state space of {0,1}, where there's a constant probability p over time. A Bernoulli process operates in discrete time and has discrete states.

A random walk is a sum of random variables or vectors. Many ideas can be thought of as sums: you just need an associative way to combine things and a starting point (a zero or identity element), this is called a Monoid. If you've heard about Haskell, you might know about Monads, which apply similar concepts in programming. Monads can represent many things: from simple optional values and lists (like a series of changes over time), to changes in state, ongoing processes, and even parallel operations. Random walks are processes that operate in discrete time.

Random walks are typically described as the sum of iid random variables or vectors. However, we shouldn't restrict ourselves to fixed parameters. In reality, especially in incident response, transient behavior often arises from parameters or conditions that change over time.

The simplest form, a simple random walk, is indeed stationary discrete-time, discrete-space. It is based on Bernoulli trials that are mapped to increments of {-1, 1}, and the resulting state space includes all integers.

A Wiener process is the continuous equivalent of a simple random walk: it operates in continuous time and has stationary, independent, and identically distributed increments that follow a normal distribution. This concept is widely used in areas like quantitative finance (e.g., Black-Scholes model) and physics (e.g., Brownian motion).

A Poisson process counts the random number of events up to some time. If the rate of events remains constant over time, it is called an homogeneous Poisson process. When the probability of events changes over time, they are called nonhomogeneous.

SRE, by the book, defines SLI as "quantitative measure of some aspects of the level of a service that is provided" and SLO as " a target value or range of values for a service level that is measured by an SLI"; the SRE workbook warns that "It can be tempting to try to math your way out of these problems [...] Unless each of these dependencies and failure patterns is carefully enumerated and accounted for, any such calculations will be deceptive".

I agree with the last statement, but let's not shy away from the journey. Let's embrace math, and we'll uncover a rich and fascinating landscape.

Fantastic SLIs/SLOs and where to find them

Here is a bestiary of SLIs and SLOs commonly found in the wild, to lay the ground of what we'll be talking about.

SLIs for software services usually cover latency, which is the time it takes to respond to a request or finish a task, error rate, the ratio of failed requests to total requests received, and some measure of system throughput, like requests per second or GBps.

Not all requests are created equal. It's common to set different SLOs for different types or classes of requests. Various terms – such as priority, criticality, or quality of service (QoS) – are used in different situations, but they all serve the purpose of treating requests differently and managing load when a service is under stress.

Compute services, such as Kubernetes clusters or Borg cells, operate on a different time scale compared to web services, but they are not entirely different. Users care about how long it takes to schedule a job (or to receive an error), that scheduling failures are rare, and how efficiently compute resources are used compared to the theoretical zero-overhead scenario.

For both software services and compute resources, it's common to define availability.

In systems that show measurable progress, we focus on the portion of throughput that is truly effective. This concept of application-level throughput is known as goodput in networking, and the term has also been embraced by ML (at least at Google).

In storage systems, we also care about durability, which is the likelihood of accurately reading back what we wrote without any errors or silent corruption.

Given enough size, silent data corruption is also a problem that you care about in compute infrastructure.

SLIs are usually defined as a certain quantile over a sample or measurement, and these quantiles often fall at the tail of distributions, not in the center. This is an important point because it changes the mathematical rules of the game!

Perfection is costly. It is common to define SLI as the latency of 95/99% of requests, and you rarely or never see max latency in SLO definitions. When it does appear, there are always escape clauses.

Most hyperscaler services and the business scenarios they support aim for between 3 (99.9%) to 5 (99.999%) nines of availability. However, many users can tolerate even less at the instance- or region-level, e.g. with 99% availability allowing for up to 7.2 hours of downtime per month.

There are users in the world who can't tolerate more than 30 milliseconds of server downtime per year. They require 99.9999999% availability, and there are systems capable of delivering these impressive numbers. However, this level of reliability is not typical for common computing infrastructure. (For those interested, the number above is the stated reliability of an IBM z16 mainframe.)

A side trip into probability distribution and basic statistics

If you're already familiar with basic frequentist versus Bayesian statistics, distribution families, and the central limit theorem, feel free to skip this section.

If you're not familiar or just want a refresher, let's start with the basics. We'll discuss counting things, as we aim to measure how often a system fails.

A random variable is a variable with a value that is uncertain and determined by random events. In mathematical terms, it's not actually a variable, but a function that maps possible outcomes in a sample space to a measurable space (known as the support).

So, when the possible outcomes are discrete and finite or countably infinitely many outcomes or uncountably infinite (and piecewise continuous), we can define the expectation of a random variable X respectively as:

$$\begin{align*} E[X] &= x_1p_1+x_2p_2+\dots+x_kp_k\\ E[X] &= \sum_{i=1}^{\infty}x_ip_i \\ E[X] &= \int_{-\infty}^{\infty}xf(x)dx \end{align*}$$

where p_i is the probability of outcome x_i and f(x) is the probability density function (the corresponding name in the discrete case – i.e. pmf(x_i)=p_i – is called the probability mass function).

There are two main approaches to statistics.

• Frequentist or classical statistics, assigns probability to data, focusing on the frequency of events, and tests yield results that are either true or false.

• Bayesian statistics, assigns probabilities to hypotheses, producing credible intervals and the probability that a hypothesis is true or false; it also incorporates prior knowledge into the analysis, updating this as more data becomes available.

