Hi, I'm Samuel from Pantic and today I'm going to give a demo of Pyantic AI temporal and Pantic logfire. I'll also cover Pyantic evals. So we have in Pantic AI support for temporal and deboss to durable execution frameworks.We're actually adding a bunch more. I think we've had something like five pull requests to add other durable execution or like workflow orchestration backends. But at the moment it's it's these two.And I think it's fair to say temporal are like the big incumbent in this space and they're ...

Core Insights - The TIOBE Index for November 2025 indicates that C may surpass Java for the first time in history, following Python's dominance since late 2023 [1][12] - C is currently the fastest-growing programming language, with a significant upward trend that could lead to it becoming the top language in 2025 [4][12] - The competition between C and Java has intensified, with the gap between their ratings now being less than 1% [12][19] Programming Language Rankings - The current top programming languages are Python, C, C++, Java, and C, with C showing a notable increase of 2.67% [12][21] - The historical ranking of programming languages shows C maintaining its position at fifth place, while Python remains at the top [28][29] - The rankings reflect the shifting focus of developers towards languages that offer modern features and cross-platform capabilities [19][30] Industry Trends - C has evolved from being a Windows-only enterprise language to a modern, cross-platform, and open-source language, making it competitive with Java in various fields [13][19] - Java continues to dominate in the financial sector due to legacy systems, but C is gaining ground in game development, web services, and cloud-native applications [7][9][19] - The programming landscape is characterized by a shift in developer preferences towards languages that enhance productivity and user experience rather than just stability [15][19]

Core Points - The Python Software Foundation (PSF) rejected a $1.5 million grant from the National Science Foundation (NSF) due to restrictions against promoting diversity, equity, and inclusion (DEI) initiatives [1][2] - The PSF board believes that such restrictions contradict the foundation's mission, leading to the decision to forgo what could have been its largest funding ever [2] - Following the announcement, the PSF received strong positive feedback from the community, resulting in a surge of donations from thousands of individual and corporate supporters [4] Financial Impact - In a matter of days, the PSF received thousands of new donations and increased its number of "supporting members" (annual fee of $99) [6] - As of last Friday, the foundation's executive director Deb Nicholson disclosed that they had received over $157,000 in donations, including 295 new supporting members [6] - Although these new donations have not yet compensated for the $1.5 million grant shortfall, the PSF emphasized the significance of the community's strong support [6] Mission and Values - The PSF reiterated its mission to "support and promote a diverse, international Python community," emphasizing the importance of maintaining its core values even at the cost of substantial funding [7]

Core Insights - The core insight of the article is that TypeScript has overtaken Python as the most widely used programming language on GitHub, marking a significant shift in developer preferences towards typed languages, particularly in the context of AI-assisted development [2][4][6]. Group 1: Language Popularity and Growth - TypeScript became the most popular language on GitHub in August 2025, surpassing Python with approximately 2.6 million contributors, a year-over-year growth of 66.6% [6][13]. - Python, while dropping to second place, still maintains a strong presence with around 2.6 million contributors, growing by 48.8% year-over-year [6][20]. - JavaScript remains a significant player with 2.15 million contributors, but its growth has slowed as developers shift towards TypeScript [7][9]. Group 2: Factors Driving TypeScript's Rise - The rise of TypeScript is attributed to its type system, which reduces code ambiguity and helps catch errors generated by AI before deployment [14][15]. - Many modern development frameworks now default to TypeScript, further driving its adoption among developers [14]. - The entry barrier for TypeScript is lower due to tools that simplify setup, making it accessible for junior developers [16] . Group 3: Python's Continued Dominance in AI - Despite TypeScript's rise, Python remains the dominant language in AI projects, driving nearly half of the new AI repositories with 582,196 new projects, a year-over-year growth of 50.7% [20]. - Jupyter Notebook continues to be the preferred exploratory environment for AI, with 402,643 repositories, reflecting a 17.8% increase [20][18]. Group 4: Broader Trends in Development - Open-source development activity reached record levels, with a total of 1.12 billion contributions, a 13% year-over-year increase [24]. - India emerged as the largest source of new developers on GitHub in 2025, contributing over 5.2 million new developers, which is more than 14% of the total new developers [26]. - The growth of traditional languages like Java and C continues, indicating their stability in enterprise environments despite the rise of AI [27]. Group 5: Emerging Languages and Tools - Luau, the scripting language for Roblox, saw a remarkable growth of over 194%, reflecting a trend towards typed flexibility in the industry [31]. - The focus on performance-centric developer tools is increasing, with tools like Ghostty and Tailwind CSS gaining attention for their speed and minimal development friction [32].

