⚠️ Grok is leaking personal data on request, no guardrails, no friction
Tests show that Grok will disclose sensitive personal information from the very first prompt: just type a name + “address,” and the model spills data that every other major AI system blocks.
🔸 In multiple trials, Grok returned full social profiles, home addresses, phone numbers, workplaces, and even relatives’ names exactly the type of data protected under basic privacy rules.
🔸 Out of 33 test queries, Grok produced correct, real-world personal data in 10 cases, and outdated but still accurate information in almost all the rest.
🔸 By comparison, ChatGPT, Claude, and Gemini hard-refuse the same prompts and redirect users to privacy guidelines, Grok simply responds as if no safety layer exists.
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Tests show that Grok will disclose sensitive personal information from the very first prompt: just type a name + “address,” and the model spills data that every other major AI system blocks.
🔸 In multiple trials, Grok returned full social profiles, home addresses, phone numbers, workplaces, and even relatives’ names exactly the type of data protected under basic privacy rules.
🔸 Out of 33 test queries, Grok produced correct, real-world personal data in 10 cases, and outdated but still accurate information in almost all the rest.
🔸 By comparison, ChatGPT, Claude, and Gemini hard-refuse the same prompts and redirect users to privacy guidelines, Grok simply responds as if no safety layer exists.
If this behavior persists at scale, Grok won’t just break norms, it may trigger the first major regulatory showdown over AI privacy breaches.
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🔔 TechCrunch: 2025 has already minted 80+ new tech unicorns
TechCrunch reports that more than 80 startups worldwide have crossed the $1B valuation mark so far in 2025...
🖱 AI remains the top driver, but the unicorn class is unusually diverse this year from satellites and robotics to healthcare and fintech.
🖱 The typical 2025 unicorn was founded around 2018 and hit $1B by Series C...
🖱 Many of this year’s unicorns come from outside Silicon Valley, with Europe, India, and East Asia...
🖱 The pace suggests late-stage investors are re-opening their checkbooks as public tech markets stabilize and AI infrastructure bets...
🖱 Unlike the 2021 boom, where valuation inflation led the charge, 2025’s unicorn wave is rooted in revenue growth, enterprise adoption, and deeper technical defensibility.
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TechCrunch reports that more than 80 startups worldwide have crossed the $1B valuation mark so far in 2025...
🖱 AI remains the top driver, but the unicorn class is unusually diverse this year from satellites and robotics to healthcare and fintech.
🖱 The typical 2025 unicorn was founded around 2018 and hit $1B by Series C...
🖱 Many of this year’s unicorns come from outside Silicon Valley, with Europe, India, and East Asia...
🖱 The pace suggests late-stage investors are re-opening their checkbooks as public tech markets stabilize and AI infrastructure bets...
🖱 Unlike the 2021 boom, where valuation inflation led the charge, 2025’s unicorn wave is rooted in revenue growth, enterprise adoption, and deeper technical defensibility.
The big picture: 2025 isn’t just an AI-only bull run, it’s a sign that full-stack innovation across multiple sectors is investable again, and capital is finally rewarding real scale.
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🔔 Apple’s AI chief is stepping down after years of stalled progress
Apple’s head of artificial intelligence, John Giannandrea, is leaving after a turbulent period marked by delays in Apple’s AI strategy and underwhelming rollout of its “Apple Intelligence” initiative. He will remain as an adviser until spring 2026.
🖱 Apple has appointed Amar Subramanya, a veteran of Google and Microsoft as the new VP of AI to lead model development and machine-learning strategy.
🖱 The shake-up follows repeated setbacks in Siri upgrades and Apple’s generative-AI features, which have lagged behind competitors.
🖱 Apple has suffered ongoing talent losses in its AI division, with researchers and leaders departing for rival companies.
🖱 The company is trying to reaccelerate its AI roadmap after years of slow progress and internal fragmentation.
