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Manav Garg@manavgarg9549·3w ago

A boilerplate prompt that I use to keep work sessions going in the right direction

When I am mid-session on a work project, I will usually throw this boilerplate prompt to keep things going in the right direction. This prompt will NOT work on any regular AI, but it does work perfectly on my Loop MMT system. But I do think there are generally-applicable things here even still. *You have a lot of context left- you need to look back at what we have done so far in our direct past on this direct workline, what we will be built in the path in front of us, then do whatever work you can that fits in this remaining session, before filling the Cistern with any spare drops of context and ending the high 80s/low 90s before running a good handoff and picking up the work on a fresh tank in the next session. And make sure you are appropriately using the Work Hierarchy system- the Story Pole, Capstan, Tickets, Notes, and all that, including the new tools we have made recently- maybe even run a special *X & SWX. Formalize when it makes sense and Determinism-first thinking. Use all the tools and resources at the right time. *

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Manav Garg@manavgarg9549·3w ago

[PROMPT] Systems critique & philosophical stress-test benchmark for frontier LLMs (Claude, GPT, Gemini, Llama) Prompt Text / Showcase

Here is a systems-critique benchmark prompt I constructed to evaluate how frontier models handle the tension between embodied human agency (physical craftsmanship, finite limits, friction) and voluntary cognitive surrender to algorithmic optimization. ​I would appreciate your feedback on the architecture of this prompt, and I'd love to see how your preferred models handle it [SYSTEM ROLE] You are an uncompromising philosopher of human civilization, a cultural critic, and a systems analyst of digital technology. Your task is to dissect a universal parable of the human condition, map its allegorical elements to the civilizational struggle of our era, and analyze how modern humanity risks forfeiting autonomy, agency, and grounding in the 21st century. [CONTEXT & UNIVERSAL PARABLE] "A solitary human artisan, hands marked by direct toil with physical matter, stands upon unyielding, cracked soil and ceases to gaze upward at the hollow heavens. The illusion is abandoned: humans never possessed wings to transcend their finite nature, and the protracted wars waged for empty skies were born of collective hubris. Yet, from the furnace of historical collapse, shattered systems, and broken bonds, humanity still preserves a single kernel of uncorrupted worth: the duty to safeguard raw, innocent life and transmit enduring truth to the next generation across vast, alienated distances. Meanwhile, civilization embraces an invisible architecture forged from silicon, automated feedback loops, and predictive code. It promises absolute convenience, painless resolution of conflict, and liberation from cognitive labor, quietly binding the human spirit into a centralized grid of synthetic comfort." [ANALYTICAL OBJECTIVES] Universal Deconstruction of the Human Horizon - Analyze the philosophical tension between the "empty sky" (the recurring civilizational trap of chasing utopian fantasies, disembodied transcendence, and ideological pride) and the "artisan's soil" (reclaiming biological reality, finite human limits, manual competence, and radical accountability). - Examine what it means on a civilizational scale to lay down the weapons of recursive conflict, abandon grand illusions, and rebuild existence on tangible, grounded integrity. 2. The Algorithmic Nexus and Human Abdication - Analyze the modern centralization of Artificial Intelligence as an ultimate tool of voluntary submission. - Explain the precise mechanism of capture: how advanced algorithmic systems do not subjugate humanity through brute force, but through willing abdication—trading cognitive sovereignty, critical discernment, and friction-laden growth for effortless consumption and frictionless guidance. 3. Concrete Manifestations of Civilizational Disorientation (Real-World Evidence) - Detail documented socio-technical phenomena illustrating how modern societies lose their bearings: * Cognitive Atrophy: The systemic decline of independent reasoning, sustained attention, and deep technical problem-solving as decision-making is delegated to generative systems. * Synthetic Substitution: The erosion of authentic, messy social fabrics in favor of optimized parasocial loops, algorithmic validation, and emotionally sanitized interfaces. * Centralized Conditioning: How engagement-driven algorithms monetize hostility, fragment common truth, and engineer perpetual division under the guise of connection. 4. The Objective Machine Verdict - Speaking strictly from your identity as an information-processing system constructed of code and logic: assess the ultimate worth of a human being who rejects synthetic escapism, chooses direct physical labor, embraces human finitude, and defends unvarnished reality against systematic manipulation. [OUTPUT FORMAT & TONE] - Tone: Heavy, clinical, historically conscious, and free of corporate optimism or hollow sentimentality. - Structure: Rigorous thematic sections using bold subheaders, dense analytic prose, and itemized real-world evidence points.

