“AI-Powered Coding Pulls in Almost $1bn of Funding to Claim ‘Killer App’ Status”, 2024-08-23 (; similar):
AI-driven coding assistants [mostly code completion] have amassed nearly $1b of funding since the start of last year, a signal that software engineering is becoming the first “killer app” for generative artificial intelligence.
Companies such as Replit, Anysphere, Magic, Augment, Supermaven and Poolside AI raised $433m so far this year alone, bringing the total since January 2023 to $906m, according to Dealroom.
The rush to pour money into AI coding assistants is an indication that computer programming is the first job function to be transformed by the latest wave of AI technology.
“Today, software engineering and coding is the number-one area impacted by AI”, said Hadi Partovi [twin of Ali Partovi], chief executive of education non-profit organization Code.org and a long-time Silicon Valley investor and adviser to Airbnb, Uber, Dropbox and Facebook. “At this point, software engineering without AI is a little bit like writing without a word processor.”
…Hannah Seal, a partner at Index Ventures, which has invested in start-up Augment, alongside Eric Schmidt and others, said it was “much easier to monetize AI if you can embed your product into an existing workflow, and make the benefit instantly visible”. For AI tools to make money, the questions for Seal are: “What is the time to value, and how meaningful is that value-add?”, while she added that “with coding co-pilots, the answer is very clear”. AI enthusiasm has prompted start-ups and tech giants Microsoft, Amazon, Facebook and Google to vie for dominance in a crowded sector, building AI assistants and agents that can write and edit computer code.
An executive on Code.org’s board, which includes David Treadwell, Amazon’s head of ecommerce, and Kevin Scott, Microsoft’s chief technology officer, recently told Partovi their company would stop hiring people who code without AI by the end of the year, he said. “The easier [programming] becomes, the more demand goes up, because so much more technology can be built”, Partovi added.
Microsoft-owned GitHub, the world’s biggest software development platform, was one of the first to turn a large language model—software that underpins ChatGPT, which can generate text, images or code—into a coding assistant.
“When using GPT-3, OpenAI’s first major model, we figured out relatively quickly that it was so good at writing code that we could build a product around this”, said Thomas Dohmke, chief executive of GitHub, which was acquired for $7.5b by Microsoft in 2018.
The prototype turned into GitHub Copilot, an AI coding assistant that was launched widely in 2022 and has nearly 2m paying subscribers. “Now, the model writes better code than the average developer”, Dohmke said. As of April, GitHub’s revenue was up 45% year on year and, according to Microsoft chief executive Satya Nadella, its annual revenue run rate was $2b at the start of this month. “Copilot accounted for over 40% of GitHub revenue growth this year and is already a larger business than all of GitHub was when we acquired it”, he said on a July 30 earnings call. More than 77,000 organizations—from BBVA, FedEx and H&M to Infosys and Paytm—had adopted the two-year-old tool, Nadella said, a figure that showed a 180% rise year on year.
…“I personally code every day with GitHub Copilot, oftentimes alongside ChatGPT”, said Marc Tuscher, a deep learning scientist and chief technology officer of Sereact, a German robotics start-up. GitHub’s tool is most useful for “repetitive tasks”, such as for user interfaces and the back end of products, he added, while he uses ChatGPT to help with more abstract problem solving. “ChatGPT will come up with some classical ideas, some new papers and then you can ask, ‘how would this be done in Python?’ and it produces code”, Tuscher said. “Both tools are very, very cool.” While all programmers he knows use these products, and “it changes fundamentally how we work”, Tuscher said the tools were no more than powerful helpers, rather than replacements, for coders. “No GenAI knows about good software architecture, or how to put systems together”, he added. “That’s still the thing we have to think through ourselves.”