#Generative AI
7 articles
4 Books on Software Development in the Generative AI Era (Prompts, Context, and AI Coding)
A reading list of 4 books for putting generative AI to work in development: prompt engineering, context engineering, AI coding in practice, and how to create value with generative AI. Each entry links to its full review.
Creating Value in the Age of Generative AI
A review of Creating Value in the Age of Generative AI. Going beyond the tooling question of how to use generative AI, it addresses how to create value in the generative AI era from a practitioner's viewpoint. Organized around mindset, skills, data, and use cases, it centers on the thinking that connects technology to organizational and business outcomes.
Beyond Vibe Coding
A review of Beyond Vibe Coding. Looking past 'vibe coding'-letting AI write code-it covers how to make real use of AI in practice, presenting practices for embedding AI into the whole development workflow rather than treating it as a mere code generator, and offering a map of how review, testing, and refactoring change in the AI era.
Context Engineering
A review of Context Engineering. It focuses on how to design the context you give an LLM. Beyond wording prompts, it covers choosing and structuring the information you pass in and combining it with retrieval and memory. Closely tied to the challenges of building RAG and agents, it offers a perspective for lifting ad hoc tweaks into reproducible engineering.
Prompt Engineering for LLMs
A review of Prompt Engineering for LLMs. An O'Reilly book that systematically organizes prompt engineering. Rather than a grab-bag of tricks, it explains from the principles of why a prompt works. Through tokenization, few-shot prompting, and output evaluation, it turns prompting from experience and intuition into something you can design.
What Is AI-DLC (AI-Driven Development Life Cycle)?
An article organizing what AWS's AI-DLC (AI-Driven Development Life Cycle) is. Positioning AI as a central collaborator in development, it explains its two pillars, AI executes while humans supervise and dynamic team collaboration, and the mental model of rapidly iterating planning, alignment, and implementation, contrasted with the traditional SDLC.
Generative AI and the Career of Software Engineers
The rapid evolution of generative AI is bringing significant changes to society. As a software engineer, anticipating these technological changes is crucial.