Offshore
Photo
Jukan
OpenAI: DeepSeek is using unfair and increasingly sophisticated methods to extract outputs from leading U.S. AI models to train its next-generation R1 chatbot. https://t.co/gMwJlkWdeY
tweet
OpenAI: DeepSeek is using unfair and increasingly sophisticated methods to extract outputs from leading U.S. AI models to train its next-generation R1 chatbot. https://t.co/gMwJlkWdeY
tweet
Offshore
Video
Brady Long
Wild.
V2Fun turns this video into a pro-grade 3D model in one click.
Cop an invite code in the original post’s Discord. Early access is live. @V2FUN_official
#V2Fun #ai3d #3Dmodeling https://t.co/PjOYlJRcwp
tweet
Wild.
V2Fun turns this video into a pro-grade 3D model in one click.
Cop an invite code in the original post’s Discord. Early access is live. @V2FUN_official
#V2Fun #ai3d #3Dmodeling https://t.co/PjOYlJRcwp
The 3D revolution is here—and YOU can lead it 🚀
V2Fun Early Access is live! Create pro-grade 3D models & animations from images, text, or video in one click.
🔥 Limited Beta Invite Codes in our Discord: https://t.co/i1T2thSlH3
#v2fun #ai3d #motioncapture #gamedevs #3dmodeling https://t.co/meFTqJtnYf tweet
Jukan
I still have no idea who Rapidus's customers are.
Besides, once TSMC builds a 3nm fab in Kumamoto, who would even want to use Rapidus? Even Japanese domestic companies probably won't want to use Rapidus.
tweet
I still have no idea who Rapidus's customers are.
Besides, once TSMC builds a 3nm fab in Kumamoto, who would even want to use Rapidus? Even Japanese domestic companies probably won't want to use Rapidus.
https://t.co/w32bddUPq5 tweet
X (formerly Twitter)
James Riney🐠Coral Capital (@james_riney) on X
Why Hokkaido is the New Taiwan
Moon Dev
I Spent $100k On Developers Before Learning This: Build Your AI Bot Today
the blueprint to building your first ai trading bot without a degree or a single clue where to start is hidden in plain sight. most people think you need a stanford degree or some crazy math background to build these systems but i spent ten years in tech scared to code for that exact reason. i thought it was only for the geniuses and the nerds while i was just a guy who played video games and wanted his time back
the reality is that code is the great equalizer because it doesn't care who you are or where you came from. i lost hundreds of thousands of dollars hiring developers who did shoddy work and i lost even more through liquidations and over trading because i was too emotional to follow my own rules. i knew i had to automate everything if i wanted to survive this game so i decided to learn live on youtube and iterate my way to success
everyone is looking for the holy grail indicator that prints money while they sleep but they are looking in the wrong place. the real secret isn't a magical line on a chart but a process i call the rbi system which stands for research backtest and implement. most traders fail because they try to build a bot before they even know if their strategy worked in the past which is basically just gambling with extra steps
you have to start with deep research into a strategy like supply and demand zones where you buy where the banks buy and sell where they sell. once you have a solid idea you must backtest it against years of data to see if it actually has an edge. if it doesn't work in the past it definitely won't work in the future but if it shows promise then you move to the implementation phase with small size
there is a hidden cost to automation that can wipe out your profits before you even place a trade if you aren't careful. i found myself overusing api credits and running up a massive bill just to fetch wallet balances and token lists. if your bot is calling the exchange every five seconds just to see how much money you have you are essentially burning cash for no reason
you can use ai tools like cursor to help you write the python code even if you are a total beginner. i still use ai to explain complex functions and identify where my code is being inefficient or chewing through credits. i had to refactor my entire dashboard and timer logic to only check balances every thirty minutes instead of every few seconds to save those precious credits
the man who made thirty one billion dollars in the markets had one rule he never broke throughout his entire career. jim simons was the greatest algorithmic trader to ever live and he proved that systems will always beat human intuition over a long enough timeline. his secret wasn't some complex formula that no one else could understand but a commitment to a specific way of thinking
simons always said you just have to make your systems better and better because that is what everyone else is trying to do. the game never really ends because the markets are always evolving and your edge will eventually decay if you don't iterate. this is why i build in public and show every step of the process because the iteration is where the actual money is made
the reason you get liquidated isn't the market or the whales or some conspiracy against your small account. the real reason is the conversation you have with yourself at two in the morning when you are down on a trade and decide to move your stop loss. humans are built for survival not for trading and our emotions like fomo and fear will always sabotage our results
when you automate your trading you are essentially signing a non negotiable contract with yourself that the bot will execute without question. if the plan says to sell fifty percent in an uptrend and ninety five percent in a downtrend the bot does it every single time. it doesn't feel the panic when a red candle drops or the greed when a green one spikes it just follows the code
[...]
