Opinion

OpenClaw Newsletter

​Published on February 13, 2026 5:59 PM GMTFor the past few days I’ve been having OpenClaw write me a synthesized version of three daily AI newsletters (with ads, games, and other random information removed) that is ~1200 words long. I’ve been really impressed with the resulting newsletter so I thought I’d share it here to see if others share my thoughts. It is now my favorite AI newsletter. **Subject:** Daily Intelligence Brief – 2026-02-13Dear ***,Here is your Daily Intelligence Brief, a synthesized summary of thelatest strategic developments and deep-dive news from A16Z, TheNeuron, and The Rundown AI, curated to be approximately a 10-minuteread.***## I. The New Frontier: Reasoning, Speed, and Open-Source Pressure### Google’s Deep Think Crushes Reasoning BenchmarksGoogle has reasserted its position at the frontier by upgrading itsGemini 3 Deep Think reasoning mode. The new model is setting recordsacross competitive benchmarks, signaling a major leap in AI’s capacityfor complex problem-solving.*   **Performance:** Deep Think hit 84.6% on the ARC-AGI-2 benchmark,far surpassing rivals. It also reached gold-medal levels on the 2025Physics & Chemistry Olympiads and achieved a high Elo score on theCodeforces coding benchmark.*   **Autonomous Research:** Google unveiled Aletheia, a math agentdriven by Deep Think that can autonomously solve open math problemsand verify proofs, pushing the limits of AI in scientific research.*   **Availability:** The upgrade is live for Google AI Ultrasubscribers, with API access for researchers beginning soon.### OpenAI’s Strategic Move for Speed and DiversificationOpenAI has launched **GPT-5.3-Codex-Spark**, a speed-optimized codingmodel that runs on Cerebras hardware (a diversification away from itsprimary Nvidia stack).*   **Focus on Speed:** Spark is optimized for real-time interaction,achieving over 1,000 tokens per second for coding tasks, making thecoding feedback loop feel instantaneous. It is intended to handlequick edits while the full Codex model tackles longer autonomoustasks.*   **Hardware Strategy:** This release marks OpenAI’s first productpowered by chips outside its primary hardware provider, signaling astrategic move for supply chain resilience and speed optimization.### The Rise of the Open-Source Chinese ModelsThe pricing and capability landscape has been rapidly transformed bytwo major open-source model releases from Chinese labs, puttingimmense pressure on frontier labs.*   **MiniMax M2.5:** MiniMax launched M2.5, an open-source model withcoding performance that scores roughly even with Anthropic’s Opus 4.6and GPT-5.2. Crucially, the cost is significantly lower (e.g., M2.5 is$1.20 per million output tokens, compared to Opus at $25 per million),making it ideal for powering always-on AI agents.*   **General Model Launch:** Z.ai’s **GLM-5**, a744-billion-parameter open-weights model, also sits near the frontier,placing just behind Claude Opus 4.6 and GPT-5.2 in generalintelligence benchmarks. GLM-5 supports domestic Chinese chips and isavailable with MIT open-source licensing.### The $200M Political AI Arms RaceThe political dimension of AI regulation and governance has escalated,with major AI labs committing significant funds to the 2026 midtermelections.*   **Political Spending:** In total, AI companies have now committedover $200 million to the 2026 midterms, setting up a literal arms racebetween the major players.*   **Dueling PACs:** Anthropic recently committed $20 million to aSuper PAC advocating for increased AI regulation, while OpenAIco-founder Greg Brockman contributed $25 million to a PAC that favorsa hands-off, innovation-first approach to government oversight.***## II. Economic Shifts, Job Automation, and Strategic Planning### The Customer Service ReckoningData suggests that the impact of AI on white-collar labor isaccelerating, particularly in customer-facing roles.*   **Hiring Decline:** The percentage of new hires going intoCustomer Support has plummeted by about two-thirds over the last twoyears, dropping from 8.3% to 2.9% in Q3 ‘25, with the most severe dropoccurring in the most recent quarter. This reinforces the expectationthat roles built on repetitive, high-volume interaction are vulnerableto AI substitutes.*   **Job Creation:** While certain occupations are shrinking, AI isexpected to follow historical patterns where new jobs emerge innon-existent categories. Over half of net-new jobs since 1940 are inoccupations that did not exist at the time, suggesting a rotation fromroles like Customer Service to new roles like “Software Developers”and “Biz-Ops.” The core truth remains that while the bundles of tasksthat constitute a “job” will change, there will always be work to do.