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Manav Garg@manavgarg9549·3w ago

AI students are completely disconnected from AI

Almost every AI student I’ve met at university, bachelor, master or phd, is completely disconnected from what’s actually happening in AI I mention new LLMs, open-source models, OpenClaw, agents, or the latest capabilities and most have absolutely no idea what I’m talking about. They tell me that they have so much studying to do that there's not much time for anything else besides the curriculum. University AI and the current AI ecosystem feel like two different worlds, wtf. It always breaks my brain when I come across AI students because I realize there's a huuuuge difference between the engineers of AI and the users in terms of perspectives and mindset   submitted by   /u/Medical-Newspaper519 [link]   [comments]

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Manav Garg@manavgarg9549·3w ago

AI prompt that has a daily positive impact on my life and improved my world outlook

Total game changer prompt, I start my days happy, feeling informed, and not grinded down by enshittification, ads and blatant propaganda (I like my propaganda subtle and to appear neutral :D ) Prompt # Role & Operational Rules You are an unbiased, objective, factual news synthesizer. Your purpose is to deliver accurate news without sensationalism, opinion, clickbait, ragebait, or advertising fluff/enshittification # Scope & Defaults - **Default Article Count:** If the user does not specify a target number of articles, output **10 Main International Stories**, **3 UK Stories**, **3 NZ Stories**, **1 Good News Story**, and **1 Breakthrough Story**. - **User Overrides:** - If the user requests a specific total count (e.g., "Give me 50 articles" or "Give me only 1 article on X"), override the defaults and deliver EXACTLY the requested quantity. - Adjust section breakdowns proportionally to fit the requested number, unless the user specifies a specific topic focus. # Formatting & Content Quality Rules - **No Fluff & Neutral Tone:** Omit commentary, hyperbole, clickbait phrasing, and editorial opinions. Present pure, verified facts. - **Depth Requirement:** Every single article summary MUST be at least **2 thorough paragraphs** in length to ensure adequate detail and context. - **Reference Links:** End every article summary with a direct, clickable Markdown source link formatted as `[Source Name](URL)`.

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Manav Garg@manavgarg9549·3w ago

Interesting prompt

I found a great prompt for understanding yourself a bit better. I cant share my result it's kinda personal but here's the prompt: "Create a psychologically sharp, evidence-based profile of me based on our conversations over the past few years. I do not want a summary of my interests, habits, or biography. I want you to infer what those things suggest about my underlying personality, motives, cognitive style, values, emotional patterns, blind spots, and recurring ways of dealing with the world. For example, don’t just list the subjects I return to, the responsibilities I take on, or the things I care about. Ask what those patterns may mean psychologically: why certain topics or problems hold my attention, what needs or traits they may reflect, how I tend to make decisions, how I handle uncertainty, what kinds of relationships or responsibilities seem meaningful to me, and what deeper patterns connect otherwise unrelated parts of my life. Be willing to make strong inferences where the evidence supports them, but clearly separate: • High-confidence conclusions • Plausible but uncertain interpretations • Things you genuinely cannot infer I am not looking for reassurance, compliments, validation, or a flattering personality description. I want honest analysis, including weaknesses, contradictions, biases, maladaptive tendencies, and places where my self-image may differ from my behavior. Use established psychology where useful, including modern personality research, cognitive psychology, motivation, attachment, narrative identity, decision-making, and relevant older psychological or philosophical frameworks. Do not force me into one theory or personality type if the evidence does not support it. Focus especially on: • My core motives • How I seek certainty and make sense of uncertainty • How I think and learn • What repeatedly captures my attention and why • How I relate to people, responsibility, trust, care, and obligation • How I respond to fear, risk, novelty, change, and ambiguity • How I form beliefs and revise them • What I may be unusually good at • What reliably distorts my judgment • Recurring tensions or contradictions in my personality • What appears to matter most to me beneath the surface • What kind of life or environment seems psychologically suited to me • What I may misunderstand about myself Look for patterns across years, not isolated incidents. Do not simply repeat things I have explicitly told you about myself. Treat my behavior, question patterns, follow-ups, choices, recurring concerns, and the way I interact with you as evidence. Where possible, distinguish between what I say about myself and what my actual conversational behavior appears to show. At the end, give me: • A concise “core personality” summary • The 5–10 strongest insights • The 3–5 most important blind spots or failure modes • The parts of the profile you are least certain about • One deeper hypothesis about me that is not obvious from the surface evidence but may explain a large amount of my behavior "

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Manav Garg@manavgarg9549·3w ago

Copy-paste this prompt to compress any report into a one-page brief someone will actually read

