According to Miles Deutscher, skillsmp.com hosts a full agent marketplace of 60,000+ Claude Skills that are ready for use now for Claude Code builders (source: Miles Deutscher on X, Jan 14, 2026). According to the source, developers are encouraged to bookmark the site, highlighting immediate access to prebuilt agents for Claude Code (source: Miles Deutscher on X). For traders, the source-reported scale and availability provide a concrete datapoint on AI agent tooling within the Claude ecosystem that can be tracked alongside AI-related crypto narratives (source: Miles Deutscher on X).

According to @lisaabramowicz1, Citi CEO Jane Fraser warned of more job cuts, stating that automation, AI, and process simplification will reshape how work gets done, with some roles changing, new ones emerging, and others no longer required. Source: Lisa Abramowicz on X citing Bloomberg, Jan 14, 2026. The remarks constitute an explicit workforce and technology adoption update at Citi, with AI and automation identified as the drivers of organizational change. Source: Lisa Abramowicz on X citing Bloomberg, Jan 14, 2026. For trading relevance, the CEO guidance signals a near term focus on cost discipline and AI deployment at Citi, creating a headline catalyst around its operating model and workforce mix that market participants may track. Source: Bloomberg via the post by Lisa Abramowicz, Jan 14, 2026. The emphasis on enterprise AI adoption within banking also intersects with AI narratives monitored across digital asset markets. Source: Lisa Abramowicz on X citing Bloomberg, Jan 14, 2026.

According to @milesdeutscher, Google offers free AI resources including 10 or more PDF guides, free live courses, and Google AI Studio for rapid prototyping. Source: @milesdeutscher, Jan 13, 2026 tweet. According to @milesdeutscher, these tools are positioned to significantly upskill AI and coding abilities while providing no-cost hands-on prototyping pathways. Source: @milesdeutscher, Jan 13, 2026 tweet. For traders focused on the AI crypto narrative, the author’s emphasis on free upskilling and prototyping resources is relevant context when monitoring builder activity around AI-related projects. Source: @milesdeutscher, Jan 13, 2026 tweet.

According to @casey_lau, bookstores and magazines in Japan are carrying many practical guides on generative AI covering prompt engineering and creative use cases, indicating widespread consumer-facing education availability (Source: @casey_lau on X, Jan 10, 2026). According to @casey_lau, one highlighted title is published by SoftBank’s publishing arm, showing corporate-backed distribution of GenAI learning materials (Source: @casey_lau on X, Jan 10, 2026). For traders, this is a verified datapoint of growing GenAI education supply in Japan, with no direct mention of listed equities or crypto assets and thus no explicit price catalyst identified in the source (Source: @casey_lau on X, Jan 10, 2026).

According to @AnthropicAI, the Anthropic Engineering Blog has published Demystifying evals for AI agents, outlining evaluation strategies that have worked across real-world deployments; source: Anthropic (@AnthropicAI), https://www.anthropic.com/engineering/demystifying-evals-for-ai-agents, Jan 9, 2026. The announcement notes that the same capabilities that make agents useful also make them harder to evaluate, underscoring a focus on rigorous, deployment-tested benchmarks; source: Anthropic (@AnthropicAI), https://www.anthropic.com/engineering/demystifying-evals-for-ai-agents, Jan 9, 2026. For traders, the post signals continued emphasis on measurable reliability from a leading AI lab, with no mention of cryptocurrencies, tokens, or partnerships in the announcement; source: Anthropic (@AnthropicAI), https://twitter.com/AnthropicAI/status/2009696515061911674, Jan 9, 2026.

According to Andrew Ng, he proposes the Turing-AGI Test as a new benchmark where either a computer or a skilled human completes multi-day real-work tasks via a computer with internet tools, and a computer passes if it performs as well as a skilled human, providing a practical measure of human-level capability for knowledge work, source: Andrew Ng via X on Jan 6, 2026; DeepLearning.AI The Batch, Issue 334. According to Andrew Ng, the setup includes access to a web browser and Zoom, with judges free to design undisclosed training and execution phases (for example, training as a call center operator then taking calls with feedback), mirroring remote work and probing generality beyond fixed datasets, source: Andrew Ng via X on Jan 6, 2026; DeepLearning.AI The Batch, Issue 334. According to Andrew Ng, this aligns with the public’s view of AGI, addresses shortcomings of the original Turing Test and leaderboard-tuned benchmarks, and focuses on economically useful work rather than fooling judges, source: Andrew Ng via X on Jan 6, 2026; DeepLearning.AI The Batch, Issue 334. According to Andrew Ng, unchecked AGI hype lowers the bar for claims and risks an investment bubble and subsequent collapse of interest, while a rigorous test could defuse hype and support a steadier path of continued investment and real progress, source: Andrew Ng via X on Jan 6, 2026; DeepLearning.AI The Batch, Issue 334. According to Andrew Ng, a Turing-AGI Test competition would create clear outcomes where broad failure would intentionally defuse hype and passing would be incredibly valuable, defining event risk and binary milestones that traders can monitor for AI-linked equities and crypto projects tied to AI narratives, source: Andrew Ng via X on Jan 6, 2026; DeepLearning.AI The Batch, Issue 334.