Core Insights - A unique team of two 14-year-old overseas students, LayersOfLogic, has gained attention at the 2025 Global "AI + Radio" Challenge, showcasing the potential of the younger generation [1][2] Group 1: Team Members - Victoria Wang, a Year 10 student at St Paul's Girls' School in the UK, excels in academics and extracurricular activities, including robotics and mathematics competitions, and demonstrates a well-rounded talent in sports and music [1] - Kevin Ke, a Year 10 student at Eton College, has a strong interest in biology, science, and mathematics, and is a music scholarship recipient, actively participating in various artistic and athletic activities [2] Group 2: Learning and Development - The team began with foundational knowledge in wireless communication and artificial intelligence, utilizing online tutorials to learn about IQ signals and signal preprocessing techniques [3] - They demonstrated mature teamwork skills, overcoming scheduling challenges through careful planning and communication, and learned the importance of perseverance in problem-solving [3] Group 3: Achievements and Future Aspirations - The experience of participating in the competition has significantly enhanced their knowledge and skills, allowing them to progress from basic Python to proficient use of TensorFlow for programming and data handling [3] - Both students expressed a desire to continue learning and exploring science and technology, applying the teamwork and problem-solving skills gained from the competition to future endeavors [4]

Core Insights - The article emphasizes that technology selection, particularly programming languages, often masks deeper issues related to personal identity and emotional attachment rather than purely technical considerations [1][4][18] - It highlights the importance of recognizing the hidden conversations that influence decision-making processes in technology choices, which can lead to significant financial implications for companies [17][19] Group 1: Case Studies - The first case involves a company, Takkle, where a new CTO's decision to switch from PHP to Perl resulted in a 9-month delay in product launch and a doubling of monthly burn rate from $200,000 to $500,000, ultimately leading to financial distress [5][6] - The second case at Google illustrates a similar pattern, where a vice president's push for Rust over Go was based on emotional and identity-driven reasoning rather than a thorough analysis of technical merits [7][8][11] Group 2: Decision-Making Dynamics - The article distinguishes between visible conversations focused on technical attributes and invisible conversations centered on personal identity and professional aspirations [9][10][18] - It argues that decisions driven by identity can lead to substantial costs, as technology stack choices account for 40% to 60% of total development costs over a product's lifecycle [17][19] Group 3: Recommendations for Improvement - Companies are encouraged to shift the focus of technology discussions from "which language is best" to "what are the costs associated with this language," encompassing all dimensions that affect survival and growth [19][20] - A framework is suggested to make hidden costs visible, allowing for more rational and economically driven decision-making in technology selection [19][20]

Core Insights - The article emphasizes the growing importance of programming as a skill for children, highlighting the need to choose the right programming language for their learning journey [2][15] - The "Children's Programming Language Development Trend List" serves as a significant reference for understanding industry trends and educational philosophies [2][3] Trend Analysis - The ranking reveals a shift from traditional programming languages like C++, Java, and Python to languages that align more closely with children's cognitive development and interests [3] - The top-ranked platform, Xigua Creator, exemplifies a successful educational approach by integrating a systematic learning path from graphical programming (Scratch) to text-based programming (Python) [3][4] Language Distribution - The list categorizes programming languages into two main tiers: graphical programming languages (e.g., Scratch, Blockly) and text-based programming languages (e.g., Python) [4] - Scratch is recognized as the standard for children's programming initiation, allowing for creative expression without the burden of complex syntax [6] Educational Pathways - The transition from graphical to text-based programming is crucial for children's development, with Python being the recommended next step due to its simplicity and wide application in fields like AI and data science [7][10] - The article outlines a structured approach to learning, emphasizing the importance of engaging and enjoyable educational experiences [8][15] Future Considerations - The choice of programming language is framed as an investment in children's future, with different languages leading to various career paths [9][10] - A comprehensive learning platform is deemed essential, providing exposure to multiple programming paradigms and fostering a supportive learning environment [11][12] Age-Specific Recommendations - For ages 6-9, graphical programming like Scratch is recommended to build foundational logic and computational thinking [16] - Ages 9-12 is identified as the optimal time to transition to Python, while ages 12 and above can focus on languages aligned with their interests, such as C++ for game development or JavaScript for web development [16]

