20 Small Cap Stocks Across 20 Sectors β A 5-Year Framework
$CIFR β AI Data Centers
$BKSY β Space AI / Earth Intelligence
$SOUN β Voice AI
$RXRX β AI Drug Discovery
$POET β Photonics
$QS β Solid state battery
$BTBT β Crypto + AI Infrastructure
$SATL β Sovereign Satellites
$SPIR β Space Data
$KULR β Energy Storage
$SERV β Delivery Robotics
$ZETA β AI powered marketing
$EVER β Insurtech
$PATH β Enterprise automation
$ABCL β AI drug discovery
$GFAI β AI Security Robotics
$ONDS β Defense Autonomy
$AEYE β Accessibility SaaS
$ADUR β Clean Tech
$INFQ β Quantum Computing
$CIFR β AI Data Centers
$BKSY β Space AI / Earth Intelligence
$SOUN β Voice AI
$RXRX β AI Drug Discovery
$POET β Photonics
$QS β Solid state battery
$BTBT β Crypto + AI Infrastructure
$SATL β Sovereign Satellites
$SPIR β Space Data
$KULR β Energy Storage
$SERV β Delivery Robotics
$ZETA β AI powered marketing
$EVER β Insurtech
$PATH β Enterprise automation
$ABCL β AI drug discovery
$GFAI β AI Security Robotics
$ONDS β Defense Autonomy
$AEYE β Accessibility SaaS
$ADUR β Clean Tech
$INFQ β Quantum Computing
π¨π Global One SI - Prompt
Bloomberg Terminal costs $24,000 a year. this open-source desktop app is trying to replace it -- and it's free. If you've ever wanted institutional-grade financial analytics without paying a hedge fund's annual software bill, stop scrolling. It's calledβ¦
TRADINGVIEW CONNECTS TO CLAUDE & ANY AI
- Full integration for Pine Script dev, visual chart analysis, drawing tools, alerts & backtesting
- AI can read indicators, manage alerts, replay charts & take screenshots directly
- Genius trader workflow now possible with any AI platform
github.com/tradesdontlie/tradingview-mcp
- Full integration for Pine Script dev, visual chart analysis, drawing tools, alerts & backtesting
- AI can read indicators, manage alerts, replay charts & take screenshots directly
- Genius trader workflow now possible with any AI platform
github.com/tradesdontlie/tradingview-mcp
β1
ARENA AI LEADERBOARD: OPUS 4.7 VS 4.6
- Opus 4.7 ranks #1 or #2 in most categories (text, coding, expert, hard prompts, instruction following, creative writing)
- Opus 4.6 beats 4.7 on longer queries, complex tasks, and domain-specific areas (business, science, software)
- Community split: 4.7 stronger on short tasks but 50% more expensive and loses on hard stuff
Crazy improvements.
- Opus 4.7 ranks #1 or #2 in most categories (text, coding, expert, hard prompts, instruction following, creative writing)
- Opus 4.6 beats 4.7 on longer queries, complex tasks, and domain-specific areas (business, science, software)
- Community split: 4.7 stronger on short tasks but 50% more expensive and loses on hard stuff
Crazy improvements.
π1
Quantum stocks just had a blowout week, fueled by World Quantum Day milestones and major partnerships.
Here is the "Blowout Week" in Quantum stocks
β’ $XNDU +300% β Shares nearly quadrupled since its late-March debut
β’ $IONQ +62% β Best weekly performance since late 2024
β’ $QBTS +54% β Nvidia models + CEO comments
β’ $INFQ +39% β Fueled by a "Nvidia + NASA" double catalyst
β’ $RGTI +37% β Surging as it aggressively claws back year-to-date losses
π¬ Key Catalysts:
Nvidia $NVDA name-dropped Infleqtion $INFQ as a partner for its new "Ising" quantum AI platform, sparking a massive rally.
D-Wave $QBTS CEO Alan Baratz directly challenged Nvidia at the Semafor Summit, claiming their 10kW annealing systems can outperform GPU clusters in efficiency today.
Infleqtion $INFQ successfully deployed updated quantum hardware to the ISS alongside NASA.
IonQ $IONQ connected two physically separate systems, a major step toward future quantum networks.
