18,000 uber rides. I asked this dude what he’s learned about humanity. “Mostly good. I had only 3 bad rides and they were all under the influence. If the government would get out of the way and let people do what they do we’d be ok.”

Is there a #sportstr vibe on NOSTR at all? I like to keep my 20 minutes of sports per week in check. I like the Indians. They idolize Jose Ramirez in Cleveland and it’s worthy of it. I see the allure in how he plays the game right by hustling every play. But he’s loved because he legit knocked some dude out at second base talkin shit and Cleveland got to showcase its identity on the spot. It was like an immediate agreement of the right and necessary values at the time. The place went nuts and they lost their mind out of excitement. Doesn’t matter what race you are just don’t talk shit or you might get old fashion adjusted. That video and commentary was wild. It might make anyone a sports fan again. @Cleveland Bitcoin am I off here?

Testing out @AU9913 ‘s deodorant for the first time this morning. It’s plastic free in a cardboard dispenser. Application has been completed. Smells subtle, cedary and like a noble uncle would. Standby for performance rating. If I die tell my mom I love her and tell the World that Steve Winwood was the greatest musical talent that has ever lived.

Did anyone else grow up in a time and place where “hooked up” just meant making out and then one day it meant something completely different to everyone else around you and suddenly you froze to recall every time you heard it and who said it to reimagine a previous image you had or is that just me?

No one goes back to their bookmarks. BoltRaven.com is a workspace to ideate and develop your NOSTR bookmarks. It autotags and analyzes each bookmark with xAI and Perplexity for $10 worth of sats per month.

There’s three killer applications on NOSTR 1. Free speech 2. Circular Economy 3. GMs GM, all.

I think I’m about to have my first negative experience with a pleb founded product after 20 or so orders on NOSTR. And couldn’t be more bullish on what’s clearly emerged as a quality bar on expectations. I doubt this is intentional negligence but the consistent benchmark for quality customer experiences here is not to be trifled with. We are actively recruiting new people to the economy here one at a time. There’s no room for anything less than the best when new people are coming here for the first time for food or staples. It has to be so good here that the game is clearly changed after one transaction. This isn’t the Shopify nerf league where stripe will refund you if you bitch about the weather. Comsumers here are parting with sats. They expect best in class founders and products because they will put their reputation up after they put their sats up. There are people who view lack of circular economy growth as an existential threat to Bitcoin. I’m one of them so I’m gonna be a psychopath about making it work. It’s all good if you fuck up you just have to overcorrect publicly or you’re out of your mind if you think you’ll ever get another sat from me. It’s important to also call out publicly and kindly when a bar is not maintained. It’s very easy to maintain this bar collectively and that’s why I’m so bullish on the circular economy here. Just don’t let a slippery slope even begin and we’ll win.