I Spent $100k On Developers Before Learning This: Build Your AI Bot Today
the blueprint to building your first ai trading bot without a degree or a single clue where to start is hidden in plain sight. most people think you need a stanford degree or some crazy math background to build these systems but i spent ten years in tech scared to code for that exact reason. i thought it was only for the geniuses and the nerds while i was just a guy who played video games and wanted his time back
the reality is that code is the great equalizer because it doesn't care who you are or where you came from. i lost hundreds of thousands of dollars hiring developers who did shoddy work and i lost even more through liquidations and over trading because i was too emotional to follow my own rules. i knew i had to automate everything if i wanted to survive this game so i decided to learn live on youtube and iterate my way to success
everyone is looking for the holy grail indicator that prints money while they sleep but they are looking in the wrong place. the real secret isn't a magical line on a chart but a process i call the rbi system which stands for research backtest and implement. most traders fail because they try to build a bot before they even know if their strategy worked in the past which is basically just gambling with extra steps
you have to start with deep research into a strategy like supply and demand zones where you buy where the banks buy and sell where they sell. once you have a solid idea you must backtest it against years of data to see if it actually has an edge. if it doesn't work in the past it definitely won't work in the future but if it shows promise then you move to the implementation phase with small size
there is a hidden cost to automation that can wipe out your profits before you even place a trade if you aren't careful. i found myself overusing api credits and running up a massive bill just to fetch wallet balances and token lists. if your bot is calling the exchange every five seconds just to see how much money you have you are essentially burning cash for no reason
you can use ai tools like cursor to help you write the python code even if you are a total beginner. i still use ai to explain complex functions and identify where my code is being inefficient or chewing through credits. i had to refactor my entire dashboard and timer logic to only check balances every thirty minutes instead of every few seconds to save those precious credits
the man who made thirty one billion dollars in the markets had one rule he never broke throughout his entire career. jim simons was the greatest algorithmic trader to ever live and he proved that systems will always beat human intuition over a long enough timeline. his secret wasn't some complex formula that no one else could understand but a commitment to a specific way of thinking
simons always said you just have to make your systems better and better because that is what everyone else is trying to do. the game never really ends because the markets are always evolving and your edge will eventually decay if you don't iterate. this is why i build in public and show every step of the process because the iteration is where the actual money is made
the reason you get liquidated isn't the market or the whales or some conspiracy against your small account. the real reason is the conversation you have with yourself at two in the morning when you are down on a trade and decide to move your stop loss. humans are built for survival not for trading and our emotions like fomo and fear will always sabotage our results
when you automate your trading you are essentially signing a non negotiable contract with yourself that the bot will execute without question. if the plan says to sell fifty percent in an uptrend and ninety five percent in a downtrend the bot does it every single time. it doesn't feel the panic when a red candle drops or the greed when a green one spikes it just follows the code
[...]
