Tagged articles

AI-Native SDLC

6 articles · Page 1 of 1

Oct 15, 2026 · Artificial Intelligence

7-Layer Architecture for AI-Native SDLC: How Anthropic, OpenAI, GitHub & Kiro Map to the Stack

This article presents a 7-layer reference architecture for AI-native software development platforms, mapping capabilities from Anthropic, OpenAI, GitHub, and AWS Kiro across infrastructure, specifications, context engineering, agent orchestration, evaluation, production feedback, and governance layers, with a practical migration path from traditional DevOps.

7-layer architectureAI-Native SDLCContext Engineering

0 likes · 19 min read

7-Layer Architecture for AI-Native SDLC: How Anthropic, OpenAI, GitHub & Kiro Map to the Stack

Qborfy AI

Oct 14, 2026 · R&D Management

AI-Native SDLC: The Real Bottlenecks Beyond Code Generation

This article introduces AI-Native SDLC, explaining why code generation is no longer the bottleneck in software development and how the bottleneck has shifted to requirements specification, context management, verification, governance, and production feedback loops, outlining a 7-layer architecture, artifact-driven workflow, and a 9-part series roadmap.

AI-Native SDLCAgentic workflowContext Engineering

0 likes · 14 min read

AI-Native SDLC: The Real Bottlenecks Beyond Code Generation

Data Bricklaying Diary

Sep 17, 2026 · R&D Management

Closing the Loop: AI-Native SDLC Feeds Production Reality Back to R&D

This article explains how AI-native SDLC transforms production incidents into continuous development feedback by using deterministic detection for anomalies, AI-assisted diagnosis for evidence gathering, risk-tiered automation paths, protected regression tests from failures, and multi-layer asset updates — all while keeping humans accountable for decisions and releases.

AI-Native SDLCAI-assisted diagnosisR&D management

0 likes · 12 min read

Closing the Loop: AI-Native SDLC Feeds Production Reality Back to R&D

Data Bricklaying Diary

Sep 3, 2026 · R&D Management

AI Coding Accelerates, But R&D Process Emerges as New Bottleneck

As AI speeds up code generation, bottlenecks shift from coding to requirements clarity, design validation, verification evidence, and release accountability; the article argues for an AI-native SDLC built on authoritative artifacts, independent evidence, risk-based responsibility gates, and production feedback loops rather than simply adding agents to each phase.

AI-Native SDLCR&D ProcessSpec-Driven Development

0 likes · 12 min read

AI Coding Accelerates, But R&D Process Emerges as New Bottleneck

Architect

Aug 27, 2026 · R&D Management

Anthropic’s AI‑Native SDLC: From Planning and Design to Secure Production

Anthropic’s AI‑Native SDLC Playbook shows how agents can accelerate coding but also expose new challenges in intent definition, specification, verification, release gating, production monitoring, and permission management, illustrated with a payment‑duplicate‑callback case and internal productivity data.

AI-Native SDLCAgentClaude

0 likes · 19 min read

Anthropic’s AI‑Native SDLC: From Planning and Design to Secure Production

Fighter's World

Aug 26, 2026 · Artificial Intelligence

Beyond Code Generation: Coding Agents Now Compete on AI-Native SDLC

The article argues that code generation is no longer the bottleneck; competition among coding agents is shifting toward managing the entire AI-Native software development lifecycle — Plan, Design, Build, Test, Deploy, Maintain — using versioned artifacts, automated verification, governance gates, and context engineering, as raw model capabilities become commoditized.

AI-Native SDLCAI-assisted developmentAnthropic

0 likes · 50 min read

Beyond Code Generation: Coding Agents Now Compete on AI-Native SDLC