The human sciences are shifting: for the first time, core research tasks can be handed off to machines. AI chatbots increasingly contribute to scientific research, including in the most prestigious publications and in the social sciences. This has spurred optimism that AI could boost research productivity—while also stoking fears about overloaded peer review and a deluge of academic AI slop. But while turn-taking AI chatbots have primarily been used for writing assistance, coding agents could restructure social science research more radically. Agentic coding platforms like Claude Code and Code
Coding agents in the social sciences… Consider a five-server setup: GitHub: 35 tools ~26K tokens Slack: 11 tools ~21K tokens Sentry: 5 tools ~3K tokens Grafana: 5 tools ~3K tokens Splunk: 2 tools ~2K tokens That's 58 tools consuming approximately 55K tokens before the conversation even starts. …
… But only 20% have adopted coding agents—tools like Claude Code that autonomously write and execute analysis code—into their work. There are sharp disparities in use of coding agents. Twice as many researchers with typically male names use coding agents as those with female names. …
… In combination with other prompt changes, it hurt coding quality and was reverted on April 20. …
… Today, we’re releasing a set of connectors—tools that let Claude work alongside the software creative professionals rely on, so creatives can extend their reach. Connecting Claude to creative tools Connectors allow Claude to access other platforms and tools directly. …
… External attackers: The agent is attacked through external vectors such as tools, files, or network access. …
… Routine coding e.g. editing source files in your repo doesn't pay classifier latency; in-project edits are reviewable via version control. …
… Sonnet 4.6 brings much-improved coding skills to more of our users. …
… Claude now also works better with the office tools you already use. …
… This is especially important when using many similar tools. Test how the model uses your tools: Run many example inputs in our workbench to see what mistakes the model makes, and iterate. Poka-yoke your tools. …
… Finally, code can serve as both executable tools and as documentation. …