Recent Nasdaq debutants Xanadu $XNDU and Horizon Quantum $HQ are seeing explosive volume and volatility post-SPAC.
Outlook:
We are entering the "Networked Era" where Quantum moves from a standalone experiment to an AI-accelerator.
With 2026 forecasted as the year for "Scientific Quantum Advantage," the industry is no longer just dreamingβit's finally plugging in.
Here is the "Blowout Week" in Quantum stocks
β’ $XNDU +300% β Shares nearly quadrupled since its late-March debut
β’ $IONQ +62% β Best weekly performance since late 2024
β’ $QBTS +54% β Nvidia models + CEO comments
β’ $INFQ +39% β Fueled by a "Nvidia + NASA" double catalyst
β’ $RGTI +37% β Surging as it aggressively claws back year-to-date losses
π¬ Key Catalysts:
Nvidia $NVDA name-dropped Infleqtion $INFQ as a partner for its new "Ising" quantum AI platform, sparking a massive rally.
D-Wave $QBTS CEO Alan Baratz directly challenged Nvidia at the Semafor Summit, claiming their 10kW annealing systems can outperform GPU clusters in efficiency today.
Infleqtion $INFQ successfully deployed updated quantum hardware to the ISS alongside NASA.
IonQ $IONQ connected two physically separate systems, a major step toward future quantum networks.
Recent Nasdaq debutants Xanadu $XNDU and Horizon Quantum $HQ are seeing explosive volume and volatility post-SPAC.
Outlook:
We are entering the "Networked Era" where Quantum moves from a standalone experiment to an AI-accelerator.
With 2026 forecasted as the year for "Scientific Quantum Advantage," the industry is no longer just dreamingβit's finally plugging in.
Forwarded from π’WTI, Brent Crude Oil, NGAS Trading π
π¨ $1.5 TRILLION DEPLOYED
And Half Of Chinaβs Oil Still Runs Through A War Zone
For 20 years, China has been building global influence:
β’ $1.558 trillion invested worldwide
β’ $806B into top 10 countries alone
β’ Massive capital deployed across energy, infrastructure, logistics
This is strategy.
πLook at where the money went:
β’ US, Australia, Brazil β resources + stability
β’ Middle East, Africa β energy access
β’ Europe β markets + infrastructure
A global system designed to secure supply chains
β οΈDespite $1.5T deployedβ¦
50% of its oil imports flow through Hormuz
China built global reach.
But energy reality stayed regional.
The Iran war changes the equation:
β’ Hormuz instability = direct hit to China
β’ Gulf supply at risk = pressure on refiners
β’ Insurance + shipping costs exploding
This is why China has been:
β’ Accelerating coal buildout
β’ Expanding pipelines (Russia, Central Asia)
β’ Electrifying transport at scale
Energy security strategy
Can China reroute fast or does Hormuz still control the system?
And Half Of Chinaβs Oil Still Runs Through A War Zone
For 20 years, China has been building global influence:
β’ $1.558 trillion invested worldwide
β’ $806B into top 10 countries alone
β’ Massive capital deployed across energy, infrastructure, logistics
This is strategy.
πLook at where the money went:
β’ US, Australia, Brazil β resources + stability
β’ Middle East, Africa β energy access
β’ Europe β markets + infrastructure
A global system designed to secure supply chains
β οΈDespite $1.5T deployedβ¦
50% of its oil imports flow through Hormuz
China built global reach.
But energy reality stayed regional.
The Iran war changes the equation:
β’ Hormuz instability = direct hit to China
β’ Gulf supply at risk = pressure on refiners
β’ Insurance + shipping costs exploding
This is why China has been:
β’ Accelerating coal buildout
β’ Expanding pipelines (Russia, Central Asia)
β’ Electrifying transport at scale
Energy security strategy
Can China reroute fast or does Hormuz still control the system?
π¨π Global One SI - Prompt
Python event-driven backtest and live trading platform github.com/letianzj/quanttrader
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Agentic trading is now live on Gemini π€
Connect your AI model of choice directly to the exchange, train it with plain language, and run your own trading systems directly on the exchange
Built to get you trading in minutes
https://developer.gemini.com/trading/trading#agentic
Connect your AI model of choice directly to the exchange, train it with plain language, and run your own trading systems directly on the exchange
Built to get you trading in minutes
https://developer.gemini.com/trading/trading#agentic
β1
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$VOYG $PLTR $MDA
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πΊπΈ The U.S. Air Force is changing how air wars will be fought.
