News and Tech Update

Anthropic is removing a step most developers were skipping anyway. Starting August 14, Claude Code will run in auto mode by default for Pro, Max, and Team plan users, cutting back the steady stream of permission prompts that ask developers to approve each action the AI agent wants to take. The company first tested auto mode back in March, framing it as a middle ground between speed and control. Instead of stopping to ask permission for every command, auto mode routes each tool call through a classifier that only interrupts when an action looks irreversible, destructive, or aimed outside the user’s own environment. Everything else runs without a pause. The timing tracks with a pattern Anthropic says it’s seeing across its own usage data: People don’t actually review most permission prompts. According to the company’s blog post announcing the change, users approve 97% of permission requests in Claude Code. That’s not evidence people are carefully checking e...

DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted as part of an effort to better serve our audience. Our goal in these challenging economic times is to make it just that much easier for DevOps professionals to advance their careers. Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role, it tends to create opportunities for others. The ten job postings shared this week are selected based on the company looking to hire, the vertical industry segment and naturally, the pay scale being offered. We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration. Dice Booz Allen Hamilton McLean, VA DevOps Engineer $77,600 to $176,000 Alarm.com Centennial, CO DevOps Engineer $120,000 to $130,000 HarbourVest Partners Boston, MA DevOps Engineer $135,00...

AI coding assistants write code fast. Whether that code can be trusted is a separate question, and it’s becoming a more urgent one. Surveys this year put average developer trust in AI-generated output at just above the midpoint of a five-point scale, and more than half of developers admit they ship AI code without testing it first. Coverage numbers on AI-written code often look fine on paper, but plenty of that coverage turns out to be shallow: tests that check a result isn’t null and call it a day. Microsoft is trying to close that gap with a new open-source agent built specifically for unit testing. Called code-testing-generator , it lives inside the dotnet-test plugin in the dotnet/skills repository, and it’s designed to answer the questions a bare “generate unit tests” prompt leaves open: which code needs coverage, what framework the project already uses, where new tests belong, and whether the build will actually find them. That last point matters ...

HackerOne has added a remediation capability to its H1 Platform that reduces the amount of time required to remediate validated vulnerabilities and other weaknesses affecting specific lines of source code. Nidhi Aggarwal, chief product officer for HackerOne, said H1 Remediation combines artificial intelligence (AI) and crowdsourced research to identify the root cause of issues that are traced back to specific lines of code. Designed to integrate with existing issue tracking tools and AI coding agents via a Model Context Protocol (MCP) server, the goal is to better prioritize remediation efforts in a way that reduces the amount of exposure debt that continues to increase as advanced AI models discover many more vulnerabilities in code, said Aggarwal. Reports generated, in addition to root cause analysis, also detail exactly where a risky input enters the code and the resulting damage caused, language-specific code change suggestions, business context, and implementation guidance. Add...

We’re in the middle of a reliability reckoning. Thanks to AI, companies are shipping code much faster than before. But if there’s anything to learn from the surge in high-profile outages over the last couple of years, it’s that with more code comes more reliability risks. And when those risks do lead to an outage, the impact can be a whole different order of magnitude. It’s like driving around a race track. At low speeds, it’s quick and easy to recover from a spinout. But when you’re going significantly faster, a single slip-up can spell catastrophe. The nature of these risks is also changing. With AI code, we’re less likely to find typos but more likely to find unplanned dependencies, configuration drift, or infrastructure changes due to AI agents not having the proper context. Any company that cares about its reliability needs to implement AI reliability guardrails: automated feedback loops that safely create real failure conditions to validate resilience, propose solutions for an...

In an effort to catch up with OpenAI and Anthropic in one of AI’s fastest-growing markets, Meta has launched its first AI coding agent, Muse Code, alongside an updated coding-focused AI model. CEO Mark Zuckerberg announced the preview release of Muse Code, describing it as a tool that can handle software engineering tasks from planning code changes to writing software and validating the results. The release also includes Muse Spark 1.2 , an updated version of Meta’s foundation model that has been optimized for coding workloads. The products come from Meta Superintelligence Labs, the AI division led by Chief AI Officer Alexandr Wang. Wang joined Meta as part of Zuckerberg’s effort to jumpstart the company’s AI development after its earlier models struggled to match rivals in several key benchmarks, particularly software development. Coding assistants are a highly competitive segment of generative AI. Products from OpenAI and Anthropic have demonstrated that AI...