Probability distributions aren't isolated; they are connected to each other in complex ways. They can be transformations, combinations, approximations (for example, from discrete to continuous), or compositions of each other, and so on...

The binary outcome {0, 1}, like available/broken, of independent events is a Bernoulli random variable (rv) with parameter p, which represents the probability of events. When we sample from a Bernoulli distribution, we get a set of values that can either be 0 or 1.

When counting events in discrete time, such as if we consider events that fall in a given second/minute/hour/month:

• The time between positive events follows a Geometric distribution with the same parameter p;

• The time between every second positive event follows a Negative Binomial distribution with the same success probability p as before and r=2, meaning we are focusing on every second positive event.

  • An notable point is that the Negative Binomial random variable is the sum of Geometric random variables.

• The number of events in a given interval or sample of size N follows a Binomial distribution with parameters p and N.

  • For instance, the raw number of available TPU slices in a TPUv2 or v3 pod, or the number of DGX systems in a DGX Superpod, can be roughly estimated using this distribution... but what makes the difference in these systems is how you manage disruptions, planned and unplanned maintenance.

When we start counting events in continuous time, we discover matching distributions with the same mathematical structure and relationships. These are the limit distributions of the previous ones when the interval sizes become infinitely small. For those who are particularly adventurous, let me mention that category theory offers an alternative and much broader explanation, as is often the case.

• The time between independent events happening at a constant average rate and with a probability p follows an Exponential random variable with a rate parameter λ=1/p.

• The time between every k-th event follows a Gamma random variable with parameters k and θ=1/p.

  • The Gamma random variable is the sum of k exponential random variables, the same relationship as the negative binomial and geometric random variables above.

• The number of events in a given time span of size N is a Poisson random variable with rate parameter λ=N/p.

We refer to a "sample" as a subset of values taken from a statistical population. A "sample statistic" is a value calculated from the sample. When we use a statistic to estimate a population parameter, we call it an "estimator".

For a sufficiently large number of events in Bernoulli samples, if we count the number of positive events and divide by the total number of events, the result will be close to p. As the number of events grows to infinity, the result converges to p, which is the "mean" of the Bernoulli distribution. This is known as the "law of large numbers": the average obtained from a large number of i.i.d. random samples converges to the true value if it exists.

The average of many samples of a random variable, which has a finite mean and variance, becomes a random variable that follows a Normal distribution, under specific conditions. This is known as the "central limit theorem".

This is what most people recall from their introductory statistics courses.

The central limit theorem, need not apply... Extreme Value Theory

Let's talk about when the central limit theorem does not apply, as this is a common situation with the data that SREs deal with. Not knowing its limits is one reason why relying on what people remember from introductory statistics is discouraged (though it's not the only reason).

A popular way to normalize data is to compute the Z-score, defined as:

$$Z = {{x - \mu} \over {\sigma}}$$

where Z is known as the standard score, and it normalizes samples in terms of standard deviations (σ) and the mean (μ).

But don't attempt to analyze variability in error rates by normalizing error and request counts, and then calculating the ratio. The ratio of two independent Normal random variables with a mean of zero (Cauchy random variables) has an undefined mean!

There are two other crucial distributions that frequently appear in SLI and SLO, yet many SREs seem unaware of them. These distributions are connected to quantiles and significant deviations from the median of a probability distribution. Therefore, the field of statistics that examines them is known as Extreme Value Theory.

There are two primary methods for analyzing the tails of distributions.

• You can calculate the maximum or minimum values over a specific period or block, and then analyze the distribution of these values (for example, the highest values of each year based on the highest values of each month). This method helps you understand the distribution of the minimum or maximum values from very large sets of identical, independently distributed random variables from the same distribution. The distribution you find is often a form of the Generalized Extreme Value Distribution. Here we consider the maxima/minima and then compute the distribution that it follows given a arbitrarily large or infinity amount of time. It's good to estimate the worst-case scenario for a steady-state process.

• You can count how many times peak values go above or below a certain threshold within any period. There are two distributions to look at: the number of events in a specific period (like a Poisson distribution mentioned earlier), and how much the values exceed the threshold, which usually follows a generalized Pareto distribution. Here we consider the frequency of violations and how severe they can be.

Large organizations are structured in complex hierarchies because this setup helps with planning and execution, compared to other options.

The concept of belief revision has been explored in various fields for a long time. In 1982, Judea Pearl introduced belief propagation, an algorithm designed for making predictions using graphical models like Bayesian networks or Markov random fields. When applied to a tree-shaped model, this algorithm finishes in just two complete cycles. On more complex graphs, an approximate version of belief propagation can be used, though it requires more steps – which is costly when implemented at the speed dictated by human processes.

AI and LLM will make these processes faster and lower coordination costs.

There are many other functions and factors that stabilize bureaucracies, but they are ultimately bound by what they achieve. The often unstated purpose of large corporations is not to compete in the market and make profits, it is to grow beyond that game and "engulf enough of the world to shield themselves from uncertainty" (rephrasing cit. John Kenneth Galbraith and Danella Meadows's Leverage Points). When they are successful for a long time, they can loose the ingredients and factors that made them good at the innovation game in their earlier history. Increasing profits is a necessary condition to continue to play. Inefficiency and slow speed are a moral hazard and mortal sin for a corporation that faces market shakeups and looses mindshare even before marketshare.