How to use AI coding assistants without letting your hard-earned engineering skills wither away.
How to Do AI-Assisted Engineering
15 experienced engineers and engineering leaders share their real-world experiences with AI-assisted engineering.
AI Coding will Prevent Expertise | Lars Faye
The need for ongoing friction in long-term skill formation.
DrCatHicks/learning-opportunities
A Claude or Codex skill for deliberate skill development during AI-assisted coding
How I’d start my engineering career today
If you could start your engineering career over today, here’s what actually matters now that AI has made most coding skills nearly worthless.
SkillMD.ai - Discover & Create Agent Skills
The open directory for agent skills. Discover, create, and share SKILL.md files for AI coding assistants.
Agent Skills
AI coding agents take the shortest path to done, which usually means skipping the specs, tests, and reviews that make software reliable at scale. Agent Skill...
AI coding wisdom from the people who would know
Essays and threads from experienced developers who've gone deep on AI-assisted coding.
Usage, Effects and Requirements for AI Coding Assistants in the Enterprise: An Empirical Study
The rise of large language models (LLMs) has accelerated the development of automated techniques and tools for supporting various software engineering tasks, e.g., program understanding, code generation, software testing, and program repair. As CodeLLMs are being employed toward automating these tasks, one question that arises, especially in enterprise settings, is whether these coding assistants and the code LLMs that power them are ready for real-world projects and enterprise use cases, and how do they impact the existing software engineering process and user experience. In this paper we survey 57 developers from different domains and with varying software engineering skill about their experience with AI coding assistants and CodeLLMs. We also reviewed 35 user surveys on the usage, experience and expectations of professionals and students using AI coding assistants and CodeLLMs. Based on our study findings and analysis of existing surveys, we discuss the requirements for AI-powered coding assistants.
How to harness AI
"Coding agents" are complicated but intelligible
How AI Impacts Skill Formation
AI assistance produces significant productivity gains across professional domains, particularly for novice workers. Yet how this assistance affects the development of skills required to effectively supervise AI remains unclear. Novice workers who rely heavily on AI to complete unfamiliar tasks may compromise their own skill acquisition in the process. We conduct randomized experiments to study how developers gained mastery of a new asynchronous programming library with and without the assistance of AI. We find that AI use impairs conceptual understanding, code reading, and debugging abilities, without delivering significant efficiency gains on average. Participants who fully delegated coding tasks showed some productivity improvements, but at the cost of learning the library. We identify six distinct AI interaction patterns, three of which involve cognitive engagement and preserve learning outcomes even when participants receive AI assistance. Our findings suggest that AI-enhanced productivity is not a shortcut to competence and AI assistance should be carefully adopted into workflows to preserve skill formation -- particularly in safety-critical domains.
How AI Impacts Skill Formation
AI assistance produces significant productivity gains across professional domains, particularly for novice workers. Yet how this assistance affects the development of skills required to effectively supervise AI remains unclear. Novice workers who rely heavily on AI to complete unfamiliar tasks may compromise their own skill acquisition in the process. We conduct randomized experiments to study how developers gained mastery of a new asynchronous programming library with and without the assistance of AI. We find that AI use impairs conceptual understanding, code reading, and debugging abilities, without delivering significant efficiency gains on average. Participants who fully delegated coding tasks showed some productivity improvements, but at the cost of learning the library. We identify six distinct AI interaction patterns, three of which involve cognitive engagement and preserve learning outcomes even when participants receive AI assistance. Our findings suggest that AI-enhanced productivity is not a shortcut to competence and AI assistance should be carefully adopted into workflows to preserve skill formation -- particularly in safety-critical domains.
Why Software Engineering Is Indispensable in the Age of Coding Agents
Can AI make Software Engineering (SE) -- the discipline -- obsolete? And can it make software engineers -- the professionals -- redundant? This paper argues that the rise of capable AI coding...
Why AI hasn’t replaced software engineers, and won’t
Coding agents as normal technology
How AI assistance impacts the formation of coding skills
A randomized trial with 52 developers found AI assistance lowered comprehension scores, except when used for explanations rather than delegation.
Running an AI-native engineering org | Claude
How the Claude Code engineering team’s processes and structure changed once agentic coding became the default way of working.
