Tag: AI Software Engineering
Waterfall 2.0: Controlling LLM-Driven Software Development with Stage-Gated Discipline
Georgy Starikov | | ADRs, Agile vs Waterfall, AI coding, AI development lifecycle, AI Software Engineering, AI-assisted engineering, architecture decision records, combi-shaper, engineering workflows, generative AI development, knowledge corpus, LLM engineering, LLM software development, MCP, Model Context Protocol, software architecture, software testing, system design, Waterfall 2.0Waterfall 2.0 reimagines classic stage-gated software development for the LLM era, combining fast AI generation with structured validation, cheap backtracking and a shared knowledge corpus ...
Google’s Next Coding Agent Could Change How Developers Think About Their Work
Tom Smith | | agentic coding, AI Software Engineering, autonomous coding agents, Gemini 3.1 Pro, Google I/O 2026, Google Jules V2, KPI-Driven Development, Outcome-Driven Development, Project Jitro, Software Lifecycle AutomationGoogle’s internal Project Jitro marks the evolution of the Jules coding agent from a task-executor to an outcome-driven collaborator. By shifting from manual prompting to KPI-driven development, Jitro autonomously identifies and executes ...
Meta Introduces Confucius Code Agent: A New Approach to AI-Powered Software Engineering
Tom Smith | | Agent Architecture, Agent Experience, AI coding assistants, AI Development Systems, AI Software Engineering, code refactoring, Confucius SDK, developer experience, Hierarchical Working Memory, Modular Interfaces, Performance Evaluation, Persistent Memory, Problem-Solving Styles., software development, SWE-Bench-Pro Benchmark, Tool Management, user experienceExplore the Confucius Code Agent by Meta and Harvard, designed to enhance productivity in software engineering with a focus on agent architecture and operational performance ...