According to CoinMarketCap, the Binance Alpha airdrop program uses an Alpha Points system to gate access to early-stage tokens, with a rolling 15-day calculation that explicitly rewards consistent participation, directly shaping trading allocation strategies for airdrop hunters. Source: CoinMarketCap on X, Jan 3, 2026. According to CoinMarketCap, 2026 narratives are infrastructure-focused, with AI, restaking, and RWA tokenization identified as leading themes, signaling where airdrop-linked activity and attention may concentrate. Source: CoinMarketCap on X, Jan 3, 2026. According to CoinMarketCap, traders tracking Binance Alpha should prioritize the consistency emphasized by the 15-day rolling mechanism and monitor AI, restaking, and RWA pipelines as the primary sectors flagged by the source. Source: CoinMarketCap on X, Jan 3, 2026.

According to @StockMKTNewz, Amazon Web Services (AMZN) announced a plan to build and deploy purpose-built AI and high-performance computing for the U.S. government, including a commitment to invest up to $50 billion to expand AI and supercomputing capabilities; source: @StockMKTNewz tweet dated 2025-12-30. For traders, headline-driven AI capex announcements can be near-term catalysts for AMZN and government cloud peers, while also lifting sentiment across AI-linked crypto narratives; this specific post names no cryptocurrencies, so any crypto impact would be narrative-driven rather than fundamental; sources: @StockMKTNewz tweet (2025-12-30) and the absence of crypto assets mentioned in the same post.

According to @hamster_kombat, OpenAI is recruiting a Head of Preparedness, a headline that can sway AI-related crypto narratives in the near term, source: @hamster_kombat on X, Dec 30, 2025. According to @hamster_kombat, Trust Wallet users reportedly lost $7 million via a hacked Chrome extension, raising wallet-security risk and potential risk-off behavior in the wallet ecosystem, source: @hamster_kombat on X, Dec 30, 2025. According to @hamster_kombat, JPMorgan froze accounts of stablecoin startups Blindpay and Kontigo, highlighting ongoing banking and compliance frictions for fiat on-ramps that can affect stablecoin market sentiment, source: @hamster_kombat on X, Dec 30, 2025. According to @hamster_kombat, BlackRock's BUIDL reached $100 million in payouts, underscoring steady tokenized real-world asset distribution activity that traders may track for RWA narrative strength, source: @hamster_kombat on X, Dec 30, 2025. According to @hamster_kombat, traders should monitor headline confirmations and price reactions across wallet-security plays, stablecoin infrastructure, and RWA tokens for near-term volatility, source: @hamster_kombat on X, Dec 30, 2025.

According to @CNBC, Meta has acquired intelligent agent firm Manus, with the outlet describing the deal as capping a year of aggressive AI moves by the company (Source: CNBC). CNBC’s post did not include deal size, timing, or integration details, which means traders will likely look for official Meta updates to assess any concrete catalysts for positioning in AI-exposed equities (Source: CNBC). CNBC did not reference crypto assets in the update; any crypto-market read-through would be narrative-based rather than a direct linkage from this announcement (Source: CNBC).

According to @CNBC, the outlet has published a one-year review asking whether the UK's grand AI plan has delivered a successful infrastructure buildout, signaling an investor focus on real-world deployment and capacity progress (source: CNBC). For trading, this spotlight makes UK AI infrastructure updates a near-term catalyst to watch for sentiment in AI-exposed equities and AI-related crypto narratives, where policy and buildout progress often drive momentum (source: CNBC).

According to @DeepLearningAI, its year-end The Batch edition frames 2025 as the year reasoning models changed everything and explores how AI learned to think before it speaks (source: DeepLearning.AI). The edition highlights three themes: China turning chip restrictions into innovation fuel, coding agents becoming true development partners, and U.S. economic growth driven by infrastructure spending (source: DeepLearning.AI). It also features a holiday message from Andrew Ng to the AI community (source: DeepLearning.AI). For traders, these covered themes map directly to compute supply chains, software automation, and capex cycles that shape positioning in AI equities and AI-linked crypto narratives (source: DeepLearning.AI).

According to @LexSokolin, crypto will continue to fail in AI and robotics if markets prioritize narrative over real traction, making verifiable adoption the key filter for capital allocation in 2025, source: Lex Sokolin on X, Dec 26, 2025. For trading, this signals de-risking narrative-only AI and robotics plays and prioritizing projects that show measurable usage, user growth, or on-chain activity to reduce drawdowns and capture durable upside, source: Lex Sokolin on X, Dec 26, 2025.