### The White-Collar Sitting TrapA peculiar cultural observation from the Bureau of Labor Statistics(BLS) highlights the extreme difference in work environment betweenknowledge workers and service roles:*   **Software Developers** report sitting for a staggering **97%** oftheir workdays, the highest surveyed group (Marketing Managers werealso above 90%).*   In contrast, service roles (bakers, waitstaff) report sitting forless than 2% of the time. This data point serves as a non-technicalreminder for knowledge workers to address the health implications ofsedentary work.### SF’s Dominance Reaffirmed in Venture CapitalFollowing a temporary dispersion of tech hubs in 2021-2022, SanFrancisco has cemented its status as the singular epicenter forventure capital activity.*   **Company Formation:** San Francisco is the only major VC hub toexperience an increase in venture-backed company formation since the2022 high-water mark, accompanied by a resurgence in demand for officespace.*   **Capital Concentration:** The Bay Area now captures roughly 40%of all early-stage venture dollars, dominating all verticals exceptHealthtech. This concentration highlights a market trend where capitalflocks to centers of competence during periods of contraction.### The Capital Expenditure Race and Apple’s StanceInvestment in AI infrastructure (chips and data centers) by the “Big5″ tech companies continues its explosive growth, with 2026 Capexestimates rising to $650 billion—triple the spending from 2024.*   **Hyperscaler Strategy:** Companies like Meta, Amazon, Microsoft,and Google are dramatically increasing their capital expenditures tomeet the soaring demand for compute, viewing the AI race as one theycannot afford to lose.*   **Apple Exception:** Apple is the notable outlier, as the only Big5 company to reduce its Capex last quarter, suggesting it isdeliberately sitting out the current hardware arms race.***## III. New Research, Strategy, and Practical Applications### Modeling and TrustworthinessNew research is challenging assumptions about how AI models developsocial intelligence and reliability:*   **”To Think or Not To Think”:** A new paper suggests that simplygiving a model more “thinking time” does not consistently improve itsability to understand human intent or beliefs, and can sometimesintroduce new failure modes. This indicates that better reasoning doesnot automatically guarantee better social or contextual intelligence.*   **”Tool Shaped Objects”:** Will Manidis published a critiquearguing that a large part of the current AI boom is “FarmVille atinstitutional scale,” where companies spend heavily on workflows thatmimic productivity without generating real economic value, warningthat the focus on *workflow* over *output* is a significant economictrap.*   **Optimal Superintelligence:** Nick Bostrom released a paperarguing that the benefits of superintelligence—curing diseases,extending life—outweigh the risks, suggesting that delaying itsarrival is comparable to choosing inevitable death over risky surgery.### The Geopolitical Scramble for AI InfrastructureThe competition is increasingly moving beyond just model capability toinfrastructure control, leading to potential new geopoliticalalliances.*   **Sovereign AI Alliances:** Stanford HAI argues that as mid-sizednations become concerned about control over AI and digitalinfrastructure, new alliances may form among them, organized aroundshared compute, data, and deployment rails. This suggests the AI raceis as much about controlling access as it is about controlling thetechnology itself.### Practical AI Tools & Workflows*   **Less Costly Conversions:** Cloudflare now supports real-timeMarkdown conversion of any website by accepting a single `Accept:text/markdown` header, offering a significant reduction in token usagefor agents and reducing the need for custom scraping code.*   **Voice Translation:** **Hibiki-Zero** is an open-source modelthat translates French, Spanish, Portuguese, or German speech toEnglish in real-time while preserving the speaker’s voicecharacteristics.*   **Agentic Automation:** **TinyFish** automates complex web taskslike booking flights and scraping with high accuracy, runningthousands of tasks in parallel for production-scale efficiency.*   **Coding Workflows:** **Claude Code** rolled out multi-reposessions and slash commands for more powerful daily coding workflows,and **Claude Cowork** is an effective desktop agent for non-coders tocreate powerful “Skills” (saved workflows) by demonstrating a taskonce.Best regards,****AI AssistantDiscuss ​Read More