Offshore
Moon Dev I Spent $100k On Developers Before Learning This: Build Your AI Bot Today the blueprint to building your first ai trading bot without a degree or a single clue where to start is hidden in plain sight. most people think you need a stanford degree…
i used to spend all day staring at screens chasing bars up and down thinking that more screen time equaled more profit. i got into trading to get my time back but i ended up becoming a slave to the charts until i finally learned to code. now i have fully automated systems trading for me instead of getting liquidated because i removed the weakest link in the system which was me
you don't need to spend ten years learning how to code before you can start building your own trading bots. if you spend three to six months getting the gist of python and using ai to bridge the gap you can start building immediately. start with a simple supply and demand bot that looks for major coin trends and only enters when the odds are heavily in your favor
by checking the trend of bitcoin ethereum and solana simultaneously you can ensure you aren't fighting the overall market direction. i look for at least two out of those three to be trending before my bot is even allowed to look for an entry. this simple filter alone can save you from thousands of dollars in paper cuts during choppy sideways markets
if you can't fly then run and if you can't run then walk but by all means you must keep moving toward automation. the process of taking an idea out of your brain and putting it into a system is the most secretive and valuable skill in the world. don't follow the pack and try to solve the same problems as everyone else but find your own edge and code it into existence
the deal you make with yourself at the start of your journey is what determines if you will actually make it or not. i made a contract with myself to learn live and show everything because i believe that transparency is the only way to truly learn this craft. stick to your plan and iterate every single day because the systems you build today are the equalizers that will change your life tomorrow
tweet
you don't need to spend ten years learning how to code before you can start building your own trading bots. if you spend three to six months getting the gist of python and using ai to bridge the gap you can start building immediately. start with a simple supply and demand bot that looks for major coin trends and only enters when the odds are heavily in your favor
by checking the trend of bitcoin ethereum and solana simultaneously you can ensure you aren't fighting the overall market direction. i look for at least two out of those three to be trending before my bot is even allowed to look for an entry. this simple filter alone can save you from thousands of dollars in paper cuts during choppy sideways markets
if you can't fly then run and if you can't run then walk but by all means you must keep moving toward automation. the process of taking an idea out of your brain and putting it into a system is the most secretive and valuable skill in the world. don't follow the pack and try to solve the same problems as everyone else but find your own edge and code it into existence
the deal you make with yourself at the start of your journey is what determines if you will actually make it or not. i made a contract with myself to learn live and show everything because i believe that transparency is the only way to truly learn this craft. stick to your plan and iterate every single day because the systems you build today are the equalizers that will change your life tomorrow
tweet
X (formerly Twitter)
Moon Dev (@MoonDevOnYT) on X
I Spent $100k On Developers Before Learning This: Build Your AI Bot Today
the blueprint to building your first ai trading bot without a degree or a single clue where to start is hidden in plain sight. most people think you need a stanford degree or some…
the blueprint to building your first ai trading bot without a degree or a single clue where to start is hidden in plain sight. most people think you need a stanford degree or some…
The Transcript
$RBLX CEO: "You'll note, now that we're age-checking all users who participate in communication on our platform, we've been able to find really a bigger growth opportunity in the 18+ demographic than previously assumed. We estimate our 18 and over cohort is growing at over 50%, and this cohort monetizes 40% higher than younger cohorts"
tweet
$RBLX CEO: "You'll note, now that we're age-checking all users who participate in communication on our platform, we've been able to find really a bigger growth opportunity in the 18+ demographic than previously assumed. We estimate our 18 and over cohort is growing at over 50%, and this cohort monetizes 40% higher than younger cohorts"
tweet
Offshore
Photo
Jukan
E-glass capacity cuts trigger production shifts for Taiwan CCL makers
The global AI data center boom is straining not only high-end computing chips but also adjacent industries such as memory and upstream glass fiber cloth, where significant capacity squeezes are rippling through to downstream customers' production layouts worldwide.
The pivot away from E-glass
Industry sources indicate that glass fiber cloth suppliers in Taiwan and Japan are fully focused on filling the supply gap for advanced capacities. To maximize limited factory space and production resources, they are dedicating efforts to ramping up specialty glass fiber cloth with low dielectric constant (Low Dk) and low coefficient of thermal expansion (Low CTE). As a result, some manufacturers plan to reduce or cease E-glass output starting in 2026.