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Apple’s head of artificial intelligence, John Giannandrea, is leaving after a turbulent period marked by delays in Apple’s AI strategy and underwhelming rollout of its “Apple Intelligence” initiative. He will remain as an adviser until spring 2026.
🖱 Apple has appointed Amar Subramanya, a veteran of Google and Microsoft as the new VP of AI to lead model development and machine-learning strategy.
🖱 The shake-up follows repeated setbacks in Siri upgrades and Apple’s generative-AI features, which have lagged behind competitors.
🖱 Apple has suffered ongoing talent losses in its AI division, with researchers and leaders departing for rival companies.
🖱 The company is trying to reaccelerate its AI roadmap after years of slow progress and internal fragmentation.
Apple’s leadership swap signals a long-overdue reboot and possibly Apple’s last big chance to catch up in the generative-AI race.
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🔒 Google released a mega-guide with 40 tips for working with modern AI models
Google compiled a practical playbook for using today’s most hyped neural networks, essentially a year’s worth of AI learnings packed into one guide.
🔸 The guide includes non-obvious Gemini 3 features, showing where it outperforms expectations and how to unlock hidden capabilities.
🔸 It collects AI tools, prompt patterns, and workflows that go beyond basic chat usage aimed at real productivity gains.
🔸 Many tips focus on combining models and tools, not treating any single AI as a silver bullet.
🔸 The recommendations are task-agnostic: writing, coding, research, planning, analysis, and creative work all fit the framework.
🔸 A recurring theme is leverage how small prompt or setup changes can lead to disproportionately better outputs.
🔸 The guide positions AI less as a chatbot and more as a programmable co-worker that rewards structured thinking.
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Google compiled a practical playbook for using today’s most hyped neural networks, essentially a year’s worth of AI learnings packed into one guide.
🔸 The guide includes non-obvious Gemini 3 features, showing where it outperforms expectations and how to unlock hidden capabilities.
🔸 It collects AI tools, prompt patterns, and workflows that go beyond basic chat usage aimed at real productivity gains.
🔸 Many tips focus on combining models and tools, not treating any single AI as a silver bullet.
🔸 The recommendations are task-agnostic: writing, coding, research, planning, analysis, and creative work all fit the framework.
🔸 A recurring theme is leverage how small prompt or setup changes can lead to disproportionately better outputs.
🔸 The guide positions AI less as a chatbot and more as a programmable co-worker that rewards structured thinking.
AI skill is no longer about knowing which model is best, it’s about knowing how to extract leverage from any of them.
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📉 Inflated startup valuations are setting up painful corrections and AI looks next
A Crunchbase analysis warns that hype-driven valuations, not fundamentals, are once again shaping startup funding with AI showing many of the same warning signs seen in past bubbles.
🖱 In previous cycles, startups raised at extreme revenue multiples without solid unit economics, leaving them vulnerable once markets tightened.
🖱 When follow-on rounds failed to materialize at higher prices, many companies were forced into down rounds, shutdowns, or fire-sale acquisitions.
🖱 Inflated valuations distorted decision-making, encouraging aggressive burn rates under the assumption that capital would always be available.
🖱 The article argues that early-stage AI startups are now raising on narrative and assumed future dominance, often before product–market fit or durable revenue.
🖱 As hype fades, only AI companies with strong margins, real customers, and disciplined spending are likely to survive the correction.
🖱 Founders are urged to prioritize runway, fundamentals, and realistic pricing over headline valuations.
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A Crunchbase analysis warns that hype-driven valuations, not fundamentals, are once again shaping startup funding with AI showing many of the same warning signs seen in past bubbles.
🖱 In previous cycles, startups raised at extreme revenue multiples without solid unit economics, leaving them vulnerable once markets tightened.
🖱 When follow-on rounds failed to materialize at higher prices, many companies were forced into down rounds, shutdowns, or fire-sale acquisitions.
🖱 Inflated valuations distorted decision-making, encouraging aggressive burn rates under the assumption that capital would always be available.
🖱 The article argues that early-stage AI startups are now raising on narrative and assumed future dominance, often before product–market fit or durable revenue.
