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The evolution of AI in life sciences has ushered in a new era for scientific research, enabling rapid development and deployment of expertise through computational skills. The SciCraft initiative presents 176 validated scientific skills specially designed for AI coding agents, encompassing a wide array of subjects such as genomics, proteomics, drug discovery, and biostatistics. This robust framework not only allows for the creation of new skills but also streamlines workflows by providing tools necessary for diverse scientific tasks. At the heart of SciCraft is the Claude Code, which utilizes a sophisticated 6-step workflow encoded in a CLAUDE.md file to generate high-quality skills efficiently. Users can easily add new skills by simply describing their requirements, after which Claude Code will produce a complete production-ready skill in a matter of minutes. The skills range from pipelines and toolkits to database connectors, catering to various needs in scientific computing. The integration of these skills into existing projects is seamless, empowering researchers to perform complex analyses without deep technical expertise. Moreover, the structured documentation and active community support position SciCraft as a vital resource for scientists looking to leverage AI in tackling intricate research challenges. This heightened accessibility not only enhances productivity but also accelerates the pace of innovation in life sciences.

The Thoughtworks Future of Software Development Retreat in February 2026 provided a significant overview of the current landscape of AI-driven software development. Martin Fowler emphasized that the engineering discipline is not diminishing but evolving, migrating upstream into specifications, test suites, and continuous comprehension. The concept of Test-Driven Development (TDD) has transitioned into a critical form of prompt engineering, where pre-written tests ensure the integrity of AI agents' outputs. Three loops of operation—inner (coding), outer (CI/CD), and a newly formed middle loop aimed at evaluating AI outputs—are now essential. Successful engineers exhibit strong delegation and orchestration skills while navigating these loops. However, current career ladders fail to recognize these evolving skill sets adequately. Interestingly, while the adoption of AI tools has the potential to enhance productivity, it poses challenges like increased cognitive load among developers and potential issues in the PM-developer relationship. Furthermore, organizations must recognize that adapting to AI-driven practices requires not only technical transformations but also cultural changes. Matters such as establishing secure defaults in platform engineering and building comprehensive change logs and agent identity controls are crucial for success. With the landscape constantly shifting, it becomes imperative for organizations to focus on the 'agent experience' alongside the traditional developer experience, ensuring that both AI tools and human developers can thrive.

The Thoughtworks Future of Software Development Retreat provided deep insights on the evolving landscape of software with a significant emphasis on AI integration. Key themes emerged about how AI is reshaping traditional software development practices. The retreat highlighted the challenges organizations face in adapting their processes, tools, and roles to accommodate AI-assisted work. Attendees, including some of the industry's leading experts, shared their experiences and uncertainties surrounding the integration of AI, reflecting a collective realization that there is no one-size-fits-all solution. Among the major discussion topics were the supervisory engineering middle loop, which has been recognized as a new workflow category, and risk tiering that proves vital in this new engineering discipline. The dialogue also emphasized the importance of developer experience investment and posed critical questions about the sustainability of existing practices in light of AI's acceleration of work. Challenges concerning the roles of specialist versus generalist developers were discussed, questioning whether the rise of large language models (LLMs) would diminish the need for specialized skills or enhance the role of expert generalists. Moreover, the implications of AI on the cost of development and security considerations were examined. Participants expressed concerns regarding the balance between rapid development and maintaining security, illustrating the necessity for robust platform approaches to ensure safe deployment of AI technologies. Ultimately, the event reinforced the ongoing uncertainty in the industry while fostering a collaborative environment for exploring innovative solutions to forthcoming challenges.

SideDisplay is an innovative application that transforms your Tesla's large touchscreen into a wireless second monitor for your Mac. Utilizing the Tesla Web Browser, this service allows users to extend their workspace seamlessly without the need for cables or physical modifications. Ideal for users with an Apple Silicon Mac running macOS 26 or later, SideDisplay offers a trial period of 30 minutes per day for free, after which it costs $10.99 per year for unlimited usage. The installation process is straightforward. Users can connect their iPhone hotspot and enable Internet Sharing on their Mac, then launch SideDisplay and navigate to the provided URL in the Tesla web browser. With a latency of approximately 100 milliseconds, this setup delivers a smooth user experience, making it a practical solution for those who need a larger display option on the go. This new functionality is particularly appealing for professionals or creatives who require additional screen space while traveling. As technology continues to evolve, applications like SideDisplay represent an exciting convergence of automotive and computing power, showcasing the potential for innovative use cases in modern vehicles.