How Braintrust turns customer requests into code with Codex
How Braintrust engineers use Codex with GPT-5.5 to run experiments and code faster.
Fast Company AI·
For decades, software engineering has relied on something surprisingly fragile: veteran developers passing down institutional knowledge from person to person. As AI transforms how code gets written and maintained, that culture of inherited memory may be starting to break apart.
Read full articleHow Braintrust engineers use Codex with GPT-5.5 to run experiments and code faster.
Instead of relying solely on human auditors, developers may increasingly use AI to mathematically prove code behaves correctly.
While generative AI has shown promising results in advancing software engineering, its inclusion within end-user applications is a different story. Features labeled as AI continue to pop up across every UI, but they’re not always helpful or useful. Often driven by hype, they can become a distraction, or worse, a productivity killer. “Many fall into the trap of tacking on AI capabilities to cash in on the hype rather than because they solve a real, tangible user problem,” says Jody Bailey, chief product and technology officer at Stack Overflow. “The results are brittle features that introduce bugs, create security gaps, or disrupt workflows.” As a result, end users are souring on “AI everywhere, all the time.” Only 8% of Americans would pay extra for AI, according to ZDNET-Aberdeen research. Amid rising AI slop concerns and growing consumer pushback, The Wall Street Journal reports that companies are becoming more cautious about how they promote AI in products. “The biggest anti-pattern
New tools let its AI connect conversations with live enterprise data, giving workers and agents deeper access to organizational memory.
Infosys said the integration will be used to help its clients modernize software development, automate workflows and deploy AI systems, initially focusing software engineering, legacy modernization, and DevOps.
The week’s largest round was a $650 million financing for electric pickup truck maker Slate Auto. Other sizable investments went to spaces including drug development, autonomous public transit and software engineering.
There's a lot more code—but it's a lot more expensive and requires a lot more rewriting.
Anthropic has today released a new, improved Claude model, Opus 4.7, but has deliberately built it to be less capable than the highly-anticipated Claude Mythos. Anthropic calls Opus 4.7 a “notable improvement” over Opus 4.6, offering advanced software engineering capabilities and improved visioning, memory, instruction-following, and financial analysis. However, the yet-to-be-released (and inadvertently leaked) Mythos seems to overshadow the Opus 4.7 release. Interestingly, Anthropic itself is downplaying Opus 4.7 to an extent, calling it “not as advanced” and “less broadly capable” than the Claude Mythos Preview. The Opus upgrade also comes on the heels of the launch of Project Glasswing, Anthropic’s security initiative that uses Claude Mythos Preview to identify and fix cybersecurity vulnerabilities. “For once in technological history, a product is being released with a marketing message that is focused more on what it does not do than on what it does,” said technology analyst Carmi