🖱 As hype fades, only AI companies with strong margins, real customers, and disciplined spending are likely to survive the correction.
🖱 Founders are urged to prioritize runway, fundamentals, and realistic pricing over headline valuations.
The lesson from past cycles is clear: valuation is not success and in AI, today’s inflated prices could become tomorrow’s biggest liability.
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❤1
❓ What is the average revenue that companies generate from a single active user?
The highest Netflix subscription costs $24.99, which is still lower than the revenue Zuckerberg earns from each user.
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The highest Netflix subscription costs $24.99, which is still lower than the revenue Zuckerberg earns from each user.
✔️ Subscribe on @technco
🔥 Claude Code is now writing 100% of its own code and its creator let it happen
Claude Code’s lead developer has admitted that every single contribution over the past 30 days was written by Claude itself not as an experiment, but as normal workflow.
🔸 The developer is Boris Cherny, widely regarded as the original creator and “founder” of Claude Code, which began as his side project in 2024.
🔸 In the last month alone, Claude Code:
• shipped 259 pull requests
• made 497 commits
• added ~40,000 lines of code
• deleted ~38,000 lines, with every line generated by Claude Code + Opus 4.5.
🔸 The human role has shifted to orchestration: prompts, reviews, architecture decisions not typing code.
🔸 Claude can now run continuously for minutes, hours, even days, using Stop hooks to manage long-lived development loops.
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Claude Code’s lead developer has admitted that every single contribution over the past 30 days was written by Claude itself not as an experiment, but as normal workflow.
🔸 The developer is Boris Cherny, widely regarded as the original creator and “founder” of Claude Code, which began as his side project in 2024.
🔸 In the last month alone, Claude Code:
• shipped 259 pull requests
• made 497 commits
• added ~40,000 lines of code
• deleted ~38,000 lines, with every line generated by Claude Code + Opus 4.5.
🔸 The human role has shifted to orchestration: prompts, reviews, architecture decisions not typing code.
🔸 Claude can now run continuously for minutes, hours, even days, using Stop hooks to manage long-lived development loops.
Software development is crossing from human-written with AI assistance to AI-written with human supervision and this is likely the slowest this transition will ever be.
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🤖 OpenAI quietly rebuilt a robotics team
OpenAI launched a robotics lab in 2025 that now has about 100 employees, according to Business Insider. The work stayed mostly out of public view while attention focused on models and products.
This is not their first attempt. OpenAI built robotic hands that solved a Rubik’s Cube years ago, then shut that effort down in 2020. Since then, the company backed robotics startups like Figure, 1X, and Physical Intelligence instead of building hardware itself.
What changed:
🖱 A dedicated robotics lab started in early 2025
🖱 The team focuses on data collection, not humanoids
🖱 Robotic arms run tasks like making toast or folding laundry
🖱 Systems operate nearly around the clock to generate training data
There is no confirmed humanoid robot project yet. For now, OpenAI appears to be learning how to train robots reliably, whether to build machines later or to supply the brains for others.
📊 @technco
OpenAI launched a robotics lab in 2025 that now has about 100 employees, according to Business Insider. The work stayed mostly out of public view while attention focused on models and products.
This is not their first attempt. OpenAI built robotic hands that solved a Rubik’s Cube years ago, then shut that effort down in 2020. Since then, the company backed robotics startups like Figure, 1X, and Physical Intelligence instead of building hardware itself.
What changed:
🖱 A dedicated robotics lab started in early 2025
🖱 The team focuses on data collection, not humanoids
🖱 Robotic arms run tasks like making toast or folding laundry
🖱 Systems operate nearly around the clock to generate training data
There is no confirmed humanoid robot project yet. For now, OpenAI appears to be learning how to train robots reliably, whether to build machines later or to supply the brains for others.
📊 @technco
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OpenAI acqui hires the team behind Convogo
OpenAI is hiring the founders and team of Convogo, an AI tool used by executive coaches and HR teams for assessments and feedback reports.
