Blog

We present SWE-Gym, the first environment for training real-world software engineering (SWE) agents. SWE-Gym contains 2,438 real-world Python task instances, each comprising a codebase with an executable runtime environment, unit tests, and a task specified in natural language. We use SWE-Gym to train language model based SWE agents, achieving up to 19% absolute gains in …

Read more “Training Software Engineering Agents and Verifiers with SWE-Gym”

As generative AI applications grow in sophistication, development workflows become more fragmented. Although AI can be a force multiplier, teams may design prompts in one environment, manage versions in spreadsheets or text files, and then manually integrate them into their code. This leads to inefficiencies, versioning chaos, and collaboration bottlenecks.  Vertex AI Studio is designed …

Read more “Announcing prompt management in the Vertex AI SDK”

We’re rolling out significant updates to Veo that give people even more creative control.

We present an approach to software testing automation using Agentic Retrieval-Augmented Generation (RAG) systems for Quality Engineering (QE) artifact creation. We combine autonomous AI agents with hybrid vector-graph knowledge systems to automate test plan, case, and QE metric generation. Our approach addresses traditional software testing limitations by leveraging LLMs such as Gemini and Mistral, multi-agent …

Read more “Agentic RAG for Software Testing with Hybrid Vector-Graph and Multi-Agent Orchestration”