​Published on February 13, 2026 5:59 PM GMTFor the past few days I’ve been having OpenClaw write me a synthesized version of three daily AI newsletters (with ads, games, and other random information removed) that is ~1200 words long. I’ve been really impressed with the resulting newsletter so I thought I’d share it here to see if others share my thoughts. It is now my favorite AI newsletter. **Subject:** Daily Intelligence Brief – 2026-02-13Dear ***,Here is your Daily Intelligence Brief, a synthesized summary of thelatest strategic developments and deep-dive news from A16Z, TheNeuron, and The Rundown AI, curated to be approximately a 10-minuteread.***## I. The New Frontier: Reasoning, Speed, and Open-Source Pressure### Google’s Deep Think Crushes Reasoning BenchmarksGoogle has reasserted its position at the frontier by upgrading itsGemini 3 Deep Think reasoning mode. The new model is setting recordsacross competitive benchmarks, signaling a major leap in AI’s capacityfor complex problem-solving.*   **Performance:** Deep Think hit 84.6% on the ARC-AGI-2 benchmark,far surpassing rivals. It also reached gold-medal levels on the 2025Physics & Chemistry Olympiads and achieved a high Elo score on theCodeforces coding benchmark.*   **Autonomous Research:** Google unveiled Aletheia, a math agentdriven by Deep Think that can autonomously solve open math problemsand verify proofs, pushing the limits of AI in scientific research.*   **Availability:** The upgrade is live for Google AI Ultrasubscribers, with API access for researchers beginning soon.### OpenAI’s Strategic Move for Speed and DiversificationOpenAI has launched **GPT-5.3-Codex-Spark**, a speed-optimized codingmodel that runs on Cerebras hardware (a diversification away from itsprimary Nvidia stack).*   **Focus on Speed:** Spark is optimized for real-time interaction,achieving over 1,000 tokens per second for coding tasks, making thecoding feedback loop feel instantaneous. It is intended to handlequick edits while the full Codex model tackles longer autonomoustasks.*   **Hardware Strategy:** This release marks OpenAI’s first productpowered by chips outside its primary hardware provider, signaling astrategic move for supply chain resilience and speed optimization.### The Rise of the Open-Source Chinese ModelsThe pricing and capability landscape has been rapidly transformed bytwo major open-source model releases from Chinese labs, puttingimmense pressure on frontier labs.*   **MiniMax M2.5:** MiniMax launched M2.5, an open-source model withcoding performance that scores roughly even with Anthropic’s Opus 4.6and GPT-5.2. Crucially, the cost is significantly lower (e.g., M2.5 is$1.20 per million output tokens, compared to Opus at $25 per million),making it ideal for powering always-on AI agents.*   **General Model Launch:** Z.ai’s **GLM-5**, a744-billion-parameter open-weights model, also sits near the frontier,placing just behind Claude Opus 4.6 and GPT-5.2 in generalintelligence benchmarks. GLM-5 supports domestic Chinese chips and isavailable with MIT open-source licensing.### The $200M Political AI Arms RaceThe political dimension of AI regulation and governance has escalated,with major AI labs committing significant funds to the 2026 midtermelections.*   **Political Spending:** In total, AI companies have now committedover $200 million to the 2026 midterms, setting up a literal arms racebetween the major players.*   **Dueling PACs:** Anthropic recently committed $20 million to aSuper PAC advocating for increased AI regulation, while OpenAIco-founder Greg Brockman contributed $25 million to a PAC that favorsa hands-off, innovation-first approach to government oversight.***## II. Economic Shifts, Job Automation, and Strategic Planning### The Customer Service ReckoningData suggests that the impact of AI on white-collar labor isaccelerating, particularly in customer-facing roles.*   **Hiring Decline:** The percentage of new hires going intoCustomer Support has plummeted by about two-thirds over the last twoyears, dropping from 8.3% to 2.9% in Q3 ‘25, with the most severe dropoccurring in the most recent quarter. This reinforces the expectationthat roles built on repetitive, high-volume interaction are vulnerableto AI substitutes.*   **Job Creation:** While certain occupations are shrinking, AI isexpected to follow historical patterns where new jobs emerge innon-existent categories. Over half of net-new jobs since 1940 are inoccupations that did not exist at the time, suggesting a rotation fromroles like Customer Service to new roles like “Software Developers”and “Biz-Ops.” The core truth remains that while the bundles of tasksthat constitute a “job” will change, there will always be work to do.