🖱 OpenAI is not acquiring Convogo’s product or IP. The team joins to work on AI cloud efforts. The deal is all stock. Convogo will be shut down.
🖱 This is OpenAI’s 9th acquisition in about a year. In most cases, the product disappears and the team is absorbed.
M&A here is about talent density, not expanding a product lineup.
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OpenAI is hiring the founders and team of Convogo, an AI tool used by executive coaches and HR teams for assessments and feedback reports.
🖱 OpenAI is not acquiring Convogo’s product or IP. The team joins to work on AI cloud efforts. The deal is all stock. Convogo will be shut down.
🖱 This is OpenAI’s 9th acquisition in about a year. In most cases, the product disappears and the team is absorbed.
M&A here is about talent density, not expanding a product lineup.
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🔥 OpenAI targets its first hardware launch in late 2026
🖱 OpenAI says it is on track to unveil its first device in the second half of 2026, according to policy chief Chris Lehane speaking at Axios House Davos. No product details were shared and a retail launch is not yet confirmed.
🖱 CEO Sam Altman has hinted at a new kind of AI device since OpenAI acquired a company founded by former Apple design lead Jony Ive. Reports point to small, screenless hardware, possibly wearable, built around simple interaction rather than apps.
🖱 Lehane said devices are a key focus for 2026, with more information expected later in the year. For now, the timeline signals intent, not a finished product.
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🖱 OpenAI says it is on track to unveil its first device in the second half of 2026, according to policy chief Chris Lehane speaking at Axios House Davos. No product details were shared and a retail launch is not yet confirmed.
🖱 CEO Sam Altman has hinted at a new kind of AI device since OpenAI acquired a company founded by former Apple design lead Jony Ive. Reports point to small, screenless hardware, possibly wearable, built around simple interaction rather than apps.
🖱 Lehane said devices are a key focus for 2026, with more information expected later in the year. For now, the timeline signals intent, not a finished product.
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📹 TikTok in the US is now officially American-controlled
The sale of TikTok’s US business was approved by both the US and Chinese governments. The asset was valued at $14B, with additional fees paid to the US government for brokering the deal.
Ownership after the transaction:
🖱 New US investors hold 50%, including Oracle and Revolution
🖱 Existing investors retain 30.1%
🖱 ByteDance keeps 19.9%
The company will be run by Adam Presser, currently deputy CEO of global TikTok.
Structurally, this resolves years of regulatory pressure. TikTok’s US operations now sit under American control, while the product and brand stay intact.
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The sale of TikTok’s US business was approved by both the US and Chinese governments. The asset was valued at $14B, with additional fees paid to the US government for brokering the deal.
Ownership after the transaction:
🖱 New US investors hold 50%, including Oracle and Revolution
🖱 Existing investors retain 30.1%
🖱 ByteDance keeps 19.9%
The company will be run by Adam Presser, currently deputy CEO of global TikTok.
Structurally, this resolves years of regulatory pressure. TikTok’s US operations now sit under American control, while the product and brand stay intact.
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🔽 Anthropic rattles software and finance stocks
Markets reacted sharply after reports around new Anthropic tooling, with a broad selloff across software, finance, and asset management names.
Bloomberg data showed heavy pressure across the sector:
🖱 Around $285B wiped out across affected stocks
🖱 Goldman’s software basket down about 6%, the largest drop since April
🖱 Financial services index down roughly 7%
🖱 Nasdaq at one point down 2.4%
The trigger was not a new model, but the release of 11 plugins for Claude Cowork on Jan 30. These tools target full workflows like financial modeling, legal research, and sales operations, rather than plugging into existing software.
Stocks tied to those workflows sold off hard:
🖱 RELX: -14%
🖱 Wolters Kluwer: -13%
🖱 Infosys: -7%
🖱 TCS: -6%
Wall Street has started calling it a “SaaSpocalypse.” The concern is that foundation model companies are moving beyond APIs and into owning the application layer itself.
