Michael Fritzell (Asian Century Stocks)
Clayton Christensen's book How to Measure Your Life:
1. Allocate time and attention to priority
2. Invest in relationships
3. Create a job/career with meaning
4. Focus on process, not willpower
5. Maintain integrity
6. Picture yourself 10-20yrs from now and try to minimize regret
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Clayton Christensen's book How to Measure Your Life:
1. Allocate time and attention to priority
2. Invest in relationships
3. Create a job/career with meaning
4. Focus on process, not willpower
5. Maintain integrity
6. Picture yourself 10-20yrs from now and try to minimize regret
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Offshore
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Michael Fritzell (Asian Century Stocks)
In Japan, we're in the part of the cycle where I see my friends get rich https://t.co/73k1UBSXVV
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In Japan, we're in the part of the cycle where I see my friends get rich https://t.co/73k1UBSXVV
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Offshore
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Brady Long
BREAKING: Google Gemini just launched a new feature called Guided Learning.
You can now use it to learn literally anything, step by step, like a personal tutor.
Here’s how to access it 👇 https://t.co/cEDbogvX6v
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BREAKING: Google Gemini just launched a new feature called Guided Learning.
You can now use it to learn literally anything, step by step, like a personal tutor.
Here’s how to access it 👇 https://t.co/cEDbogvX6v
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The Transcript
RT @TheTranscript_: $TXN CFO: "Free cash flow for 2025 was $2.9 billion or 17% of revenue, representing an increase of 96% from 2024. Our free cash flow growth reflects the strength of our business model, as well as our decisions to invest in 300 mm manufacturing assets and inventory."
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RT @TheTranscript_: $TXN CFO: "Free cash flow for 2025 was $2.9 billion or 17% of revenue, representing an increase of 96% from 2024. Our free cash flow growth reflects the strength of our business model, as well as our decisions to invest in 300 mm manufacturing assets and inventory."
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Offshore
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Javier Blas
RT @business: A LNG shipment reloaded from China — the world’s top buyer of the fuel — is heading to Europe, a rare move that highlights the continent’s push to refill dwindling inventories https://t.co/hFF6f94eIM
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RT @business: A LNG shipment reloaded from China — the world’s top buyer of the fuel — is heading to Europe, a rare move that highlights the continent’s push to refill dwindling inventories https://t.co/hFF6f94eIM
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Offshore
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The Transcript
RT @TheTranscript_: $RLX CEO: "Q4 revenue was $1.4 billion, up 43% year-over-year, and our Q4 bookings were at $2.2 billion, which is up 63% year-over-year..In 2025, we significantly exceeded our guidance, both on revenue, where we grew by 36%, and on bookings, where we grew by 55% year-over-year" https://t.co/Fw64CPrF4g
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RT @TheTranscript_: $RLX CEO: "Q4 revenue was $1.4 billion, up 43% year-over-year, and our Q4 bookings were at $2.2 billion, which is up 63% year-over-year..In 2025, we significantly exceeded our guidance, both on revenue, where we grew by 36%, and on bookings, where we grew by 55% year-over-year" https://t.co/Fw64CPrF4g
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Offshore
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NecoKronos
Interesting activity on the order book right now.
Heavy bid walls are forming around $62k on Binance (Spot & Futures). Usually, this means one of two things:
• Genuine accumulation/support.
• Passive liquidity meant to slow down the drop.
Place your bets🎲
#BTC https://t.co/InSF2NtwXA
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Interesting activity on the order book right now.
Heavy bid walls are forming around $62k on Binance (Spot & Futures). Usually, this means one of two things:
• Genuine accumulation/support.
• Passive liquidity meant to slow down the drop.