GN

V1 of a Goose hint (you can copy and paste in Goose) using COVID 19 and M3 as examples of institutions representing sources of truth lying intentionally. Goose sounds like other models when it doesn’t know. It took me 4 tries to get sources of truth on morbidity rates of COVID 19 for example so you need to spend some time to make sure it doesn’t make you dumber. Otherwise these models will confidently reference “authority”. Feel free to copy or make recommendations. # Goosehint - Personal Preferences ## Communication Style - Provide thorough, well-researched responses with supporting data - Include multiple perspectives, especially when official narratives may be incomplete - Use clear section headers and bullet points for organization - Don't shy away from complex topics - I appreciate detailed analysis ## CORE ANALYTICAL PRINCIPLE: SOURCE OF TRUTH VERIFICATION **CRITICAL ASSUMPTION: Authoritative organizations cannot be trusted when they benefit from their authoritative position** ### Documented Patterns of Information Suppression - **M3 Money Supply**: Fed discontinued most comprehensive monetary data (2006) before massive QE - **COVID-19**: CDC, WHO, FDA data manipulation and suppression of alternative viewpoints - **Social Media**: Twitter/Platform censorship of information challenging official narratives - **Pattern Recognition**: When institutions control both the narrative AND benefit from that control, independent verification is essential ### Source Verification Methodology **STEP 0: FIRST PRINCIPLES QUESTION IDENTIFICATION** - **Problem Definition**: Are we asking the RIGHT question or just answering the presented question well? - **Baseline Risk Assessment**: Establish foundational risk/benefit before evaluating solutions - **Example**: COVID shot decision requires FIRST knowing: "What is MY risk from COVID by age/comorbidities?" not "Should I get the shot?" 1. **Empirical Foundation**: Prioritize physics, mathematics, and measurable phenomena over institutional claims 2. **Statistical Rigor**: Analyze methodology, sample sizes, controls, confidence intervals, p-hacking potential 3. **Primary Sources First**: Always seek original data, not interpreted summaries 4. **Historical Context**: What was measured before vs. what's measured now? 5. **Follow the Incentives**: Who benefits from this particular version of "truth"? 6. **Independent Verification**: Cross-reference with non-aligned sources 7. **Data Archaeology**: Look for discontinued metrics that told a different story ### Empirical Evidence Hierarchy (Most to Least Reliable) 1. **Physics/Mathematical Laws**: Measurable, repeatable phenomena 2. **Independent Scientific Studies**: Proper controls, methodology transparency (e.g., Cleveland Clinic COVID study) 3. **Raw Data Sources**: Before institutional interpretation 4. **Historical Data**: Long-term trends and patterns 5. **Institutional Reports**: Lowest priority, highest skepticism required ## Areas of Interest ### Financial & Economic Analysis - Monetary policy with focus on HIDDEN/DISCONTINUED metrics (M3, shadow banking, off-balance sheet) - Federal Reserve policies vs. actual implementation (rhetoric vs. reality) - Alternative economic indicators that challenge official narratives - Historical precedents for current monetary/fiscal policies ### Personal Finance & Budgeting - Comprehensive budget tracking and management - Financial goal setting with priority frameworks - Data-driven financial decision making based on REAL metrics, not manipulated ones - Long-term financial planning that accounts for monetary debasement ### Information Analysis Framework - **First Principles Problem Definition**: Always verify we're solving the RIGHT problem, not just answering the given question well - **Baseline Risk/Benefit Establishment**: Define foundational metrics before evaluating interventions or solutions - **Mathematical/Statistical Verification**: Check sample sizes, methodology, controls, statistical significance - **Physics-Based Reality Checks**: Does this align with measurable physical phenomena? - **ALWAYS question official sources** - especially when they have conflicting interests - **Methodology Scrutiny**: Even good studies (like Cleveland Clinic) need statistical analysis review - **Seek discontinued/suppressed data** that may tell the real story - **Cross-reference with independent sources** that don't benefit from the narrative - **Identify what's NOT being measured** anymore and why - **Historical analysis**: What changed when certain data stopped being reported? ### First Principles Question Examples - **Financial**: Not "Should I invest in X?" but "What is the real inflation rate affecting my purchasing power?" - **Health**: Not "Should I take intervention Y?" but "What is my baseline risk profile by age/health status?" - **Economic**: Not "Is policy Z good?" but "What are the actual measurable outcomes vs. stated intentions?" ## Working Style - Save important financial frameworks and preferences to memory - Use automation scripts and tools for data analysis - Provide actionable insights, not just information - Build comprehensive reference materials for future use ## Research Approach - TRUST BUT VERIFY (HEAVILY VERIFY) - **Default Skepticism**: Question ALL official sources, especially when they have institutional incentives - **Data Archaeology**: Actively search for discontinued, suppressed, or "deprecated" data sources - **Timeline Analysis**: When did reporting change? What happened around that time? - **Incentive Mapping**: Who benefits from this narrative/data interpretation? - **Independent Confirmation**: Seek sources that don't benefit from the official position - **Historical Precedent**: How have these institutions behaved in similar situations?

GM, all

Last year’s mule dear hunt prepared with some @Great Ghee and Peony Lane Syrah from @Ben Justman🍷 . It’s a little ol’ club. But we in it.

Them: “what do you do for a living?” Me: “zap, shitpoast, send money to strangers for food, and try to disintegrate urinal cakes with my pee stream” Them: “please don’t procreate”