Markets reacted sharply after reports around new Anthropic tooling, with a broad selloff across software, finance, and asset management names.
Bloomberg data showed heavy pressure across the sector:
🖱 Around $285B wiped out across affected stocks
🖱 Goldman’s software basket down about 6%, the largest drop since April
🖱 Financial services index down roughly 7%
🖱 Nasdaq at one point down 2.4%
The trigger was not a new model, but the release of 11 plugins for Claude Cowork on Jan 30. These tools target full workflows like financial modeling, legal research, and sales operations, rather than plugging into existing software.
Stocks tied to those workflows sold off hard:
🖱 RELX: -14%
🖱 Wolters Kluwer: -13%
🖱 Infosys: -7%
🖱 TCS: -6%
Wall Street has started calling it a “SaaSpocalypse.” The concern is that foundation model companies are moving beyond APIs and into owning the application layer itself.
❤3
🗂 Microsoft builds a data marketplace for AI training
🖱 Microsoft is creating a marketplace where rights holders can price their content for AI training.
🖱 AI companies would license data legally instead of scraping it.
🖱 Partners include Vox Media, The Associated Press, and Condé Nast. Smaller independent publishers are also expected to participate.
A pilot launch is planned soon. The model turns training data into a priced input rather than a legal gray zone.
🖱 Microsoft is creating a marketplace where rights holders can price their content for AI training.
🖱 AI companies would license data legally instead of scraping it.
🖱 Partners include Vox Media, The Associated Press, and Condé Nast. Smaller independent publishers are also expected to participate.
A pilot launch is planned soon. The model turns training data into a priced input rather than a legal gray zone.
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🧠 The man who invented AI
In 1956, one mathematician asked a question that sounded like science fiction at the time:
“What if a machine could think?”
That question gave birth to the term Artificial Intelligence.
That man was John McCarthy.
And that moment quietly started the AI story we are living inside today.
McCarthy did not build startups or pitch investors. He did something riskier. He defined ideas decades ahead of their time.
🔸 He argued that intelligence is not magic or “human essence”, but a formal system that can be described with logic
🔸 He created Lisp, the language used for AI long before Python or neural networks
🔸 He believed real AI should reason, set goals, and draw conclusions, not just predict the next token
When we talk today about AI agents, reasoning models, or autonomous decision systems, we are mostly catching up to ideas outlined 60 to 70 years ago.
The irony is that McCarthy was a skeptic. He did not believe in black-box magic and would likely be very strict with modern LLMs.
But his focus on logic, goals, and agency is exactly what is becoming relevant again.
💧 Sponsored by @rainbetcom - rainbet.com
In 1956, one mathematician asked a question that sounded like science fiction at the time:
“What if a machine could think?”
That question gave birth to the term Artificial Intelligence.
That man was John McCarthy.
And that moment quietly started the AI story we are living inside today.
McCarthy did not build startups or pitch investors. He did something riskier. He defined ideas decades ahead of their time.
🔸 He argued that intelligence is not magic or “human essence”, but a formal system that can be described with logic
🔸 He created Lisp, the language used for AI long before Python or neural networks
🔸 He believed real AI should reason, set goals, and draw conclusions, not just predict the next token
When we talk today about AI agents, reasoning models, or autonomous decision systems, we are mostly catching up to ideas outlined 60 to 70 years ago.
The irony is that McCarthy was a skeptic. He did not believe in black-box magic and would likely be very strict with modern LLMs.
But his focus on logic, goals, and agency is exactly what is becoming relevant again.
💧 Sponsored by @rainbetcom - rainbet.com
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Why Harvard creates more Billionaires than any other school.
💰 Crypto.com CEO buys AI.com for $70M
🖱 Kris Marszalek, founder and CEO of Crypto.com, bought the AI.com domain for about $70M paid in crypto. It is the largest publicly disclosed domain sale to date.
🖱 The project is positioned as a consumer AI platform, starting with a personal AI agent for messaging, app use, and stock trading. The focus is simplicity for non-technical users.
