OpenAI, Google, and Anthropic are dominating the software world. Writing code has been a major application for AI even before discussions around AI became mainstream. In spring 2021, Microsoft launched GitHub Copilot in collaboration with OpenAI, aiming to help developers by suggesting code snippets. Despite being a preliminary version, it gained over a million interested developers.
Large language models (LLMs) have the potential to simplify and accelerate software development due to the structured nature of coding and the extensive documentation available online. Initially, LLMs were expected to help write code faster by predicting text, but soon, the vision extended to LLMs potentially handling much of the coding work.
The tech industry had long pursued “low code” and “no code” solutions, allowing users to create software without complex coding knowledge. AI coding tools presented a business opportunity: reducing costs by lowering the need for developers and speeding up product creation. Companies like Cursor and Windsurf raised significant funding, while OpenAI, Google, and Anthropic developed new tools for developers.
Initially, AI coding tools required extensive checks to ensure accuracy. In late 2023, programmer Simon Willison likened LLMs to “weird coding interns,” highlighting both their potential and their shortcomings. By early 2025, Anthropic’s Claude Code began to make more impactful contributions to coding, prompting discussions about AI’s growing role in development.
By late 2025, Anthropic’s Claude LLM Opus 4.5 version demonstrated significant improvement, capturing developers’ attention by transforming prompts into functional prototypes. AI tools like OpenAI’s Codex and Google’s Gemini model have also advanced, making AI coding a key business area.
AI-generated code offers a mainstream use case with lucrative business prospects. Companies like Anthropic experienced revenue surges, with OpenAI aiming to compete strongly in this space. Both firms are considering public offerings, driven by the necessity to yield returns on their substantial investments.
Silicon Valley firms are increasingly integrating AI, leading to potential productivity gains and workforce reductions. As AI coding tools evolve, they could reshape the industry, reducing the need for external software and instigating a surge of AI-native startups.
While AI tools mark progress, they still pose challenges, from requiring familiarity with coding environments to privacy and security concerns. Companies like Anthropic are exploring how to simplify AI usage, while products like Perplexity Computer could potentially overhaul device interactions.
Emerging trends indicate possible widespread changes, with companies envisioning scaled-down workforces empowered by advanced AI tools. In contrast, AI coding tools continue to advance, some predicting further disruption in the software valuation and business landscape. Meanwhile, products like Claude Cowork are focusing on making these tools more user-friendly and broadly accessible.