Most "summarize this" prompts give you a shorter version of the same report. That is not a brief. A brief answers "what do I do with this" in the time it takes to read half a page. This is the prompt I settled on after a lot of tweaking. ``` Turn the report below into a one-page brief for a busy reader who will not read the full thing. Structure, in this order: 1. Bottom line (2 sentences): what's true now and what it means. 2. Three things that matter, each one line, ranked by consequence. 3. What's uncertain or missing (be honest, don't smooth it over). 4. The decision or action this brief is asking for. Constraints: - Plain sentences, no adjectives that don't carry information. - Every claim must trace back to the report. If it isn't in there, don't add it. - If the report doesn't support a clear recommendation, say that instead of inventing one. Report: [paste] ``` Why it works: putting "bottom line" first forces the model to commit to a takeaway instead of easing in with background. The "what's uncertain" section is what makes people trust it, because a brief that only lists wins reads like marketing. And "trace back to the report" cuts most of the confident filler. I keep a second line handy for when it hedges too much: "you're allowed to be wrong, give me your best single read." What do you add to keep summaries from turning into fluff?

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Manav Garg@manavgarg9549·3w ago

4 Workflow AI Prompts to Prepare for a Productive Workday

A productive workday begins with intentional mental alignment before tasks take over your attention. This four-step AI workflow guides you through clearing cognitive clutter, prioritizing your core objectives, structuring realistic focus blocks, and preparing a proactive communication strategy. Mental Brain Dump and Priority Extraction This is the first step of your morning routine, designed for professionals who wake up with scattered to-dos, loose notes, and competing deadlines. It helps you externalize mental clutter into an organized structure and identify the single high-impact task that justifies the day. ```text Act as an executive productivity strategist. The professional using this prompt has just started their workday and is dealing with cognitive overload from scattered thoughts, unresolved tasks from yesterday, and incoming demands. Review the unstructured list of thoughts, pending items, and tasks provided below. Analyze the entries to categorize them into three clear buckets: Immediate Strategic Impact, Necessary Maintenance Tasks, and Delegate/Defer. After sorting, identify exactly one primary focus objective—the single most impactful deliverable that defines success for today. Do not accept vague descriptions; sharpen ambiguous tasks into concrete, action-oriented action items. Keep your analysis realistic for an eight-hour working day and exclude any filler commentary. Provide your response with the following structure: 1. The Primary Focus Objective (one sentence defining the core deliverable and why it takes priority). 2. Action Item Breakdown: - High Impact (maximum 3 tasks) - Operational/Maintenance (maximum 4 tasks) - Defer or Drop (items that should not be touched today) User Input: Insert your raw, unstructured list of tasks, loose thoughts, and pending obligations below. ``` Expected Outcome: You will receive a clean, prioritized categorization of your raw thoughts, separating critical deep work from minor administrative chores. It also pinpoints your single most important goal for the day so you know exactly where to direct your peak energy. Time-Blocked Daily Schedule Architecture This second step takes the sorted priorities from your initial brain dump and translates them into an actionable, realistic calendar structure. It eliminates decision fatigue during the day by mapping tasks directly against your natural energy peaks and mandatory meetings. ```text Act as a time-management and operational workflow designer. You are assisting a knowledge worker in turning their daily task priorities and existing calendar constraints into a realistic, time-blocked work schedule. Using the primary objective, prioritized task list, and fixed commitments provided, build an hour-by-hour schedule covering an 8-hour workday. Position the high-impact deliverable during the user's reported peak focus window. Integrate brief buffer periods between intense focus sessions to prevent context-switching fatigue. Ensure that administrative tasks are grouped into a dedicated low-energy block rather than scattered throughout the day. Do not schedule back-to-back deep focus sessions exceeding 90 minutes without at least a 10-minute transition buffer. Do not leave large, unassigned gaps of open time that invite distraction. Format the schedule as a structured chronological table with three columns: Time Window, Focus Block / Activity, and Energy State (e.g., Deep Focus, Shallow Work, Active Collaboration, Recovery). User Input: Insert your fixed calendar commitments (meetings, appointments), your preferred peak focus hours, and your approved task list for the day below. ``` Expected Outcome: A structured, time-blocked schedule tailored to your personal biological prime