Reported impact
Business outcome
"+15M developers use JetBrains—and now we’re bringing OpenAI into that workflow" Kang tells us that. The shift isn’t just about automation; it’s also about empowerment.
- Customer Experience
- Productivity Improvement
OpenAISoftware / SaaSApplication RefactoringIT Operations AutomationDevOpsGenerative AI / LLMCustomer ExperienceProductivity Improvement2025 OpenAIOA#10a37fSoftware / SaaSGlobalEngineers are already delegating real tasks to agents—and seeing them completed. "I assign increasingly difficult tasks to an agent, backed by GPT‑5—and to my surprise, many of the tasks are completed successfully" says…"+15M developers use JetBrains—and now we’re bringing OpenAI into that workflow" Kang tells us that. The shift…Nov 25, 20256Application Refactoring|IT Operations AutomationCodex · GPT-50 2025-11-25 6
JetBrains
Application Refactoring · IT Operations Automation
Engineers are already delegating real tasks to agents—and seeing them completed. "I assign increasingly difficult tasks to an agent, backed by GPT‑5—and to my surprise, many of the tasks are completed successfully" says Kang.
"+15M developers use JetBrains—and now we’re bringing OpenAI into that workflow" Kang tells us that. The shift isn’t just about automation; it’s also about empowerment.
Engineers are already delegating real tasks to agents—and seeing them completed. "I assign increasingly difficult tasks to an agent, backed by GPT‑5—and to my surprise, many of the tasks are...
Solution
Engineers are already delegating real tasks to agents—and seeing them completed. "I assign increasingly difficult tasks to an agent, backed by GPT‑5—and to my surprise, many of the tasks are completed successfully" says Kang. By integrating OpenAI models across its tools and workflows, JetBrains is redefining how developers design, reason, and build with AI. We sat down with Kris Kang, Head of Product at JetBrains, to explore how the team is using OpenAI models to change how developers build—not to replace what they do, but to raise the ceiling. Externally, JetBrains customers can choose GPT‑5 in Junie, the company’s coding agent, and in AI Assistant (for chat assistance).
Data flow
By integrating OpenAI models across its tools and workflows, JetBrains is redefining how developers design, reason, and build with AI.
Solution architecture
- Compute
- Codex Implements, tests, reviews, or proposes code changes so engineers can move faster with human oversight.
- GPT-5 Provides deep reasoning inside the customer workflow.
Architecture clues
- By integrating OpenAI models across its tools and workflows, JetBrains is redefining how developers design, reason, and build with AI.
- Externally, JetBrains customers can choose GPT‑5 in Junie, the company’s coding agent, and in AI Assistant (for chat assistance).
- Implements, tests, reviews, or proposes code changes so engineers can move faster with human oversight.
- Provides deep reasoning inside the customer workflow.
- We sat down with Kris Kang, Head of Product at JetBrains, to explore how the team is using OpenAI models to change how developers build—not to replace what they do, but to raise...
Evidence from the source
"+15M developers use JetBrains—and now we’re bringing OpenAI into that workflow"
"I assign increasingly difficult tasks to an agent, backed by GPT‑5—and to my surprise, many of the tasks are completed successfully"
By integrating OpenAI models across its tools and workflows, JetBrains is redefining how developers design, reason, and build with AI.
Engineers are already delegating real tasks to agents—and seeing them completed.
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value76/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth20/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity16/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact15/251 metric describe measurable impact.
- Deployment scale5/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence20/204 direct source quotes retained.
- Date provenance8/10The publication date comes from publisher-controlled metadata.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity10/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://openai.com/index/jetbrains-2025/OpenAIFirst-party
JetBrains customer story
Supports- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
- Publication date
Date evidence
- Publisher catalog date Nov 25, 2025 · OpenAI · First-partyOpen date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.
Related
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