According to the source, a civil complaint in Connecticut alleges ChatGPT contributed to a murder-suicide, naming OpenAI and Microsoft as defendants (source: publicly accessible court filings in Connecticut). The litigation elevates disclosed legal and product-liability risks around generative AI that Microsoft warns could materially affect results and reputation, implying potential near-term volatility in MSFT and related AI equities (source: Microsoft Corporation, Form 10-K for FY2024, Risk Factors). Crypto traders should track sentiment spillover to AI-linked tokens and liquidity conditions around legal milestones, given prior market research documenting sensitivity of AI narrative tokens to AI news flow (source: Kaiko, Market Report 2024 on AI token performance and headline sensitivity).

According to @OpenAI, monitoring a model’s chain-of-thought is more effective than watching only its actions or final answers, and longer CoTs make it easier to spot issues, source: OpenAI on X, Dec 18, 2025, https://twitter.com/OpenAI/status/2001791132645437703. The post underscores that transparent reasoning traces should be prioritized for AI oversight and evaluation workflows because they provide stronger signals for detecting failures during monitoring, source: OpenAI on X, Dec 18, 2025, https://twitter.com/OpenAI/status/2001791132645437703. For trading relevance, the statement flags a focus area for AI tooling narratives intersecting crypto—such as verification-oriented agent frameworks and auditable inference logs—as potential catalysts for attention and due diligence screens, without asserting price impact, source: OpenAI on X, Dec 18, 2025, https://twitter.com/OpenAI/status/2001791132645437703.

According to @gdb (Greg Brockman), OpenAI marked the 10-year anniversary of its announcement, amplifying Sam Altman’s post that links to OpenAI’s Ten Years retrospective. Source: Greg Brockman on X https://twitter.com/gdb/status/1999239492704829534; Sam Altman on X https://x.com/sama/status/1999232754131804249; OpenAI Ten Years https://openai.com/index/ten-years/ The cited posts are commemorative and do not include product, funding, token, or partnership disclosures, indicating no direct price-sensitive catalyst in the materials themselves for crypto markets; any trading relevance is limited to potential sentiment around the AI narrative. Source: Greg Brockman on X https://twitter.com/gdb/status/1999239492704829534; Sam Altman on X https://x.com/sama/status/1999232754131804249.

According to @timnitGebru, the current AI cycle is a hype-driven bubble tied to AGI and AI existential risk circles that she expects will pop, noting that women were early critics, source: Timnit Gebru on X, Dec 10, 2025. For traders, this public skepticism from a prominent AI ethicist is a sentiment signal that could weigh on AI-exposed equities and AI-themed crypto narratives if hype unwinds, source: Timnit Gebru on X, Dec 10, 2025. The post names no tickers or tokens, so the immediate use is monitoring social sentiment rather than initiating a trade, source: Timnit Gebru on X, Dec 10, 2025.

According to @AnthropicAI, its visualization of worker sentiment indicates most workers feel optimistic about AI’s role at work, especially for productivity and communication, as they adapt to more integrated AI workflows (source: AnthropicAI on X, Dec 4, 2025). Reliability was highlighted as a concern, signaling that consistency and trust remain key adoption filters in enterprise AI deployments (source: AnthropicAI on X, Dec 4, 2025). For trading, this supports monitoring enterprise software names emphasizing measurable productivity gains and reliability benchmarks, and tracking AI-related crypto narratives that react to enterprise adoption updates for sentiment shifts (source: AnthropicAI on X, Dec 4, 2025).

According to @Gajpower, blockchain adoption is still at an early stage and AI is just coming alive, with both described as explosive accelerants for the on-chain economy that could shape crypto market narratives. Source: @Gajpower on X https://twitter.com/Gajpower/status/1996274534442569757 For traders, this sentiment highlights the AI plus blockchain theme as a potential focus for momentum and liquidity rotation across on-chain infrastructure and AI-crypto segments. Source: @Gajpower on X https://twitter.com/Gajpower/status/1996274534442569757

According to @lisaabramowicz1, Anthropic’s chief scientist Jared Kaplan said AI systems could handle most white-collar work within two to three years, as reported by The Guardian on December 2, 2025. Source: @lisaabramowicz1 on X; The Guardian. The Guardian interview also highlights Kaplan’s view that future AI models may increasingly train themselves, indicating a faster capability ramp defined by the lab’s own research trajectory. Source: The Guardian. For traders, this explicit 2–3 year horizon offers a concrete benchmark to reassess positioning across AI-exposed equities and AI narratives in digital assets, grounded in a senior lab scientist’s guidance rather than marketing claims. Source: @lisaabramowicz1 on X; The Guardian.