Enrollment Trends - Accounting programs in U.S. colleges saw a 12% increase in student enrollment in 2024, although the number of bachelor's degrees fell by 10.3% from 2021-2022 to 2022-2023, with a slower decline of 3.3% the following year [1][2] Employment Landscape - Public accounting firms reported hiring 11,985 new graduates in 2024, with 75% being accounting majors, and three-quarters of firms expect to hire the same or more in 2025 [3] - However, the AICPA survey had a low response rate of only 1% from the 19,097 firms surveyed, limiting the reliability of the hiring data [4] Impact of Automation - Automation is increasingly handling tasks traditionally filled by entry-level positions in audit and tax, leading to a disconnect between education and employment [2][5] - 63% of accounting programs have incorporated instruction in AI, data analytics, and tools like Power BI, Alteryx, and Python, but the relevance of these skills is questioned as automation reduces the roles they were intended to fill [5] Career Development Concerns - The traditional apprenticeship model in public accounting is being challenged as machines can perform routine tasks faster and cheaper, potentially shrinking the pipeline of future partners in the profession [6]

Core Viewpoint - The Python Software Foundation (PSF) withdrew its grant proposal of $1.5 million from the National Science Foundation (NSF) due to conditions that conflicted with its core values of diversity, equity, and inclusion (DEI) [1][5][10]. Group 1: Grant Proposal and Objectives - PSF submitted a proposal aimed at enhancing the security of the Python ecosystem, particularly focusing on improving supply chain protection for the Python Package Index (PyPI) [3]. - The project intended to develop new automated tools for proactive review of software packages uploaded to PyPI, moving away from the current reactive mechanisms [3][4]. - The proposal was led by PSF's security developer Seth Larson and involved extensive preparation and a challenging application process, with a success rate of only 36% for first-time NSF applicants [4]. Group 2: Conditions and Risks - The NSF's conditions required PSF to refrain from operating or promoting any DEI initiatives during the grant period, which raised significant concerns for PSF [5][6]. - Violating these conditions could result in NSF reclaiming the funds, posing a substantial financial risk to PSF, which operates on an annual budget of approximately $5 million [6][7]. Group 3: Decision and Community Response - After internal discussions, PSF unanimously decided to withdraw the grant application, prioritizing its core values over the financial support [10]. - The decision was supported by members of the community, emphasizing the importance of maintaining the foundation's mission and values [12]. - The situation highlights the ongoing challenge for open-source organizations in balancing funding opportunities with their foundational principles [11][12].

Core Insights - The article discusses the growing trend of WeChat bot development in the digital age, highlighting its importance for both individual developers and corporate tech teams to automate tasks, enhance efficiency, and improve user experience [1]. Group 1: Overview of WeChat Bot Development - WeChat bots are automated tools based on the WeChat platform that can perform functions such as automatic message replies, friend additions, and posting on Moments, thereby improving work efficiency and user experience [3]. - Understanding the basic principles, development environment setup, framework selection, and coding steps is essential for creating a simple "Hello World" function, which serves as a foundation for more complex functionalities [3]. Group 2: Development Environment Setup - A suitable development environment is crucial for WeChat bot development, requiring the installation of Python, which is a commonly used programming language for this purpose [4]. - Essential development tools like PyCharm or Visual Studio Code should be installed to facilitate efficient coding, along with necessary libraries and frameworks such as itchat or wxpy, which provide rich APIs for various bot functionalities [4]. Group 3: Framework Selection - Choosing the right development framework is a key step, with popular options being itchat and wxpy; itchat is based on the WeChat Web API and supports various functionalities, while wxpy offers a more user-friendly API and enhanced features [5]. - For beginners, wxpy is recommended due to its ease of use [5]. Group 4: Writing Hello World Code - The article provides a simple code example for creating a "Hello World" function, which involves importing necessary libraries, logging into WeChat, receiving messages, and replying with "Hello World" [6][7]. - The provided code snippet demonstrates the basic functionality of the WeChat bot [7]. Group 5: Testing and Debugging - Testing and debugging are critical phases in WeChat bot development, ensuring that the bot can log in, receive messages, and respond correctly [8]. - Sending test messages helps verify the bot's functionality, and debugging tools can assist in identifying and resolving issues by examining the execution process and variable values [8]. Group 6: Deployment and Optimization - After successful testing, the WeChat bot can be deployed on a server for continuous operation, requiring careful selection of a server that meets performance needs [9]. - Optimization methods, including code and server configuration improvements, are necessary to enhance the bot's performance and stability during actual use [9].