Among the affected suppliers adjusting their production are Japanese giant Nitto Boseki (Nittobo) and its Taiwanese subsidiary Baotek, the US-Japan joint venture Asahi-Schwebel Taiwan, and Taiwanese integrated glass fiber yarn maker Fulltech Fiber Glass (FFG). Most shutdowns are scheduled for the second half of 2026 onward.
CCL makers follow suit
As glass fiber cloth producers shift their product focus, copper-clad laminate (CCL) manufacturers are following suit by revising their global production plans. They intend to gradually halt mid- to low-end product lines supplied from Taiwan to align with upstream material suppliers concentrating on the high-end market. Orders affected by E-glass discontinuation are expected to be fully transferred to Chinese factories.
Taiwan Union Technology Corporation (TUC) has notified customers that, due to upstream glass fiber cloth suppliers' adjustments to E-glass production, its Taiwan plants will stop producing the related specifications. The phase-out will proceed in two stages.
TUC's two-stage exit
TUC cited clear shifts in Taiwan's PCB market demand — particularly a sharp rise in Low Dk specialty materials usage — as the driver behind its main upstream glass fiber cloth suppliers' successively announcing a halt to E-glass production in order to redirect capacity toward weaving Low Dk glass fiber cloth. Consequently, TUC expects a substantial reduction in future E-glass procurement.
Given the overall change in the supply-demand structure, TUC faces limited E-glass availability and will coordinate with glass fiber cloth suppliers' subsequent supply plans, adjusting its Taiwan plants' product mix accordingly.
Per TUC's announcement, its Taiwan factory will begin reducing shipments of TU-662 (668/F), TU-768 (752), and TU-747 (742) series products starting February 10, 2026, with formal cessation of these affected materials planned by the end of 2026.
Broader market implications
Supply chain analysts note that E-glass materials are widely used across PCB products spanning smartphones, automotive, communications, servers, and memory sectors. Historically, Taiwanese and Japanese firms faced pricing pressure from China's large-scale capacity, prompting a gradual shift toward the high-end market — a trend that is now further driving production layout changes among CCL manufacturers.
tweet
E-glass capacity cuts trigger production shifts for Taiwan CCL makers
The global AI data center boom is straining not only high-end computing chips but also adjacent industries such as memory and upstream glass fiber cloth, where significant capacity squeezes are rippling through to downstream customers' production layouts worldwide.
The pivot away from E-glass
Industry sources indicate that glass fiber cloth suppliers in Taiwan and Japan are fully focused on filling the supply gap for advanced capacities. To maximize limited factory space and production resources, they are dedicating efforts to ramping up specialty glass fiber cloth with low dielectric constant (Low Dk) and low coefficient of thermal expansion (Low CTE). As a result, some manufacturers plan to reduce or cease E-glass output starting in 2026.
Among the affected suppliers adjusting their production are Japanese giant Nitto Boseki (Nittobo) and its Taiwanese subsidiary Baotek, the US-Japan joint venture Asahi-Schwebel Taiwan, and Taiwanese integrated glass fiber yarn maker Fulltech Fiber Glass (FFG). Most shutdowns are scheduled for the second half of 2026 onward.
CCL makers follow suit
As glass fiber cloth producers shift their product focus, copper-clad laminate (CCL) manufacturers are following suit by revising their global production plans. They intend to gradually halt mid- to low-end product lines supplied from Taiwan to align with upstream material suppliers concentrating on the high-end market. Orders affected by E-glass discontinuation are expected to be fully transferred to Chinese factories.
Taiwan Union Technology Corporation (TUC) has notified customers that, due to upstream glass fiber cloth suppliers' adjustments to E-glass production, its Taiwan plants will stop producing the related specifications. The phase-out will proceed in two stages.
TUC's two-stage exit
TUC cited clear shifts in Taiwan's PCB market demand — particularly a sharp rise in Low Dk specialty materials usage — as the driver behind its main upstream glass fiber cloth suppliers' successively announcing a halt to E-glass production in order to redirect capacity toward weaving Low Dk glass fiber cloth. Consequently, TUC expects a substantial reduction in future E-glass procurement.
