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This is a personal recollection on the Move fire on May 13, 1985
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| Artificial intelligence (AI) |
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| Glossary |
AI-assisted software development is the use of large language models (LLMs) and AI agents to assist software developers in software development. It can be used in a range of tasks, from writing source code to debugging, testing, and documentation[citation needed]. The practice can sometimes improve the velocity of software delivery, but at the cost of taking on substantive quality risks. [1]
LLMs trained or fine-tuned on source-code corpora can generate source code from natural-language descriptions, comments, or docstrings.[2][3] Research on code-generation systems often evaluates generated programs by functional correctness,[4] such as whether the output passes automated test cases[clarification needed].[5][6] Such tools can be features or extensions of integrated development environments (IDEs).[7]
Vibe coding is software development assisted by AI where the software developer describes a project or task in a prompt to an LLM that generates source code automatically. Vibe coding may involve accepting AI-generated code without thorough review of the output, instead relying on results and follow-up prompts to guide changes.[8][9]
The term was coined in February 2025 by computer scientist Andrej Karpathy, a co-founder of OpenAI and former AI leader at Tesla.[9] Merriam-Webster listed the term in March 2025 as a "slang & trending" expression.[10] It was named the Collins English Dictionary Word of the Year for 2025.[11][12]
Advocates of vibe coding say it allows amateur programmers to produce software without the extensive training and skills required for software engineering.[13][14] Critics point out a lack of accountability, maintainability, and an increased risk of introducing security vulnerabilities in the resulting software.[8][14]
AI agents using pre-trained and fine-tuned LLMs can propose code completion suggestions based on context. Code completion suggestions are small localized edits based on a partially written code fragment, usually at the level of a single line of source code. According to a 2025 literature review by Husein, Aburajouh & Catal in Computer Standards & Interfaces, "LLMs significantly enhance code completion performance across several programming languages and contexts, and their capability to predict relevant code snippets based on context and partial input boosts developer productivity substantially."[15]
LLM-based tools can be used to identify potential bugs and security vulnerabilities, and suggest fixes. AI can also be used to perform static code analysis and suggest potential performance improvements.[16][17]
Both ownership of and responsibility for AI-generated code is disputed.[18][19]
According to a report from the German Federal Office for Information Security, the use of AI coding assistants without careful oversight from experienced developers can introduce major security vulnerabilities or generate incorrect solutions (about 50% of the time), and any potential gain in productivity should be weighed against the cost of additional quality control and security measures.[20] The report also states that a programmer relying too much on AI coding assistants runs the risk of losing the skill to review and evaluate source code[20]. The report further states that AI coding assistants create novel vectors for cyberattack as well as a potential for exfiltration of confidential data for model training by the providers of AI coding assistants[20]. According to Deloitte, outputs from AI-assisted software development must be validated through a combination of automated testing, static analysis tools, and human review, creating a governance layer to improve quality and accountability.[21]
Multiple big tech companies have reported using AI for coding.
In the fall of 2024, about a quarter of Google's code was generated by AI. By the next fall, it was about half.[22] In April 2026, it was reported that roughly three quarters of new code created within Google was AI generated and then reviewed by human engineers.[22][23]
In April 2025, between 20% and 30% of the code for some of Microsoft's projects was written by AI.[22]
In April 2026, Snap said at least 65% of its new code was AI generated.[22]
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Large language models (LLMs) | |
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| Training, prompting, and alignment | |
| Models | |
| Chatbots and assistants | |
| Agents, coding, and applications | |
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| Hardware and infrastructure | |
| Benchmarks, evaluation, and detection | |
| Datasets and data | |
| Organizations | |
| People | |
| Social, economic, and governance | |
Source: Wikipedia. Article content is retrieved live through the MediaWiki API.
AI-assisted software development is the use of large language models (LLMs) and AI agents to assist software developers in software development. It can be used in a range of tasks, from writing source code to debugging, testing, and documentation. The practice can sometimes improve the velocity of software delivery, but at the cost of taking on substantive quality risks.
This is a list of AI-assisted software development tools which are tools used for AI-assisted software development, especially large language models and AI agents, to assist with software development tasks such as writing, editing, reviewing, testing, debugging, documenting, and understanding source code.
Claude is a series of large language models (LLMs) developed by American software company Anthropic. Claude was released as an AI-based chatbot in March 2023. It is also used in AI-assisted software development. Anthropic sells Claude-based agentic tools including Claude Code, a terminal coding agent, and Claude Cowork, a similar tool for non-programmers. Claude is trained using a constitution, a technique developed by Anthropic to improve ethical and legal compliance. Since Claude 3, each generation has typically been released in three sizes, named Haiku (the least capable), Sonnet, and Opus (the most capable). In 2026, a more capable model named Claude Mythos was released to a handful of companies and organizations; this was followed by the release of Claude Fable, a version of Mythos with stricter safeguards, to the general public. In February 2026, the United States Department of Defense designated Anthropic a "supply chain risk" and federal agencies were ordered to phase out Claude after the company refused to remove contractual prohibitions on using Claude for mass domestic surveillance and fully autonomous weapons. A federal judge blocked the designation in March 2026 and permanently set it aside in August 2026 as unconstitutional retaliation.
Devin AI is an AI-assisted software development tool created by Cognition Labs. It is designed to autonomously complete software development tasks. Devin AI has received both praise and skepticism regarding its capabilities and its implications for the future of artificial intelligence and software development.
Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.
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