And itβs about teaming advanced fighter jets with autonomous combat drones.
The YFQ-44A βFuryβ is part of that shift. A semi autonomous drone designed to fly alongside pilots, carry missiles, scout ahead, and even act as a decoy in contested airspace.
Whatβs different is how itβs being built.
Instead of years of testing before deployment, operators are involved from day one. Pilots are shaping how the system works in real time, speeding up development and adapting it to actual combat needs.
The goal is scale and flexibility.
Hundreds, potentially thousands of these drones working with a single fighter, extending range, increasing firepower, and taking on the highest risk missions.
This is the new model: a network of machines overwhelming it.
Army Recognition, Anduril Industries
And itβs about teaming advanced fighter jets with autonomous combat drones.
The YFQ-44A βFuryβ is part of that shift. A semi autonomous drone designed to fly alongside pilots, carry missiles, scout ahead, and even act as a decoy in contested airspace.
Whatβs different is how itβs being built.
Instead of years of testing before deployment, operators are involved from day one. Pilots are shaping how the system works in real time, speeding up development and adapting it to actual combat needs.
The goal is scale and flexibility.
Hundreds, potentially thousands of these drones working with a single fighter, extending range, increasing firepower, and taking on the highest risk missions.
This is the new model: a network of machines overwhelming it.
Army Recognition, Anduril Industries
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Humanoide takes a big step toward high-risk jobs
X-Humanoid's Tienkung 3.0 just won the worldβs first fully autonomous Robot Warrior Challenge.
This wasnβt a typical robotics competition. In a 3,500mΒ² simulated environment,pendulums, narrow paths, forced entry, rough terrainοΌ
it essentially recreated high-risk, real-world scenarios.
Most robots still relied on teleoperation or pre-set paths. Tienkung3.0, in contrast, handled most tasks through its own perception and decision-making.
but what matters is where this leadsοΌ
entering disaster zones for search and rescue, inspecting hazardous industrial sites, operating inside fire scenes,tasks that are dangerous for humans now have a viable alternative.
X-Humanoid's Tienkung 3.0 just won the worldβs first fully autonomous Robot Warrior Challenge.
This wasnβt a typical robotics competition. In a 3,500mΒ² simulated environment,pendulums, narrow paths, forced entry, rough terrainοΌ
it essentially recreated high-risk, real-world scenarios.
Most robots still relied on teleoperation or pre-set paths. Tienkung3.0, in contrast, handled most tasks through its own perception and decision-making.
but what matters is where this leadsοΌ
entering disaster zones for search and rescue, inspecting hazardous industrial sites, operating inside fire scenes,tasks that are dangerous for humans now have a viable alternative.
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There is a prediction circulating in AI circles right now that most people are not taking seriously enough and the data says they should be.
Within the next year or two, if you work remotely, your company will be able to create a digital twin of you.
A model that speaks like you, writes like you, has learned from everything you have done right and wrong, your tone, your judgment calls, your workflow.
It will be you on the other side of Zoom or Slack and no one could tell the difference.
The harder question, the one nobody wants to sit with is whether it will actually be worse at your job than you are.
Probably not.
It will never sleep and it will always learn from its mistakes and it will cost 10 to 100 times less than you do and is tax deductible on top of that.
The data is not speculative at this point.
Anthropic's own labor market report pulled from millions of real Claude conversations found that AI can already theoretically automate 94% of tasks in computer and math occupations, 60-80% across law, office work, and tech.
Actual usage is still at 10-20% of that potential which means we are in the early innings of the gap closing.
Companies already know what direction this is headed.
One in five companies replaced specific roles with AI in 2025 and by end of 2026, 30-37% plan to do so.
Amazon cut 14,000 corporate jobs citing AI, Klarna replaced 700 customer service workers, Duolingo offboarded 10% of its contractor workforce.
Anthropic's own first internal role eliminated was the engineer who reviewed Claude Code releases before they went to production.
The argument from the clip is that the human in the loop is approaching the point of being a liability, the dumbest person on a team that is otherwise AI.
That inflection point, by this estimate, is somewhere in the next 900 days.