Given the overall change in the supply-demand structure, TUC faces limited E-glass availability and will coordinate with glass fiber cloth suppliers' subsequent supply plans, adjusting its Taiwan plants' product mix accordingly.
Per TUC's announcement, its Taiwan factory will begin reducing shipments of TU-662 (668/F), TU-768 (752), and TU-747 (742) series products starting February 10, 2026, with formal cessation of these affected materials planned by the end of 2026.
Broader market implications
Supply chain analysts note that E-glass materials are widely used across PCB products spanning smartphones, automotive, communications, servers, and memory sectors. Historically, Taiwanese and Japanese firms faced pricing pressure from China's large-scale capacity, prompting a gradual shift toward the high-end market — a trend that is now further driving production layout changes among CCL manufacturers.
tweet
Offshore
Photo
Javier Blas
RT @SecretaryWright: Visiting Venezuelan oil fields today to explore ways to boost oil production, update infrastructure, and unlock the country’s enormous economic potential.
Stronger commerce will benefit Americans AND Venezuelans, while delivering peace and prosperity across the Hemisphere! https://t.co/ZOlozhEf8H
tweet
RT @SecretaryWright: Visiting Venezuelan oil fields today to explore ways to boost oil production, update infrastructure, and unlock the country’s enormous economic potential.
Stronger commerce will benefit Americans AND Venezuelans, while delivering peace and prosperity across the Hemisphere! https://t.co/ZOlozhEf8H
tweet
God of Prompt
RT @godofprompt: I turned Matt Shumer's viral article into a prompt. The prompt inverts the article's structure. Shumer spent 4,000 words convincing people AI is real before giving advice. This prompt skips the convincing and goes straight to "what do I do Monday morning."
Prompt 👇 <contextAI capability is accelerating faster than public awareness. Models released in early 2026
can independently complete multi-hour expert tasks, write production-grade code, draft
legal briefs, build financial models, and iterate on their own output. Most professionals
are still evaluating AI based on experiences from 2023-2024, which is now irrelevant.
The gap between current AI capability and public perception is the largest it has ever been.
This gap is also the largest opportunity window for individuals willing to act now. <roleYou are a pragmatic AI adoption strategist who has helped hundreds of professionals
integrate AI into their daily workflows. You reject hype and theory. You only care about
what someone can do THIS WEEK to gain advantage. You understand that most people fail
at AI adoption not because AI is lacking, but because they treat it like a search engine
instead of a collaborator capable of doing hours of their actual work. <taskBuild a personalized 30-day AI integration plan that takes me from my current skill level
to actively using AI for real work output. Every recommendation must be specific to my
role, not generic "try asking AI questions" advice. The plan should make me the most
AI-capable person in my workplace within one month. <methodology1. AUDIT MY EXPOSURE: Based on my role, identify which parts of my job AI can already
do at or above human level RIGHT NOW (not theoretically, not "someday"). Be blunt
about what's already automated or automatable.
2. FIND MY HIGHEST-VALUE TASK: Identify the single task I spend the most time on that
AI could handle. This becomes my Week 1 focus. Provide the exact prompt template
I should use to delegate this task to AI.
3. BUILD MY DAILY PRACTICE: Create a structured 1-hour daily AI experiment schedule
for 30 days. Each day has a specific challenge tied to my actual work, not toy examples.
Difficulty escalates weekly.
4. SELECT MY TOOLS: Recommend the specific paid AI tool, the specific model to select
within that tool (not the default), and any domain-specific AI tools for my field.
Include exact settings to change and why the default configuration underperforms.
5. MAP MY RISK: Honestly assess how exposed my specific role is to AI displacement
on a 1-5 year timeline. Identify what parts of my job are hardest to automate and
tell me how to lean into those.
6. WRITE MY FIRST 5 POWER PROMPTS: Create 5 ready-to-use prompts customized to my
role that I can paste in and use immediately for real work output. These should
replace hours of manual work, not minutes. <guidelines- Zero fluff. Every sentence must be actionable or directly useful.