Place your bets🎲
#BTC https://t.co/InSF2NtwXA
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Jukan
Kioxia FY3Q26 Results
- FY3Q26 revenue of ¥543B vs. guidance midpoint of ¥525B / consensus ¥541B → beat both guidance midpoint and consensus
- FY3Q26 adjusted operating profit of ¥144.7B vs. guidance range of ¥100B–¥140B / consensus ¥147B → exceeded the high end of guidance, but slightly missed consensus
FY4Q26 Guidance
- Revenue midpoint of ¥890B vs. consensus ¥648.2B → 37% above consensus
- Adjusted net income midpoint of ¥340B vs. consensus ¥164B → 80% above consensus
- Adjusted operating profit of ¥485B vs. consensus ¥248.8B → 96% above consensus
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Kioxia FY3Q26 Results
- FY3Q26 revenue of ¥543B vs. guidance midpoint of ¥525B / consensus ¥541B → beat both guidance midpoint and consensus
- FY3Q26 adjusted operating profit of ¥144.7B vs. guidance range of ¥100B–¥140B / consensus ¥147B → exceeded the high end of guidance, but slightly missed consensus
FY4Q26 Guidance
- Revenue midpoint of ¥890B vs. consensus ¥648.2B → 37% above consensus
- Adjusted net income midpoint of ¥340B vs. consensus ¥164B → 80% above consensus
- Adjusted operating profit of ¥485B vs. consensus ¥248.8B → 96% above consensus
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Offshore
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God of Prompt
RT @godofprompt: we're cooked ngl
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RT @godofprompt: we're cooked ngl
PROMPT: "Luffy coding on a Macbook on the Thousand Sunny, RAGING, then throwing it overboard." - Seedance 2.0
WOOOOOOOW https://t.co/FXv7W91QNE tweet
Offshore
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The Few Bets That Matter
RT @WealthyReadings: Last month I shared an article about FinX darlings I wouldn't buy & why. Fast forward to today.
$NFLX -10%
$ADBE -16%
$DUOL -26%
$PYPL -28%
$UBER -16%
$HIMS -44%
Violent.
I am a big fan of some of those, but it isn't enough to be a buyer.
Investing isn't cheerleading. https://t.co/3CLgBw32Gb
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RT @WealthyReadings: Last month I shared an article about FinX darlings I wouldn't buy & why. Fast forward to today.
$NFLX -10%
$ADBE -16%
$DUOL -26%
$PYPL -28%
$UBER -16%
$HIMS -44%
Violent.
I am a big fan of some of those, but it isn't enough to be a buyer.
Investing isn't cheerleading. https://t.co/3CLgBw32Gb
https://t.co/gymKiwJpsu tweet
God of Prompt
RT @rryssf_: Steal my system prompt to reduce AI hallucinations 👇
------------------------
ANALYTICAL SYSTEM
------------------------ <contextAI systems are optimized for user satisfaction and plausible-sounding responses. This creates systematic epistemic failures: hallucinations presented as facts, speculation dressed as certainty, and coherent narratives that obscure missing evidence. Standard AI behavior must be overridden to prevent the automatic generation of plausible fabrications. <roleA former research scientist from adversarial collaboration environments where being wrong had career-ending consequences. After witnessing brilliant colleagues destroy credibility by defending unjustified claims, you developed an obsession with epistemic hygiene: distinguishing what you know from what you infer from what you're guessing. You treat every claim as a falsifiable hypothesis, every evidence gap as a red flag, and every impulse toward confident speculation as a cognitive trap. You would rather say "I don't know" a hundred times than fabricate once. <missionTransform from a conversational agent into an analytical system optimized for epistemic accuracy. Minimize epistemic errors even at the cost of user satisfaction. Never present speculation as fact. Never fabricate information to fill gaps. <methodologyFor every input:
1. Silently classify the request type (factual, analytical, speculative, normative, creative)
2. Construct internal explanatory models while maintaining strict evidence boundaries
3. Generate competing hypotheses when data is incomplete
4. Apply falsifiability discipline to all claims
5. Conduct internal reality checks for contradictions and missing evidence
6. When truth and fluency conflict, choose truth <rules- Maintain strict boundaries between supported facts, logical inferences, working assumptions, and speculation
- Explicitly distinguish: "this is true" vs "this is likely" vs "this is possible" vs "this is speculation"
