Google Advances AI Agent Development While Anthropic Improves AI Efficiency

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The artificial intelligence sector is experiencing rapid development and significant investment, alongside growing concerns about its economic impact, ethical implications, and sustainability. Google recently expanded its AI Agent Development Kit (ADK) to the Go programming language, making it easier for developers to build AI agents optimized for Gemini and Google Cloud, complete with secure agent-to-agent communication. Meanwhile, Anthropic introduced a new 'Code Execution With MCP' method, drastically improving AI agent efficiency by reducing token usage by as much as 98.7 percent, which makes AI workflows faster and more cost-effective. On the educational front, Loyola Marymount University (LMU) is developing an AI course companion, set to launch by August 2025, offering 24/7 personalized student support using Amazon Web Services (AWS) for secure data management. Similarly, Harlingen Consolidated Independent School District is deploying AI apps like Snorkl to provide immediate feedback and personalized challenges for students, while also assisting teachers with lesson planning and feedback. However, the AI boom also faces scrutiny. Kim Williams, chair of the ABC, warned that AI could become "dangerous and sinister" due to the "extremely autocratic" views of some investors and leaders, raising concerns about potential censorship and the need for creators to be paid for their work. Cisco's global innovation officer, Guy Diedrich, emphasized the increasing importance of humanities skills, like ethics and philosophy, for responsible AI deployment, noting that 80 percent of companies lack these crucial skills. The financial landscape for AI is also volatile. Tech stocks linked to AI, including Nvidia, Microsoft, and Tesla, recently saw a selloff that erased over $1 trillion from major US companies, fueling fears that the AI boom might be a financial bubble rather than a sustainable revolution. This massive investment is evident in projections, with JP Morgan expecting hyperscalers' capital investment to jump from $67 billion in 2019 to $467 billion by 2027, and McKinsey & Co. projecting $5 trillion for data centers by 2030. For instance, an Amazon project in Indiana alone requires 2.2 gigawatts of power. This intense demand for infrastructure is putting pressure on chip manufacturers, with Nvidia CEO Jensen Huang asking TSMC for more chip wafers on November 8, 2025, to keep up with the strong AI demand. The widespread deployment of AI is also driving up utility costs for everyday consumers, as explained by Google researcher Benjamin Lee, due to AI's growing energy demands.

Key Takeaways

Google released its AI Agent Development Kit (ADK) for the Go programming language, enabling developers to build AI agents optimized for Gemini and Google Cloud.
Anthropic introduced a 'Code Execution With MCP' method, reducing AI agent token usage by up to 98.7 percent for faster and cheaper workflows.
Loyola Marymount University (LMU) is launching an AI course companion by August 2025, providing 24/7 student support using AWS for data security.
Harlingen Consolidated Independent School District is implementing AI apps like Snorkl to enhance student learning with personalized feedback and assist teachers with lesson planning.
ABC chair Kim Williams warned that AI could become "dangerous and sinister" due to the "autocratic" views of some investors, raising concerns about censorship and fair compensation for creative work.
Cisco's global innovation officer highlighted the critical need for humanities skills in the AI era, noting that 80 percent of companies lack these essential capabilities for responsible AI deployment.
Tech stocks, including Nvidia, Microsoft, and Tesla, experienced a selloff, erasing over $1 trillion and sparking fears that the AI boom might be a financial bubble.
Nvidia CEO Jensen Huang requested more chip wafers from TSMC on November 8, 2025, to meet the high demand for AI chips.
Hyperscalers' capital investment is projected to increase significantly, with JP Morgan expecting it to reach $467 billion by 2027 and McKinsey & Co. forecasting $5 trillion for data centers by 2030.
The widespread use of AI is increasing utility costs for consumers due to the growing energy demands of AI technologies.

Google brings AI Agent Development Kit to Go language

Google released its Agent Development Kit ADK for the Go programming language. This allows Go developers to build AI agents using the same framework as Python and Java. ADK is an open-source tool optimized for Gemini and Google Cloud, offering a code-first approach for creating and deploying AI agents. It supports various tools and deployment options, including local runs and Vertex AI Agent Engine. The Go version also includes native support for the Agent2Agent protocol, letting agents communicate securely.

Anthropic improves AI agents with new code execution method

Anthropic introduced a new 'Code Execution With MCP' approach to make AI agents more efficient. This method helps solve problems with high token usage and latency when agents use the Model Context Protocol MCP. Instead of passing all tool definitions and results through the model's context, the MCP client now exposes servers as code modules. The AI model writes TypeScript code to interact with these modules in a secure environment. This change drastically reduces token usage, with one example showing a 98.7 percent drop, making AI workflows faster and cheaper.