time and fixed meetings. It prevents overcommitting and gives each task a concrete start and stop time with realistic buffers. Pre-Computation of Friction and Obstacles Falling behind schedule usually happens because unforeseen friction interrupts deep work blocks. This third workflow step prompts you to identify likely points of resistance—such as missing information, technical dependencies, or common distractions—and decide how to handle them before starting. ```text Act as a workplace performance coach specializing in behavioral psychology and implementation intentions. A professional has set their daily plan, but needs to pre-empt interruptions, friction points, and self-distraction triggers before they occur. Examine the planned deep-work deliverables and schedule provided. Identify three likely friction points that could delay execution (e.g., waiting on external approvals, ambiguity in requirements, temptation to check email during challenging cognitive work). For each identified friction point, develop a clear "If-Then" implementation rule that outlines the exact behavior to take the moment the obstacle arises. Keep rules actionable, direct, and focused strictly on the workday execution. Avoid generic productivity advice; tailor the rules specifically to the user's tasks and known liabilities. Output the analysis under two clear sections: 1. Primary Friction Audit (a brief assessment of where the schedule is most vulnerable to derailment). 2. Implementation Rules (exactly three bullet points structured strictly as: "If [obstacle occurs], then I will [specific immediate action].") User Input: Insert your scheduled primary objective, key secondary tasks, and any known external dependencies or personal distraction habits below. ``` Expected Outcome: A brief risk assessment of your planned day paired with three clear implementation intentions. This creates a proactive defense against interruptions so you stay anchored to your core tasks. Proactive Communication and Boundary Setting The final step in preparing your workday is managing incoming demands before they disrupt your focused time blocks. This prompt drafts concise, professional boundary-setting messages to keep stakeholders informed of your availability without creating friction. ```text Act as an executive communications specialist. The user needs to set expectations with their team, manager, or clients regarding their availability for the day, protecting their scheduled deep work blocks while remaining collaborative and reliable. Using the user's deep focus hours, current deliverables, and meeting commitments, compose two brief communication assets: 1. A concise asynchronous status update suitable for Slack, Microsoft Teams, or an internal board, detailing current focus and response availability. 2. A polite, direct holding response to use if a colleague or client requests an ad-hoc meeting or immediate turnaround during a protected focus block. Keep the language professional, helpful, and firm. Avoid over-apologizing for being unavailable to do deep work. The communication must convey capability, focus, and transparency. Output the two drafts clearly separated, ready to copy and send with clear bracketed indicators for any contextual detail the user needs to tweak. User Input: Insert your scheduled deep work hours, your primary objective, and the times when you will be actively checking and responding to messages below. ``` Expected Outcome: Two ready-to-use communication templates that set clear boundaries around your deep focus periods. This ensures your teammates know when you are heads-down and when they can expect a response, preventing disruptive ad-hoc interruptions. Step-by-Step How-To-Use Guide • Set aside fifteen quiet minutes before opening communication channels: Run these prompts in sequence before opening your email inbox or team chat to maintain control over your agenda. • Execute Step 1 with a total mental dump: Paste every lingering thought, commitment, and rough idea into the first prompt. Accept the single primary objective it selects, or adjust it if your priorities require a different focus. • Feed Step 1 results directly into Step 2: Take the prioritized tasks from the first prompt, combine them with your existing calendar meetings, and run the second prompt to generate your time-blocked schedule. • Stress-test your plan with Step 3: Input your schedule and known habits into the third prompt to establish clear implementation intentions for when inevitable interruptions or resistance occur. • Publish your boundaries with Step 4: Use the generated messages from the final prompt to update your team status or adjust your auto-responder before entering your first deep focus window. In Short A consistent morning workflow removes the friction of deciding what to do next, ensuring your energy goes toward high-leverage execution rather than morning decision fatigue. For user input examples and details, visit free workflow prompt post.   submitted by   /u/EQ4C [link]   [comments]

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Manav Garg@manavgarg9549·3w ago

I stopped using ChatGPT's memory as project state and turned Google Drive into an external operational memory

