Engineering at Anthropic: Inside the team building reliable AI systems
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Redesigning source control at Anthropic
As our merges per day grew more than tenfold, source control became our biggest development bottleneck. Here, we share how we migrated to an in-house version control system in five months.
How we contain Claude across products
An update on recent Claude Code quality reports
Scaling Managed Agents: Decoupling the brain from the hands
How we built Claude Code auto mode: a safer way to skip permissions
Harness design for long-running application development
Eval awareness in Claude Opus 4.6’s BrowseComp performance
Quantifying infrastructure noise in agentic coding evals
Building a C compiler with a team of parallel Claudes
Designing AI-resistant technical evaluations
Demystifying evals for AI agents
Effective harnesses for long-running agents
Introducing advanced tool use on the Claude Developer Platform
Code execution with MCP: Building more efficient agents
Beyond permission prompts: making Claude Code more secure and autonomous
Equipping agents for the real world with Agent Skills
Effective context engineering for AI agents
A postmortem of three recent issues
Writing effective tools for agents — with agents
Desktop Extensions: One-click MCP server installation for Claude Desktop
How we built our multi-agent research system
Claude Code: Best practices for agentic coding
The "think" tool: Enabling Claude to stop and think in complex tool use situations
Raising the bar on SWE-bench Verified with Claude 3.5 Sonnet
Building effective agents