May 29, 2026
The AI as Social Actor Design Speculations for Reimagining Human – Thing Relationships
The AI as Social Actor Design Speculations for Reimagining Human – Thing Relationships | 10.07 MB
Title: The AI as Social Actor
Author: Bhuvaneswari Subramani
Category: Nonfiction, Computers, Advanced Computing, Artificial Intelligence
Language: English | 142 Pages | ISBN: 9798903423668
Description:
Artificial intelligence (AI) is reshaping everyday development work. AI-Driven Development Lifecycle (AI-DLC), invented and open-sourced by Amazon Web Services (AWS) in 2025, is a methodology in which AI takes part in each phase of the build while humans shape direction, review outcomes, and guide quality. Traditional SDLC depends on staged handoffs while AI-DLC brings humans and AI into one continuous flow. This book explains that shift in a simple and practical way. The AI-DLC approach shows how intent moves through stages and AI-Native rituals like Mob elaboration and mob construction for both brownfield and greenfield projects. Readers see how AI supports task decomposition, planning, code generation, refactoring, and validation in a way that reduces friction and improves flow. Two case studies outline how teams navigate legacy constraints and fresh builds, giving developers a close look at real-world decisions, prompt work, architecture choices, and review steps. The focus stays on easy adoption, predictable outcomes, and strong human judgment. Developers gain a grounded path to build reliable systems with speed, clarity, and confidence while staying fully in control of their work.
Artificial intelligence (AI) is reshaping everyday development work. AI-Driven Development Lifecycle (AI-DLC), invented and open-sourced by Amazon Web Services (AWS) in 2025, is a methodology in which AI takes part in each phase of the build while humans shape direction, review outcomes, and guide quality. Traditional SDLC depends on staged handoffs while AI-DLC brings humans and AI into one continuous flow. This book explains that shift in a simple and practical way. The AI-DLC approach shows how intent moves through stages and AI-Native rituals like Mob elaboration and mob construction for both brownfield and greenfield projects. Readers see how AI supports task decomposition, planning, code generation, refactoring, and validation in a way that reduces friction and improves flow. Two case studies outline how teams navigate legacy constraints and fresh builds, giving developers a close look at real-world decisions, prompt work, architecture choices, and review steps. The focus stays on easy adoption, predictable outcomes, and strong human judgment. Developers gain a grounded path to build reliable systems with speed, clarity, and confidence while staying fully in control of their work.
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