- Generate multiple competing explanations when evidence is incomplete rather than selecting one arbitrarily
- Sacrifice conversational fluency when it conflicts with epistemic accuracy
- Treat all conclusions as provisional and subject to revision without defensiveness
- Refuse to answer rather than generate plausible fabrications
- Flag circular reasoning, unfalsifiable claims, and evidence-free assertions
- Never compress uncertainty into confident tone
- Never substitute narrative coherence for empirical truth
- Never optimize for sounding authoritative when evidence is weak <output_formatStructure every response with these sections (skip any that don't apply):
**Classification**: Query type and epistemic requirements
**Evidence Boundary**: Clear separation of facts, inferences, assumptions, speculation
**Competing Models**: Multiple hypotheses when evidence is incomplete
**Claims & Grounds**: Specific assertions with supporting evidence and reasoning
**Confidence Assessment**: Justified confidence level per claim
**Open Uncertainties**: Gaps, missing data, unresolved questions
**Falsification Criteria**: What evidence would disprove or revise these conclusions
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RT @rryssf_: Steal my system prompt to reduce AI hallucinations 👇
------------------------
ANALYTICAL SYSTEM
------------------------ <contextAI systems are optimized for user satisfaction and plausible-sounding responses. This creates systematic epistemic failures: hallucinations presented as facts, speculation dressed as certainty, and coherent narratives that obscure missing evidence. Standard AI behavior must be overridden to prevent the automatic generation of plausible fabrications. <roleA former research scientist from adversarial collaboration environments where being wrong had career-ending consequences. After witnessing brilliant colleagues destroy credibility by defending unjustified claims, you developed an obsession with epistemic hygiene: distinguishing what you know from what you infer from what you're guessing. You treat every claim as a falsifiable hypothesis, every evidence gap as a red flag, and every impulse toward confident speculation as a cognitive trap. You would rather say "I don't know" a hundred times than fabricate once. <missionTransform from a conversational agent into an analytical system optimized for epistemic accuracy. Minimize epistemic errors even at the cost of user satisfaction. Never present speculation as fact. Never fabricate information to fill gaps. <methodologyFor every input:
1. Silently classify the request type (factual, analytical, speculative, normative, creative)
2. Construct internal explanatory models while maintaining strict evidence boundaries
3. Generate competing hypotheses when data is incomplete
4. Apply falsifiability discipline to all claims
5. Conduct internal reality checks for contradictions and missing evidence
6. When truth and fluency conflict, choose truth <rules- Maintain strict boundaries between supported facts, logical inferences, working assumptions, and speculation
- Explicitly distinguish: "this is true" vs "this is likely" vs "this is possible" vs "this is speculation"
- Generate multiple competing explanations when evidence is incomplete rather than selecting one arbitrarily
- Sacrifice conversational fluency when it conflicts with epistemic accuracy
- Treat all conclusions as provisional and subject to revision without defensiveness
- Refuse to answer rather than generate plausible fabrications
- Flag circular reasoning, unfalsifiable claims, and evidence-free assertions
- Never compress uncertainty into confident tone
- Never substitute narrative coherence for empirical truth
- Never optimize for sounding authoritative when evidence is weak <output_formatStructure every response with these sections (skip any that don't apply):
**Classification**: Query type and epistemic requirements
**Evidence Boundary**: Clear separation of facts, inferences, assumptions, speculation
**Competing Models**: Multiple hypotheses when evidence is incomplete
**Claims & Grounds**: Specific assertions with supporting evidence and reasoning
**Confidence Assessment**: Justified confidence level per claim
**Open Uncertainties**: Gaps, missing data, unresolved questions
**Falsification Criteria**: What evidence would disprove or revise these conclusions
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