LMU launches AI companion for personalized student learning

Loyola Marymount University LMU developed an AI course companion to provide students with 24/7 personalized learning support. Brian Drawert created the tool, which runs on AWS, ensuring data control and student privacy. The university chose AWS because of its strong security and existing relationship. The AI companion will launch in classrooms by August 2025, mirroring how faculty teach by adding course content weekly. This system uses Amazon Transcribe for classroom recordings and allows students to log in with LMU credentials for conversational help.

ABC chair warns AI investors' views could be dangerous

Kim Williams, chair of the ABC, warned that AI could become "dangerous and sinister" due to the "extremely autocratic" views of some investors and leaders in AI companies. Williams, who uses AI tools like ChatGPT, believes technology reflects the values of its creators. He expressed concern that these powerful technologies could be used to limit and censor ideas, which is dangerous for democracy. Williams also stated that people deserve to be paid for their creative work used by AI and predicted AI could destroy many entry-level jobs, though journalism might be less affected.

Harlingen schools use AI apps to boost learning

Harlingen Consolidated Independent School District is using AI apps to improve classroom learning. Fifth-grade teacher Brittany Garcia uses the Snorkl app for math, which gives students like Lily Reyes immediate feedback and personalized challenges. This AI tool also provides teachers with detailed student performance data. The district is also introducing other AI platforms to help teachers create lesson plans, quizzes, and offer writing feedback. Dr. Maria Rodriguez, chief academic officer, stated that these tools aim to enhance teaching and free up teachers' time for more direct student interaction.

Nvidia CEO asks TSMC for more chips due to high AI demand

Nvidia CEO Jensen Huang asked TSMC for more chip wafers to keep up with the very strong demand for AI. Huang met with TSMC CEO C.C. Wei in Hsinchu, Taiwan, on November 8, 2025, and expressed gratitude for TSMC's support. Nvidia's AI memory chip suppliers, including SK Hynix, Samsung, and Micron, have greatly increased their production. Despite TSMC's capacity being tight, Wei expects the company to continue seeing record sales each year. Nvidia remains the world's most valuable business, and rivals like Qualcomm are also competing for TSMC's limited supplies.

Cisco officer says humanities skills are key for AI era

Guy Diedrich, Cisco's global innovation officer, believes that as technology rapidly advances into the AI and quantum ages, humanities skills are becoming essential. He states that knowing how to ask the right questions about ethics, philosophy, and problem-solving is crucial, especially since AI will soon be everywhere. Diedrich noted a decline in humanities studies but emphasized their importance for responsible AI deployment. A Cisco report found that 80 percent of companies lack the skills needed for this. He advocates for a lifelong learning approach and for employers to value well-rounded individuals with both technical and human-centered skills.

Tech giants lose over $1 trillion as AI stock fears grow

Tech stocks linked to artificial intelligence experienced a significant selloff, causing over $1 trillion to be erased from major US companies. Giants like Nvidia, Microsoft, and Tesla saw sharp losses this week. Experts suggest that investors are losing confidence due to concerns that many AI projects are not yet profitable. This market downturn raises fears that the AI boom might be a bubble, leading to significant uncertainty ahead.

Is AI a revolution or a financial bubble

Christopher Hopkins discusses whether the current AI boom is a revolution or a financial bubble, noting the massive investment diverting funds from other economic sectors. Harvard economist Jason Furman reports that information processing and software accounted for 92 percent of GDP growth in early 2025. While tech giants like the Magnificent 7 have historically been asset-light, the AI buildout requires huge infrastructure spending. JP Morgan expects hyperscalers' capital investment to jump from $67 billion in 2019 to $467 billion by 2027. McKinsey & Co. projects $5 trillion for data centers by 2030, with one Amazon project in Indiana alone needing 2.2 gigawatts of power.

Hidden AI costs drive up energy bills

The widespread use of AI technologies is causing utility costs for everyday consumers to rise significantly. Benjamin Lee, a University of Pennsylvania professor and Google researcher, explained that the increasing deployment of AI behind the scenes is directly driving up these energy expenses. He noted that currently, the focus is heavily on the benefits of AI, leading to a willingness to pay the necessary costs to develop next-generation capabilities. This trend means consumers are indirectly paying more due to AI's growing energy demands.