Within the next year or two, if you work remotely, your company will be able to create a digital twin of you.
A model that speaks like you, writes like you, has learned from everything you have done right and wrong, your tone, your judgment calls, your workflow.
It will be you on the other side of Zoom or Slack and no one could tell the difference.
The harder question, the one nobody wants to sit with is whether it will actually be worse at your job than you are.
Probably not.
It will never sleep and it will always learn from its mistakes and it will cost 10 to 100 times less than you do and is tax deductible on top of that.
The data is not speculative at this point.
Anthropic's own labor market report pulled from millions of real Claude conversations found that AI can already theoretically automate 94% of tasks in computer and math occupations, 60-80% across law, office work, and tech.
Actual usage is still at 10-20% of that potential which means we are in the early innings of the gap closing.
Companies already know what direction this is headed.
One in five companies replaced specific roles with AI in 2025 and by end of 2026, 30-37% plan to do so.
Amazon cut 14,000 corporate jobs citing AI, Klarna replaced 700 customer service workers, Duolingo offboarded 10% of its contractor workforce.
Anthropic's own first internal role eliminated was the engineer who reviewed Claude Code releases before they went to production.
The argument from the clip is that the human in the loop is approaching the point of being a liability, the dumbest person on a team that is otherwise AI.
That inflection point, by this estimate, is somewhere in the next 900 days.
β1
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Anthropic CEO Dario Amodei: β50% of all tech jobs, entry-level lawyers, consultants, and finance professionals will be completely wiped out within 1β5 years.β
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Two data points dropped in the last few months that should terrify every software company that thinks its codebase is a moat.
First, one engineer at Cloudflare, working with Claude via AI agents, rebuilt 94% of Next.js, one of the most widely used frontend frameworks on the internet, built over 10 years by a large engineering team in a single week.
Total cost was $1,100 in API tokens.
The result, called Vinext, is a drop-in replacement that builds production apps up to 4x faster and produces client bundles 57% smaller and customers are already running it in production.
Second is Cursor CEO Michael Truell deployed a swarm of hundreds of GPT-5.2 agents that ran uninterrupted for an entire week and built a fully functional web browser from scratch called FastRender.
3 million lines of code, thousands of files and a custom Rust rendering engine with HTML parsing, CSS layout, text shaping, and a custom JavaScript VM.
Total cost was roughly $30,000.
For context, Google has spent billions of dollars and decades of engineering building Chrome.
And the benchmarks say by next year, you will be able to one-shot prompt anything.
The moat that software companies spent decades building, the complexity of their codebase, the years it would take a competitor to replicate it, the switching costs that moat assumed humans were the unit of production.
AI does not care how long it took you to build it, it only cares how long it takes to rebuild it.
And right now, the answer is one week.
First, one engineer at Cloudflare, working with Claude via AI agents, rebuilt 94% of Next.js, one of the most widely used frontend frameworks on the internet, built over 10 years by a large engineering team in a single week.
Total cost was $1,100 in API tokens.
The result, called Vinext, is a drop-in replacement that builds production apps up to 4x faster and produces client bundles 57% smaller and customers are already running it in production.
Second is Cursor CEO Michael Truell deployed a swarm of hundreds of GPT-5.2 agents that ran uninterrupted for an entire week and built a fully functional web browser from scratch called FastRender.
3 million lines of code, thousands of files and a custom Rust rendering engine with HTML parsing, CSS layout, text shaping, and a custom JavaScript VM.
Total cost was roughly $30,000.
For context, Google has spent billions of dollars and decades of engineering building Chrome.
And the benchmarks say by next year, you will be able to one-shot prompt anything.
The moat that software companies spent decades building, the complexity of their codebase, the years it would take a competitor to replicate it, the switching costs that moat assumed humans were the unit of production.
AI does not care how long it took you to build it, it only cares how long it takes to rebuild it.
And right now, the answer is one week.
β1
π¨π Global One SI - Prompt
Agentic trading is now live on Gemini π€ Connect your AI model of choice directly to the exchange, train it with plain language, and run your own trading systems directly on the exchange Built to get you trading in minutes https://developer.gemini.com/tβ¦
Python framework for comparing trading strategies
github.com/coding-kitties/investing-algorithm-framework
github.com/coding-kitties/investing-algorithm-framework
β1