Source: https://internal-agents.com/agents/databricks-costar # Databricks — coSTAR and internal engineering agents Databricks runs internal engineering agents for work such as on-call support and automated code review. coSTAR ships and tests them, using LLM judges as the test suite and a coding assistant to refine the agent until the judges pass. Databricks' open-source Omnigent is a separate product. - Approach type: Agent system - Deployment stage: Scaled - Autonomy: Unknown - Evidence strength: Detailed primary - Status: Internal - First reported year: 2025 - Work: Coding, Code review, On-call - Invocation: Interactive, Background - Entry reviewed: 2026-09-15 ## Where people stay involved - **internal engineering workflows → agent-produced changes** — Unknown · Level unknown ## Overview ### Summary Databricks runs internal engineering agents for work such as on-call support and automated code review. coSTAR ships and tests them, using LLM judges as the test suite and a coding assistant to refine the agent until the judges pass. Databricks' open-source Omnigent is a separate product. Fact · Reported · High confidence · `databricks-costar--summary` Confidence reason: A linked first-party source states the claim. Evidence: - Supports · [1] [coSTAR: how we ship AI agents at Databricks fast](https://www.databricks.com/blog/costar-how-we-ship-ai-agents-databricks-fast-without-breaking-things) · [Preserved copy](https://github.com/steel-experiments/internal-agents-map/blob/main/archive/sources/databricks-costar-source-1/content.md) - Supports · [2] [Benchmarking coding agents on a multi-million line codebase](https://www.databricks.com/blog/benchmarking-coding-agents-databricks-multi-million-line-codebase) · [Preserved copy](https://github.com/steel-experiments/internal-agents-map/blob/main/archive/sources/databricks-costar-source-2/content.md) ## Supervision evidence ### Operating model assessment Unclassified for internal engineering workflows → agent-produced changes; human attention boundary: unknown. Inference · Catalog judgment · Unverified confidence · `databricks-costar--operating-models-0` Confidence reason: The record covers several internal engineering agents with different workflows, so no single human-attention boundary applies. Qualifications: - Observation date: 2025 Evidence: - Supports · [1] [coSTAR: how we ship AI agents at Databricks fast](https://www.databricks.com/blog/costar-how-we-ship-ai-agents-databricks-fast-without-breaking-things) · [Preserved copy](https://github.com/steel-experiments/internal-agents-map/blob/main/archive/sources/databricks-costar-source-1/content.md) ## Implementation details ### Harness coSTAR framework for shipping and testing internal agents Fact · Reported · High confidence · `databricks-costar--architecture-harness` Confidence reason: A linked first-party source states the claim. Evidence: - Supports · [1] [coSTAR: how we ship AI agents at Databricks fast](https://www.databricks.com/blog/costar-how-we-ship-ai-agents-databricks-fast-without-breaking-things) · [Preserved copy](https://github.com/steel-experiments/internal-agents-map/blob/main/archive/sources/databricks-costar-source-1/content.md) ### Knowledge Private benchmark built from the Databricks multi-million line codebase Fact · Reported · High confidence · `databricks-costar--architecture-knowledge` Confidence reason: A linked first-party source states the claim. Evidence: - Supports · [2] [Benchmarking coding agents on a multi-million line codebase](https://www.databricks.com/blog/benchmarking-coding-agents-databricks-multi-million-line-codebase) · [Preserved copy](https://github.com/steel-experiments/internal-agents-map/blob/main/archive/sources/databricks-costar-source-2/content.md) ## Reported outcomes and statements ### Key observation Internal agents serve as daily coding drivers on the Databricks codebase Fact · Reported · Medium confidence · `databricks-costar--key-metrics-0` Confidence reason: Databricks described internal use in its own engineering blog. Evidence: - Supports · [1] [coSTAR: how we ship AI agents at Databricks fast](https://www.databricks.com/blog/costar-how-we-ship-ai-agents-databricks-fast-without-breaking-things) · [Preserved copy](https://github.com/steel-experiments/internal-agents-map/blob/main/archive/sources/databricks-costar-source-1/content.md) ### Key observation Private benchmark built from a multi-million line codebase Fact · Reported · Medium confidence · `databricks-costar--key-metrics-1` Confidence reason: Databricks described the benchmark in its own engineering blog. Evidence: - Supports · [2] [Benchmarking coding agents on a multi-million line codebase](https://www.databricks.com/blog/benchmarking-coding-agents-databricks-multi-million-line-codebase) · [Preserved copy](https://github.com/steel-experiments/internal-agents-map/blob/main/archive/sources/databricks-costar-source-2/content.md) ## Sources 1. [coSTAR: how we ship AI agents at Databricks fast](https://www.databricks.com/blog/costar-how-we-ship-ai-agents-databricks-fast-without-breaking-things) - Engineering blog · First party · Evidence - Original URL: - Accessed: 2026-08-13 · Last verified: 2026-08-31 - Preserved copy in the repository: 2. [Benchmarking coding agents on a multi-million line codebase](https://www.databricks.com/blog/benchmarking-coding-agents-databricks-multi-million-line-codebase) - Engineering blog · First party · Evidence - Original URL: - Accessed: 2026-08-13 · Last verified: 2026-08-31 - Preserved copy in the repository: