Anthropic's internal teams are transforming their workflows with Claude Code, enabling developers and non-technical staff to tackle complex projects, automate tasks, and bridge skill gaps that previously limited their productivity.
To learn more, we spoke with the following teams:
Data infrastructure Product development Security engineering Inference Data science and visualization Product engineering Growth marketing Product design Reinforcement learning (RL) engineering Legal Through these interviews, we've gathered insights on how different departments use Claude Code, its impact on their work, and tips for other organizations considering adoption.
Claude Code for data infrastructure The Data Infrastructure team organizes all business data for teams across the company. They use Claude Code for automating routine data engineering tasks, troubleshooting complex infrastructure issues, and creating documented workflows for technical and non-technical team members to access and manipulate data independently.
Main Claude Code use cases Kubernetes debugging with screenshots
When Kubernetes clusters went down and weren't scheduling new pods, the team used Claude Code to diagnose the issue. They fed screenshots of dashboards into Claude Code, which guided them through Google Cloud's UI menu by menu until they found a warning indicating pod IP address exhaustion. Claude Code then provided the exact commands to create a new IP pool and add it to the cluster, bypassing the need to involve networking specialists.
Plain text workflows for finance team
Engineers showed Finance team members how to write plain text files describing their data workflows, then load them into Claude Code to get fully automated execution. Employees with no coding experience could describe steps like "query this dashboard, get information, run these queries, produce Excel output," and Claude Code would execute the entire workflow, including asking for required inputs like dates.
Codebase navigation for new hires
When new data scientists join the team, they're directed to use Claude Code to navigate their massive codebase. Claude Code reads their Claude.md files (documentation), identifies relevant files for specific tasks, explains data pipeline dependencies, and helps newcomers understand which upstream sources feed into dashboards. This replaces traditional data catalogs and discoverability tools.
End-of-session documentation updates
The team asks Claude Code to summarize completed work sessions and suggest improvements at the end of each task. This creates a continuous improvement loop where Claude Code helps refine the Claude.md documentation and workflow instructions based on actual usage, making subsequent iterations more effective.
Parallel task management across multiple instances
When working on long-running data tasks, the team opens multiple instances of Claude Code in different repositories for different projects. Each instance maintains full context, so when they switch back after hours or days, Claude Code remembers exactly what they were doing and where they left off, enabling true parallel workflow management without context loss.
Team impact Resolved infrastructure problems without specialized expertise
Resolves Kubernetes cluster issues that would normally require pulling in systems or networking team members, using Claude Code to diagnose problems and provide exact fixes.
Accelerated onboarding
New data analysts and team members can quickly understand complex systems and contribute meaningfully without extensive guidance.
Enhanced support workflow
Claude Code can process much larger data volumes and identify anomalies (like monitoring 200 dashboards) that would be impossible for humans to review manually.
Enabled cross-team self-service
Finance teams with no coding experience can now execute complex data workflows independently.
Top tips from the Data Infrastructure team Write detailed Claude.md files
According to the team the better you document your workflows, tools, and expectations in Claude.md files, the better Claude Code performs. This makes Claude Code excel at routine tasks like setting up new data pipelines when you have existing design patterns.
Use MCP servers instead of CLI for sensitive data
They recommend using MCP servers rather than the BigQuery CLI to maintain better security control over what Claude Code can access, especially for handling sensitive data that requires logging or has potential privacy concerns.
Share team usage sessions
The team held sessions where members demonstrated their Claude Code workflows to each other. This helped spread best practices and showed different ways to use the tool they might not have discovered on their own.

Anthropic's internal teams are transforming their workflows with Claude Code, enabling developers and non-technical staff to tackle complex projects, automate t

How Anthropic teams use Claude Code