VS Code 1.90 to JetBrains 2026.1: 50 Dev Productivity Gains

In early 2025, our 50-person engineering team made the controversial decision to migrate off VS Code 1.90 to JetBrains 2026.1 across all our product squads. Six months later, we’re sharing hard data on productivity lifts, unexpected wins, and lessons learned from one of our largest tooling shifts in years.

Why We Left VS Code 1.90

VS Code 1.90 had served us well for 3 years, but as our monorepo grew to 12M+ lines of code spanning Java, TypeScript, Python, and Go, we hit consistent pain points: frequent OOM crashes when indexing large modules, slow debugger attach times (averaging 45 seconds for our main service), and fragmented plugin ecosystems that required manual maintenance across 50 seats. A Q4 2024 survey found 68% of engineers reported losing >2 hours weekly to tooling friction.

Migration Timeline: 8 Weeks to Full Rollout

We opted for a phased rollout of JetBrains 2026.1 (matching IDEs to tech stacks: IntelliJ IDEA for Java, WebStorm for TypeScript, PyCharm for Python, GoLand for Go) to minimize disruption:

• Weeks 1-2: Pilot group of 8 senior engineers tested JetBrains 2026.1, documented plugin gaps, and built internal setup scripts.
• Weeks 3-5: 50% of team onboarded, with weekly office hours to address learning curve questions.
• Weeks 6-8: Full rollout, decommissioned VS Code 1.90 from all corporate devices.

Quantified Productivity Gains

We tracked 4 core metrics pre- and post-migration, with results normalized across all 50 engineers:

• Debug session startup: Reduced from 45 seconds to 8 seconds (82% improvement)
• Code search latency: Down from 12 seconds to 1.2 seconds for cross-module searches (90% improvement)
• Weekly tooling downtime: Fell from 2.1 hours to 0.4 hours per engineer (81% reduction)
• Feature delivery velocity: 22% increase in story points completed per sprint across all squads

Engineers cited JetBrains 2026.1’s native monorepo support, built-in Kubernetes and database tools, and context-aware AI code completion as top drivers of these gains. “I no longer switch between 4 separate tools to debug a service, check a database, and review a PR,” said Senior Backend Engineer Maria Chen. “That alone saves me 3 hours a week.”

Challenges and Mitigations

No migration is without friction. Key issues we faced:

• Learning curve: 32% of engineers reported initial slowdowns in the first 2 weeks. We mitigated this with 2 half-day training sessions and a internal JetBrains cheat sheet.
• Plugin compatibility: 3 custom internal VS Code extensions had no JetBrains equivalent. Our tooling team built lightweight alternatives in 3 weeks.
• License costs: JetBrains 2026.1 licenses cost 40% more than our previous VS Code setup (including paid extensions). The 22% velocity gain offset this cost in 4.5 months.

Final Takeaways

For teams of 20+ engineers working in large, multi-language codebases, the switch to JetBrains 2026.1 delivered measurable ROI within 6 months. Key lessons for other orgs:

• Run a small pilot first to identify edge cases before full rollout
• Invest in role-specific training instead of generic documentation
• Track quantitative metrics early to justify the switch to stakeholders

We’re now expanding our JetBrains 2026.1 usage to include JetBrains AI Enterprise features in Q3 2026, with early pilots suggesting an additional 10% productivity lift from automated code review and test generation.