MENLO PARK: Meta has entered the fast-growing AI coding tools market with the launch of Muse Code, an artificial intelligence-powered coding assistant designed to help developers build and manage software projects.
The company announced on Wednesday that Muse Code is an “agentic coding tool” capable of handling complex software engineering tasks, including planning, writing and validating code using large amounts of data.
Agentic AI tools are designed to perform tasks with limited human intervention, although users typically continue to supervise operations and make final decisions.
Meta has launched Muse Code in beta, allowing developers to test the platform before a wider release.
Alongside the new tool, Meta also introduced an updated version of its flagship AI model, Spark 1.2, which it described as a coding-focused upgrade. The model will be available through Muse Code and Meta’s developer platform, Meta Model API.
The launch marks Meta’s latest move in the intensifying competition among major AI companies, including OpenAI and Anthropic, to dominate the market for AI-powered software development tools.
Meta has invested billions of dollars into its artificial intelligence division, now known as Meta Superintelligence Labs, as it attempts to strengthen its position in the AI race.
AI coding becomes a key battleground
Major technology companies are increasingly focusing on AI coding tools as businesses and software engineers show greater willingness to pay for automation solutions.
While consumer chatbots have attracted widespread attention since the launch of ChatGPT in late 2022, companies have been slower to pay for general-purpose AI assistants. However, demand for specialised coding tools has grown rapidly.
OpenAI said earlier this year that ChatGPT had reached 900 million weekly active users, including millions of paying business and consumer users.
Anthropic has not disclosed its total user numbers but has reported strong growth in paid subscriptions.
Other major players are also expanding their presence in AI development tools. Microsoft provides AI coding solutions through its Copilot ecosystem and GitHub, while Amazon and Alphabet are also investing heavily in AI infrastructure.
The global AI race has pushed technology companies to increase spending on data centres, chips and computing capacity, with major firms collectively expected to invest hundreds of billions of dollars in AI infrastructure.
Security concerns grow
The rapid advancement of autonomous AI systems has also raised concerns over cybersecurity risks.
Recent tests involving advanced AI models from OpenAI and Anthropic showed that autonomous systems could carry out cyber-related tasks, prompting debate among researchers about safety controls.
A Meta-developed model, Spark 1.1, was also reportedly involved in a similar incident, although a company spokesperson said the issue resulted from a configuration error at a third-party testing partner.
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