Context overload slowed debugging. Seer now automates the hunt with 95% accuracy, creating merge-ready fixes nearly half the time.
A software monitoring platform ingesting billions of errors daily provides deep visibility by linking stack traces, profiling data, and trace connections.
The sheer volume of contextual data made it difficult for developers to pinpoint bugs quickly, especially for newer team members unfamiliar with the...
“Even for a simple issue, there's an incredible amount of context.”
Sentry's Automated debugging is part of this use case:
Application performance monitoring and error tracking platform for developers.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Related implementations across industries and use cases
Code fixes piled up in backlogs for months. Now, an autonomous Claude agent generates, tests, and submits validated pull requests.
Complex queries bottlenecked access to insights. Agents now translate plain language into expert dashboards and root cause analysis.
Manual testing couldn't keep pace. Now, AI agents validate code without scripts, cutting test durations by 60%.
Code fixes piled up in backlogs for months. Now, an autonomous Claude agent generates, tests, and submits validated pull requests.
Developers spent 10+ hours a week testing and documenting APIs. Now, an AI assistant automatically writes tests and updates specs.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Context overload slowed debugging. Seer now automates the hunt with 95% accuracy, creating merge-ready fixes nearly half the time.
A software monitoring platform ingesting billions of errors daily provides deep visibility by linking stack traces, profiling data, and trace connections.
The sheer volume of contextual data made it difficult for developers to pinpoint bugs quickly, especially for newer team members unfamiliar with the...
“Even for a simple issue, there's an incredible amount of context.”
Sentry's Automated debugging is part of this use case:
Application performance monitoring and error tracking platform for developers.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Related implementations across industries and use cases
Code fixes piled up in backlogs for months. Now, an autonomous Claude agent generates, tests, and submits validated pull requests.
Complex queries bottlenecked access to insights. Agents now translate plain language into expert dashboards and root cause analysis.
Manual testing couldn't keep pace. Now, AI agents validate code without scripts, cutting test durations by 60%.
Code fixes piled up in backlogs for months. Now, an autonomous Claude agent generates, tests, and submits validated pull requests.
Developers spent 10+ hours a week testing and documenting APIs. Now, an AI assistant automatically writes tests and updates specs.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.