AI-Assisted Programming: Better Planning, Coding, Testing, and Deployment
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AI-Assisted Programming: Better Planning, Coding, Testing, and Deployment
Get practical advice on how to leverage AI development tools for all stages of code creation.
AI-Assisted Programming: Better Planning, Coding, Testing, and Deployment
Nº de artículo: 89998541

AI-Assisted Programming: Better Planning, Coding, Testing, and Deployment

88% of respondents would recommend this to a friend

Nº de artículo: 89998541

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NIO 3435

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What Stands Out

Comprehensive Guidance
Offers an all-in-one resource for mastering AI-assisted development, covering planning through deployment with clear insights and strategies.
Enhanced Productivity
Equips developers with techniques to streamline coding and testing processes, leading to faster project completion and improved efficiency.
Expert Insights
Includes contributions from industry experts, providing readers with cutting-edge knowledge and practices in AI integration for software development.

Detalles de producto

Shop AI-Assisted Programming: Better Planning, Coding, Testing, and Deployment online at a best price in Nicaragua. 1098164563
  • Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, design, coding, debugging, testing, and documentation. With this book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Gemini, and Claude) to code-specific systems (GitHub Copilot, Tabnine, Cursor, and Amazon CodeWhisperer). You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation. Author Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code. This guide also describes the best ways of using general purpose LLMs to learn a programming language, explain code, or convert code from one language to another. This book examines: The core capabilities of AI-based development tools Pros, cons, and use cases of popular systems such as GitHub Copilot and Amazon CodeWhisperer Ways to use ChatGPT, Gemini, Claude, and other generic LLMs for coding Using AI development tools for the software development lifecycle, including requirements, planning, coding, debugging, and testing Prompt engineering for development Using AI-assisted programming for tedious tasks like creating regular expressions, starter code, object-oriented programming classes, and GitHub Actions How to use AI-based low-code and no-code tools, such as to create professional UIs
Publisher O'Reilly Media
Publication date May 21, 2024
Edition 1st
Language English
Print length 222 pages
ISBN-10 1098164563
ISBN-13 978-1098164560
Item Weight 2.31 pounds (1.05 kg)
Dimensions 6.75 x 0.5 x 9 inches (17.1 x 1.3 x 22.9 cm)

Who Should Buy?

Suitable For
  • Novice Programmers

    Ideal for beginners seeking guidance in programming concepts, enabling better understanding and skill development with AI assistance.

  • Development Teams

    Perfect for teams looking to enhance collaboration, streamline coding processes, and integrate AI tools for planning and testing.

  • Project Managers

    Useful for managers aiming to improve project planning and deployment strategies through intelligent automation and efficient resource allocation.

Not Suitable For
  • Advanced Developers

    Experienced programmers may find the content basic and not sufficiently challenging for their high-level coding capabilities.

DESCRIPCIÓN DEL PRODUCTO

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Preguntas y respuestas de los clientes

  • Pregunta: What is AI-Assisted Programming?

    Respuesta: AI-Assisted Programming refers to the integration of artificial intelligence technologies in the software development process to improve various stages like planning, coding, testing, and deployment. By leveraging AI tools, developers can automate repetitive tasks, optimize code efficiency, and quickly identify bugs. For example, tools like automated code suggestions can significantly speed up the coding process, allowing developers to focus on more complex problems or innovative features.
  • Pregunta: How can AI improve planning in software development?

    Respuesta: AI enhances planning in software development by analyzing historical data and project metrics to provide actionable insights. These insights help teams estimate timelines, allocate resources effectively, and foresee potential roadblocks. For instance, using machine learning models, project managers can predict which projects are likely to face challenges, thus making informed decisions for smoother execution.
  • Pregunta: What benefits does AI bring to coding?

    Respuesta: AI assists in coding by offering intelligent code completion, detecting errors in real-time, and suggesting best practices based on existing codebases. Tools equipped with AI can learn from previous code to provide contextual recommendations, which can drastically reduce development time. As developers write code, AI can highlight potential issues before they become significant problems, enhancing code quality and reliability.
  • Pregunta: How does AI help in testing software?

    Respuesta: AI enhances software testing by automating routine testing processes and providing predictive analytics that identifies high-risk areas in the code. Machine learning algorithms can analyze past testing data to suggest which areas of the code base need more rigorous testing. For example, if a certain module frequently experiences failures, AI can prioritize its testing in the deployment workflow, ensuring a higher quality dispatch of software.
  • Pregunta: Can AI-Assisted Programming improve deployment processes?

    Respuesta: Yes, AI-Assisted Programming can streamline the deployment process by predicting potential issues based on historical deployment data. AI tools can automate the rollout of updates and monitor system performance during and after deployment. This proactive approach minimizes downtime and ensures that deployments are stable and secure, allowing teams to respond quickly to any anomalies that may arise.
  • Pregunta: What tools are commonly used in AI-Assisted Programming?

    Respuesta: Common tools used in AI-Assisted Programming include advanced IDEs like Visual Studio Code with AI extensions, automated testing frameworks, and deployment pipelines with AI capabilities such as Jenkins or GitHub Actions enhanced with machine learning. These tools facilitate various stages of development by providing insights, improving code quality, and automating workflows, making software development more efficient.
  • Pregunta: What skills are needed to leverage AI in programming?

    Respuesta: To effectively utilize AI in programming, developers should possess a solid understanding of programming fundamentals, algorithms, and familiarization with AI and machine learning concepts. Knowledge in data analysis can also be highly beneficial, as it enables developers to interpret insights provided by AI tools effectively. For instance, a developer transitioning from traditional methods to AI-assisted programming may benefit from online courses focusing on AI integration in software development.
  • Pregunta: Is AI-Assisted Programming suitable for all types of software projects?

    Respuesta: While AI-Assisted Programming is advantageous for many projects, its suitability can vary based on project complexity and team size. Smaller projects may not need advanced AI tools, whereas larger, more complex projects can benefit significantly from AI insights for planning, coding, and testing. For example, enterprise-level applications with extensive codebases and user interactions often leverage AI to manage the increased complexity effectively.
  • Pregunta: What challenges may arise when implementing AI in programming?

    Respuesta: Implementing AI in programming may introduce challenges such as a steep learning curve for developers unfamiliar with AI tools, the need for clean and structured data for AI models, and the potential for biases in AI algorithms affecting decision-making. Moreover, ongoing maintenance and updates of AI systems are crucial to ensure their effectiveness, requiring a commitment from the development team to continually enhance their AI capabilities.
  • Pregunta: Where can I buy AI-Assisted Programming: Better Planning, Coding, Testing, and Deployment 1st Edition?

    Respuesta: You can buy AI-Assisted Programming: Better Planning, Coding, Testing, and Deployment 1st Edition on Ubuy in Nicaragua. Ubuy offers a user-friendly experience with a wide range of products, making it a convenient choice for all your purchasing needs.

Intelligence & Semantics Editorial Review

**** "AI-Assisted Programming: Better Planning, Coding, Testing, and Deployment" by Tom Taulli has garnered a largely positive reception, particularly from those working in the IT field. Many readers appreciate the book's clear and fluid writing style, allowing them to absorb the material quickly. It presents a thorough overview of how artificial intelligence can enhance various aspects of programming, making it accessible for both novices and seasoned developers alike. The book shines in its practical approach, offering actionable insights on integrating AI tools into the software development lifecycle—from planning and coding to testing and deployment. Many users find the modular structure beneficial for learning about different AI development tools, giving them the flexibility to focus on the areas most relevant to their needs. In particular, the inclusion of AI-generated code samples and discussions on low-code/no-code platforms adds to its educational value. However, it’s important to note that not all reviews are uniformly positive. Some readers expressed disappointment with the book's quality, citing issues with low-resolution screenshots and a perception that certain content felt repetitive or derived from vendor marketing rather than original insights. Despite these critiques, most agree that the book serves as a valuable resource for software developers looking to adapt to the rapid changes brought by AI technologies in programming. In summary, "AI-Assisted Programming" is regarded as an insightful and timely guide, making it a recommended read for anyone involved in software development and eager to leverage AI for improved productivity and effectiveness. **

Customer Reviews & Ratings

25 valoraciones de los clientes
  • 5 estrella
    73%
  • 4 estrella
    5%
  • 3 estrella
    4%
  • 2 estrella
    9%
  • 1 estrella
    9%

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ventajas

  • Clear and fluid writing style.
  • Valuable insights for both beginners and experienced developers.
  • Practical advice on integrating AI tools into the software development lifecycle.
  • Modular methodology allows focused learning on relevant topics.
  • Inclusion of AI-generated code samples.

Contras

  • Some content deemed low-quality or repetitive.

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características y beneficios

  • Learn to use AI tools for efficient coding and development.
  • Suitable for both beginners and experienced developers.
  • Covers a variety of AI tools, from LLMs to code-specific systems.
  • Provides methodologies for modular programming with AI integration.
  • Focuses on the software development lifecycle: planning, coding, testing, and more.
  • Explains prompt engineering and low-code/no-code solutions for easier programming.

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