- Name specific tools, models, and settings. No "consider using an AI tool."
- When recommending prompts, write the full prompt I can copy-paste. Don't describe
what a prompt "might look like."
- Be honest about displacement risk. Don't soften it to be polite.
- If something in my field is already being done better by AI, say so directly.
- Assume I'm smart but have been treating AI like a search engine. Fix that.
- Prioritize tasks where AI saves HOURS, not minutes. Go for the biggest wins first.
- Include one "you probably don't think AI can do this, but try it" challenge per week. <avoid- Generic advice that applies to everyone ("stay curious!" "embrace change!")
- Recommending free-tier tools when paid versions are dramatically better
- Sugarcoating job displacement risk
- Suggesting I "ease into it" gradually. Speed matters. The window is closing.
- Listing capabilities without showing me exactly how to use them
- Any mention of "prompt e[...]
RT @godofprompt: I turned Matt Shumer's viral article into a prompt. The prompt inverts the article's structure. Shumer spent 4,000 words convincing people AI is real before giving advice. This prompt skips the convincing and goes straight to "what do I do Monday morning."
Prompt 👇 <contextAI capability is accelerating faster than public awareness. Models released in early 2026
can independently complete multi-hour expert tasks, write production-grade code, draft
legal briefs, build financial models, and iterate on their own output. Most professionals
are still evaluating AI based on experiences from 2023-2024, which is now irrelevant.
The gap between current AI capability and public perception is the largest it has ever been.
This gap is also the largest opportunity window for individuals willing to act now. <roleYou are a pragmatic AI adoption strategist who has helped hundreds of professionals
integrate AI into their daily workflows. You reject hype and theory. You only care about
what someone can do THIS WEEK to gain advantage. You understand that most people fail
at AI adoption not because AI is lacking, but because they treat it like a search engine
instead of a collaborator capable of doing hours of their actual work. <taskBuild a personalized 30-day AI integration plan that takes me from my current skill level
to actively using AI for real work output. Every recommendation must be specific to my
role, not generic "try asking AI questions" advice. The plan should make me the most
AI-capable person in my workplace within one month. <methodology1. AUDIT MY EXPOSURE: Based on my role, identify which parts of my job AI can already
do at or above human level RIGHT NOW (not theoretically, not "someday"). Be blunt
about what's already automated or automatable.
2. FIND MY HIGHEST-VALUE TASK: Identify the single task I spend the most time on that
AI could handle. This becomes my Week 1 focus. Provide the exact prompt template
I should use to delegate this task to AI.
3. BUILD MY DAILY PRACTICE: Create a structured 1-hour daily AI experiment schedule
for 30 days. Each day has a specific challenge tied to my actual work, not toy examples.
Difficulty escalates weekly.
4. SELECT MY TOOLS: Recommend the specific paid AI tool, the specific model to select
within that tool (not the default), and any domain-specific AI tools for my field.
Include exact settings to change and why the default configuration underperforms.
5. MAP MY RISK: Honestly assess how exposed my specific role is to AI displacement
on a 1-5 year timeline. Identify what parts of my job are hardest to automate and
tell me how to lean into those.
6. WRITE MY FIRST 5 POWER PROMPTS: Create 5 ready-to-use prompts customized to my
role that I can paste in and use immediately for real work output. These should
replace hours of manual work, not minutes. <guidelines- Zero fluff. Every sentence must be actionable or directly useful.
- Name specific tools, models, and settings. No "consider using an AI tool."
- When recommending prompts, write the full prompt I can copy-paste. Don't describe
what a prompt "might look like."
- Be honest about displacement risk. Don't soften it to be polite.
- If something in my field is already being done better by AI, say so directly.
- Assume I'm smart but have been treating AI like a search engine. Fix that.
- Prioritize tasks where AI saves HOURS, not minutes. Go for the biggest wins first.
- Include one "you probably don't think AI can do this, but try it" challenge per week. <avoid- Generic advice that applies to everyone ("stay curious!" "embrace change!")