### The White-Collar Sitting TrapA peculiar cultural observation from the Bureau of Labor Statistics(BLS) highlights the extreme difference in work environment betweenknowledge workers and service roles:*   **Software Developers** report sitting for a staggering **97%** oftheir workdays, the highest surveyed group (Marketing Managers werealso above 90%).*   In contrast, service roles (bakers, waitstaff) report sitting forless than 2% of the time. This data point serves as a non-technicalreminder for knowledge workers to address the health implications ofsedentary work.### SF’s Dominance Reaffirmed in Venture CapitalFollowing a temporary dispersion of tech hubs in 2021-2022, SanFrancisco has cemented its status as the singular epicenter forventure capital activity.*   **Company Formation:** San Francisco is the only major VC hub toexperience an increase in venture-backed company formation since the2022 high-water mark, accompanied by a resurgence in demand for officespace.*   **Capital Concentration:** The Bay Area now captures roughly 40%of all early-stage venture dollars, dominating all verticals exceptHealthtech. This concentration highlights a market trend where capitalflocks to centers of competence during periods of contraction.### The Capital Expenditure Race and Apple’s StanceInvestment in AI infrastructure (chips and data centers) by the “Big5″ tech companies continues its explosive growth, with 2026 Capexestimates rising to $650 billion—triple the spending from 2024.*   **Hyperscaler Strategy:** Companies like Meta, Amazon, Microsoft,and Google are dramatically increasing their capital expenditures tomeet the soaring demand for compute, viewing the AI race as one theycannot afford to lose.*   **Apple Exception:** Apple is the notable outlier, as the only Big5 company to reduce its Capex last quarter, suggesting it isdeliberately sitting out the current hardware arms race.***## III. New Research, Strategy, and Practical Applications### Modeling and TrustworthinessNew research is challenging assumptions about how AI models developsocial intelligence and reliability:*   **”To Think or Not To Think”:** A new paper suggests that simplygiving a model more “thinking time” does not consistently improve itsability to understand human intent or beliefs, and can sometimesintroduce new failure modes. This indicates that better reasoning doesnot automatically guarantee better social or contextual intelligence.*   **”Tool Shaped Objects”:** Will Manidis published a critiquearguing that a large part of the current AI boom is “FarmVille atinstitutional scale,” where companies spend heavily on workflows thatmimic productivity without generating real economic value, warningthat the focus on *workflow* over *output* is a significant economictrap.*   **Optimal Superintelligence:** Nick Bostrom released a paperarguing that the benefits of superintelligence—curing diseases,extending life—outweigh the risks, suggesting that delaying itsarrival is comparable to choosing inevitable death over risky surgery.### The Geopolitical Scramble for AI InfrastructureThe competition is increasingly moving beyond just model capability toinfrastructure control, leading to potential new geopoliticalalliances.*   **Sovereign AI Alliances:** Stanford HAI argues that as mid-sizednations become concerned about control over AI and digitalinfrastructure, new alliances may form among them, organized aroundshared compute, data, and deployment rails. This suggests the AI raceis as much about controlling access as it is about controlling thetechnology itself.### Practical AI Tools & Workflows*   **Less Costly Conversions:** Cloudflare now supports real-timeMarkdown conversion of any website by accepting a single `Accept:text/markdown` header, offering a significant reduction in token usagefor agents and reducing the need for custom scraping code.*   **Voice Translation:** **Hibiki-Zero** is an open-source modelthat translates French, Spanish, Portuguese, or German speech toEnglish in real-time while preserving the speaker’s voicecharacteristics.*   **Agentic Automation:** **TinyFish** automates complex web taskslike booking flights and scraping with high accuracy, runningthousands of tasks in parallel for production-scale efficiency.*   **Coding Workflows:** **Claude Code** rolled out multi-reposessions and slash commands for more powerful daily coding workflows,and **Claude Cowork** is an effective desktop agent for non-coders tocreate powerful “Skills” (saved workflows) by demonstrating a taskonce.Best regards,****AI AssistantDiscuss ​Read More

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