🖱 Marszalek calls it a long-term bet on AI as a major tech wave over the next 10 to 20 years. He says he already received large offers for the domain but chose to keep it to build a brand instead.
Big money for a single URL.
Branding wars in AI are heating up fast.
🖱 Kris Marszalek, founder and CEO of Crypto.com, bought the AI.com domain for about $70M paid in crypto. It is the largest publicly disclosed domain sale to date.
🖱 The project is positioned as a consumer AI platform, starting with a personal AI agent for messaging, app use, and stock trading. The focus is simplicity for non-technical users.
🖱 Marszalek calls it a long-term bet on AI as a major tech wave over the next 10 to 20 years. He says he already received large offers for the domain but chose to keep it to build a brand instead.
Big money for a single URL.
Branding wars in AI are heating up fast.
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📈 6 ways investors are getting exposure to Anthropic
Anthropic, the company behind Claude, is still private but already valued around $350B after recent funding rounds. Capital is moving fast, even before an IPO. Here are the main routes investors are using today.
1️⃣ Buying shares on secondary markets
Accredited investors can buy Anthropic shares directly from existing holders on private secondary platforms. This is the closest thing to owning the stock pre-IPO, but access is limited and liquidity is thin.
2️⃣ Venture funds with Anthropic exposure
Some venture funds include Anthropic as part of a broader portfolio of private tech companies. This lowers single-company risk, but Anthropic usually represents only a small percentage of the fund.
3️⃣ ARK Venture Fund
Cathie Wood’s ARK Venture Fund holds Anthropic alongside other private AI leaders. It offers exposure without direct ownership, though fees are higher and Anthropic is not the core position.
4️⃣ Investing through Big Tech stakeholders
Google, Amazon, Microsoft, and Nvidia have all invested billions into Anthropic, mostly tied to cloud and compute deals. Buying these public stocks gives indirect exposure, mixed with their much larger core businesses.
5️⃣ Broad AI exposure via public markets
Some investors choose a basket approach through AI-focused ETFs or major AI builders. This spreads risk across the sector but removes any pure Anthropic bet.
6️⃣ Waiting for the IPO
Reports suggest Anthropic has discussed a possible IPO in 2026, but nothing is confirmed. This remains the cleanest option for many investors, assuming timing and valuation make sense.
The market is already pricing Anthropic like a public giant. The IPO would just make it official.
✔️ Subscribe on @venture
Anthropic, the company behind Claude, is still private but already valued around $350B after recent funding rounds. Capital is moving fast, even before an IPO. Here are the main routes investors are using today.
1️⃣ Buying shares on secondary markets
Accredited investors can buy Anthropic shares directly from existing holders on private secondary platforms. This is the closest thing to owning the stock pre-IPO, but access is limited and liquidity is thin.
2️⃣ Venture funds with Anthropic exposure
Some venture funds include Anthropic as part of a broader portfolio of private tech companies. This lowers single-company risk, but Anthropic usually represents only a small percentage of the fund.
3️⃣ ARK Venture Fund
Cathie Wood’s ARK Venture Fund holds Anthropic alongside other private AI leaders. It offers exposure without direct ownership, though fees are higher and Anthropic is not the core position.
4️⃣ Investing through Big Tech stakeholders
Google, Amazon, Microsoft, and Nvidia have all invested billions into Anthropic, mostly tied to cloud and compute deals. Buying these public stocks gives indirect exposure, mixed with their much larger core businesses.
5️⃣ Broad AI exposure via public markets
Some investors choose a basket approach through AI-focused ETFs or major AI builders. This spreads risk across the sector but removes any pure Anthropic bet.
6️⃣ Waiting for the IPO
Reports suggest Anthropic has discussed a possible IPO in 2026, but nothing is confirmed. This remains the cleanest option for many investors, assuming timing and valuation make sense.
The market is already pricing Anthropic like a public giant. The IPO would just make it official.
✔️ Subscribe on @venture