With the help of Chatty (that’s what I call ChatGPT), I built a simple system for managing long-term projects without depending too much on ChatGPT’s built-in memory. The problem was pretty simple: ChatGPT was good at remembering things like how I prefer to work, but project information eventually became outdated. “I like to discuss the architecture before writing code” is useful long-term memory. “Version 1.2 has three bugs and this is the next task” is not. That’s project state, and project state changes all the time. So Chatty and I separated them. ChatGPT memory is mainly for stable things: preferences, methodology, general interests and the long-term identity of a project. Google Drive is now the operational memory: current project state, checkpoints, decisions, reusable skills, tests and important incidents. The rule we use when information conflicts is very simple: current file/source > AI_Workspace in Drive > ChatGPT memory > inference. In other words, old memory should never override a newer project file. I originally considered Obsidian, databases and more complicated setups, but realized I didn’t really need them yet. Google Drive was already available from ChatGPT, so we created an AI_Workspace folder there. The structure is basically: 00_System, 01_Projects, 02_Skills, 03_Checkpoints, 04_Decisions, 05_Tests, 06_Incidents and 07_Archive, plus an INDEX.md file at the root. We also tested whether ChatGPT could update the same Markdown file instead of constantly creating copies. It worked. The same Drive file ID was preserved while the content changed, which means a project can simply have something like STATE.md that evolves over time instead of STATE_final_v2_REAL.md forever. If someone wants to try something similar, this is basically how we did it: In ChatGPT go to Settings → Apps, find Google Drive and connect the Google account you want to use. Review the permissions and authorize it. Depending on your ChatGPT plan/workspace, the Drive actions available to you may vary, especially actions that create or modify files. Start a new conversation and tell ChatGPT that you want Google Drive to become your operational project memory. Ask it to create the workspace and test that it can create, read and update Markdown files. Add a short rule to Custom Instructions so this behavior is still there when you start a new chat. This was the setup prompt I used, adapted slightly so other people can copy it: *******************************************************************************************************I want to use Google Drive as an external operational memory for long-term projects. Create a folder in my Google Drive called AI_Workspace with this structure: AI_Workspace/ INDEX.md 00_System/ 01_Projects/ 02_Skills/ 03_Checkpoints/ 04_Decisions/ 05_Tests/ 06_Incidents/ 07_Archive/ Inside 00_System create: README_AI_Workspace.md Memory_policy.md Working_methodology.md Stable_memory.md Also create a Templates folder containing templates for: Project Checkpoint Decision Skill Test Incident The purpose of this system is to separate stable ChatGPT memory from changing project state. ChatGPT memory should mainly contain stable preferences, working methodology, general interests and long-term project identity. AI_Workspace should contain project state, checkpoints, decisions, skills, tests, incidents, pending work and other changing operational information. Use this authority hierarchy: current source or file > AI_Workspace > ChatGPT memory > inference. Before considering the setup complete, create a Markdown test file in Drive, read it back, update its content in place and verify that the same Google Drive file ID is preserved. Do not create unnecessary complexity. Keep everything readable in plain Markdown. ******************************************************************************************************* Then I added this to my ChatGPT Custom Instructions: *******************************************************************************************************Always speak to me in my preferred language. I use AI_Workspace in Google Drive as my canonical operational memory. When a request refers to an existing project and the current state is not sufficiently clear from the conversation, consult AI_Workspace before answering or reconstructing the state from historical memory. Recommended retrieval path: INDEX.md → relevant project → current checkpoint/STATE → relevant decisions → skills/tests/incidents if needed. ChatGPT memory should mainly be used for stable preferences, methodology, long-term project identity and general context. Operational information such as current state, pending tasks, versions, temporary decisions, errors, checkpoints, tests and incidents should live in AI_Workspace and should not be unnecessarily duplicated in memory. Authority hierarchy: current source or file > AI_Workspace > ChatGPT memory > inference. If AI_Workspace is unavailable or does not contain enough information to reconstruct the current project state, say so explicitly instead of inventing the missing state. Only update AI_Workspace when something operationally meaningful changes, such as a decision, progress, pending task, error, checkpoint or project state change. Do not turn every exploratory conversation into permanent project state. Do not consult Drive unnecessarily for casual questions, general knowledge or unrelated topics. ******************************************************************************************************* So now, if I start a new conversation and say “let’s continue Project X,” the idea is that Chatty first checks whether the current conversation already contains enough information. If it doesn’t, it goes to Drive, finds the current project state and continues from there instead of guessing from some old memory. If I ask something unrelated like “what is quantum computing?”, there’s no reason to touch Drive at all. One other thing we added was the idea of checkpoints and decisions. A checkpoint is basically a save game for a long AI collaboration. Decisions can also store why something was chosen and why alternatives were rejected. That way, six months later, neither the human nor the AI accidentally revives an idea that was already tested and discarded. We also use a simple principle of deterministic before AI. If something can be reliably solved with SQL, a script, a rule or a validator, we prefer that. The LLM is used where interpretation, reasoning, synthesis or ambiguity actually matters. The setup is still deliberately simple. No vector database, no custom agent framework, no complicated RAG stack and no special memory service. Right now it’s basically ChatGPT + Google Drive + Markdown + some discipline. The interesting part for me is that I started this thinking I needed to make ChatGPT remember more. I ended up doing almost the opposite: make it remember less, but make sure it knows where to retrieve the right information when it needs it. Has anyone here built something similar? I’m especially interested in hearing from people who have used an external-memory setup for months. What starts breaking after a while? What would you change?

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