AI-driven coding assistants have attracted nearly $1 billion in funding since the beginning of last year, signaling that software engineering may be emerging as the first “killer app” for generative artificial intelligence.
Companies like Replit, Anysphere, Magic, Augment, Supermaven, and Poolside AI have raised $433 million this year alone, bringing the total to $906 million since January 2023, according to Dealroom data.
This surge in investment highlights that computer programming is likely the first profession to be significantly transformed by the latest advancements in AI technology.
“Today, software engineering and coding are the most impacted areas by AI,” said Hadi Partovi, CEO of the education non-profit Code.org and a seasoned Silicon Valley investor who has advised companies like Airbnb, Uber, Dropbox, and Facebook. “At this point, doing software engineering without AI is like writing without a word processor.”
While Silicon Valley’s growing confidence in AI’s impact on coding contrasts with some investors’ skepticism about the economic benefits of generative AI, and the potential returns on Big Tech’s massive investment into AI infrastructure over the next few years, the momentum is clear.
Hannah Seal, a partner at Index Ventures, which has invested in start-up Augment alongside figures like Eric Schmidt, noted that “it’s much easier to monetize AI when you can embed your product into an existing workflow and make the benefits immediately visible.”
For AI tools to be profitable, Seal emphasized the importance of assessing “time to value” and “how meaningful that value-add is.” With coding co-pilots, she added, “the answer is very clear.”
The excitement around AI has spurred start-ups and tech giants like Microsoft, Amazon, Meta, and Google to compete in a crowded field, developing AI assistants capable of writing and editing code.
An executive on Code.org’s board, which includes Amazon’s head of e-commerce David Treadwell and Microsoft’s chief technology officer Kevin Scott, recently informed Partovi that their company plans to stop hiring coders who don’t use AI by the end of the year.
The easier programming becomes, the higher the demand grows because it enables the creation of much more technology,” Partovi remarked.
GitHub, owned by Microsoft and the world’s largest software development platform, was among the first to leverage a large language model—similar to the technology behind ChatGPT that generates text, images, or code—into a coding assistant.
“When we first used GPT-3, OpenAI’s initial major model, we quickly realized its exceptional ability to write code, which led us to develop a product around it,” said Thomas Dohmke, CEO of GitHub, which Microsoft acquired for $7.5 billion in 2018.
This initial experiment evolved into GitHub Copilot, an AI-powered coding assistant launched in 2022, which now boasts nearly 2 million paying subscribers. “Today, the model writes better code than the average developer,” Dohmke noted.
As of April, GitHub’s revenue had surged by 45% year-on-year, with its annual revenue run rate reaching $2 billion at the beginning of this month, according to Microsoft CEO Satya Nadella.
“Copilot contributed over 40% of GitHub’s revenue growth this year and has already become a larger business than GitHub was at the time of our acquisition,” Nadella said during a July 30 earnings call.
More than 77,000 organizations—including BBVA, FedEx, H&M, Infosys, and Paytm—have adopted Copilot since its launch, reflecting a 180% increase year-on-year, Nadella added.
However, IT departments in large companies remain cautious about the security risks of using automated programming tools to generate production-grade code. Dohmke emphasized that AI-generated code should not be deployed without manual oversight.
“On average, we observe 20-35% productivity gains from enterprises that have shared internal data,” Dohmke said, citing customers like Latin American e-commerce giant Mercado Libre and professional services firm Accenture.
A McKinsey report from last year estimated that AI could directly boost software engineering productivity by 20-45% of current annual spending, with benefits including generating initial code drafts, code correction, and refactoring.
“By accelerating the coding process, generative AI could shift the necessary skill sets in software engineering toward code and architecture design,” McKinsey stated.
Software engineers have already integrated AI assistants into their daily workflows, finding that these tools not only speed up their work but also enhance creativity.
“I personally code every day with GitHub Copilot, often alongside ChatGPT,” said Marc Tuscher, a deep learning scientist and CTO of Sereact, a German robotics start-up.
Tuscher finds GitHub’s tool particularly useful for “repetitive tasks” like user interfaces and backend development, while he turns to ChatGPT for more abstract problem-solving.
“ChatGPT provides classical ideas, introduces new research papers, and then I can ask, ‘How would this be done in Python?’ and it generates the code,” Tuscher explained. “Both tools are incredibly powerful.”
While nearly all the programmers he knows use these tools, fundamentally changing how they work, Tuscher emphasized that these AI assistants are powerful helpers rather than replacements for coders.
“No generative AI understands good software architecture or how to design systems—that’s still something we have to figure out ourselves,” he added.