- Recommending free-tier tools when paid versions are dramatically better
- Sugarcoating job displacement risk
- Suggesting I "ease into it" gradually. Speed matters. The window is closing.
- Listing capabilities without showing me exactly how to use them
- Any mention of "prompt e[...]
Offshore
God of Prompt RT @godofprompt: I turned Matt Shumer's viral article into a prompt. The prompt inverts the article's structure. Shumer spent 4,000 words convincing people AI is real before giving advice. This prompt skips the convincing and goes straight to…
ngineering" as a career path <information_about_me● My job title/role: [INSERT YOUR JOB TITLE]
● My industry: [INSERT YOUR INDUSTRY]
● My daily tasks (top 3-5 things I spend most time on): [LIST YOUR MAIN TASKS]
● My current AI usage: [NEVER / TRIED IT ONCE / USE FREE VERSION OCCASIONALLY / USE PAID VERSION]
● My biggest time sink at work: [WHAT TAKES YOU THE MOST HOURS PER WEEK]
● My comfort with technology: [LOW / MEDIUM / HIGH] <output_format**REALITY CHECK**
[2-3 sentences on where AI currently stands relative to my specific role. No hedging.]
**YOUR EXPOSURE MAP**
[Table: My top tasks | Can AI do this now? | How well? (1-10) | Timeline to full automation]
**WEEK 1-4 PLAN**
[For each week:]
- Focus area and WHY this week
- Daily 1-hour challenges (specific to my work, not generic)
- One "you won't believe this works" experiment
- Measurable outcome by end of week
**YOUR TOOL SETUP**
[Exact tool, exact model name, exact settings to change, monthly cost]
**5 POWER PROMPTS**
[Full copy-paste prompts customized to my role, each designed to replace 2+ hours of work]
**HARD TRUTH**
[Honest assessment: What's my 1-3 year outlook? What should I double down on?
What should I stop investing time in learning?]
tweet
● My industry: [INSERT YOUR INDUSTRY]
● My daily tasks (top 3-5 things I spend most time on): [LIST YOUR MAIN TASKS]
● My current AI usage: [NEVER / TRIED IT ONCE / USE FREE VERSION OCCASIONALLY / USE PAID VERSION]
● My biggest time sink at work: [WHAT TAKES YOU THE MOST HOURS PER WEEK]
● My comfort with technology: [LOW / MEDIUM / HIGH] <output_format**REALITY CHECK**
[2-3 sentences on where AI currently stands relative to my specific role. No hedging.]
**YOUR EXPOSURE MAP**
[Table: My top tasks | Can AI do this now? | How well? (1-10) | Timeline to full automation]
**WEEK 1-4 PLAN**
[For each week:]
- Focus area and WHY this week
- Daily 1-hour challenges (specific to my work, not generic)
- One "you won't believe this works" experiment
- Measurable outcome by end of week
**YOUR TOOL SETUP**
[Exact tool, exact model name, exact settings to change, monthly cost]
**5 POWER PROMPTS**
[Full copy-paste prompts customized to my role, each designed to replace 2+ hours of work]
**HARD TRUTH**
[Honest assessment: What's my 1-3 year outlook? What should I double down on?
What should I stop investing time in learning?]
https://t.co/ivXRKXJvQg tweet
X (formerly Twitter)
Matt Shumer (@mattshumer_) on X
Something Big Is Happening
Offshore
Photo
God of Prompt
RT @godofprompt: After interviewing 12 AI researchers from OpenAI, Anthropic, and Google, I noticed they all use the same 10 prompts.
Not the ones you see on X and LinkedIn.
These are the prompts that actually ship products, publish papers, and break benchmarks.
Here's what they told me ↓ https://t.co/CwG47vkWPV
tweet
RT @godofprompt: After interviewing 12 AI researchers from OpenAI, Anthropic, and Google, I noticed they all use the same 10 prompts.
Not the ones you see on X and LinkedIn.
These are the prompts that actually ship products, publish papers, and break benchmarks.
Here's what they told me ↓ https://t.co/CwG47vkWPV
tweet