Qodo
@QodoAI
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The agentic AI code review platform. Code quality for the enterprise.
Joined December 2022
Qodo Context Engine agents (Deep Research & PR Knowledge) are now smarter after experimenting with @OpenAI 's GPT-5.1-Codex-Max. Beating our internal benchmarks by a wide margin, Qodo context engine now has deeper understanding, accurate answers, and is a smarter teammate. ⚡️ As
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Why leverage three different models instead of one? Code review needs different capabilities at different stages. Sr. AI Engineer Dr. Ofir Friedman wrote a full technical breakdown here →
qodo.ai
See how Qodo benchmarks AI models on real pull requests and why GPT-5.2, Gemini 2.5 Pro, and Claude Haiku 4.5 power our PR reviews.
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GPT-5.2 (scored 80.8): Finds multiple critical bugs per diff. Best for deep analysis. Gemini 2.5 Pro (56.3): Consistent, structured, lowest harmful fix rate. Best for stable reviews. Claude Haiku 4.5 (48.8): High precision, fast, cost-efficient. Best for high-volume repos.
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Full Self-Driving Supervised has many times more driving experience than any human driver It's trained on >100 years of data & collectively experiences a lifetime of driving scenarios every 10 minutes
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We run 400 real PRs across 100+ repos to benchmark every major AI model. Here's why GPT-5.2, Gemini 2.5 Pro, and Claude Haiku 4.5 are now Qodo's default code reviewers 🧵
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💻 @QodoAI is bringing AI to code quality. Context-aware reviews, automated testing, and enterprise deployment with Vertex AI help developers move confidently at AI speed.
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Automated unit tests scale. Manual ones don't. When microservices multiply and PRs pile up, coverage gaps compound fast. Qodo generates behavior-driven tests in your IDE → validates them in PR → enforces coverage in CI. Read more here 🔗 https://t.co/oVv693TR4w
qodo.ai
Learn how enterprises can optimize automated unit test generation to improve code quality, reduce defects, and accelerate continuous delivery.
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60% of MCP tool usage in agentic workflows is dedicated to context retrieval. Context isn't a feature. It's the foundation. Without it, you're just generating plausible code, not production-ready code. What context gaps are you seeing with AI-generated code?
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Sleigh the season with the most personal gift around. Get them a Cameo video!
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AI code quality isn't about better models. It's about better context: → Awareness of your codebase → Understanding team norms → Following project structure → Enforcing organization rules Better context = better quality.
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"Surgery is much harder than invention." 🩺 Ben Stice (VP Eng, Salesforce) nailed the 2025 AI reality check: - AI loves invention (greenfield, messy). - Enterprise needs surgery (legacy, precise, high-stakes). Stop treating your production codebase like a hackathon demo. We
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→ More code → More PRs → Same bugs per line (or more) → Review can't keep up AI boosts output 97.8%, but review time increases 91.1%. This is the bottleneck in software development. Qodo’s State of AI Code Quality 2025 digs into the numbers. https://t.co/bLyxuuhIjm
qodo.ai
Learn more about the insights we've gathered from 600+ developers on how generative AI is shaping developer experience, trust, productivity and code quality across the SDLC.
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AI code gen tools adoption: 82-92% Productivity boost: 3x faster coding Quality concerns: 67% report difficulty maintaining standards Devs are now writing code faster than they can safely ship it.
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65% of developers say at least 25% of each commit is AI-generated. But only 28% are confident in their AI code. The productivity boost is real. The quality gap is also real.
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3 major cloud outages in 3 weeks. Companies report AI-generated code growing: 10% → 30% → 50% of codebases. Are these somehow related? 🧵
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AI code assistants write code in seconds. But "working" isn't the same as production-ready. The biggest challenge is validating whether AI-generated code fits your architecture, maintains standards, and won't break three months from now. Code quality is an entire workflow now.
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With AI, you achieve software maintainability when it understands your entire system, not just the diff in your PR. Read more:
qodo.ai
Discover how context-aware AI helps enterprises reduce technical debt, enhance developer productivity, and ensure scalable software maintainability.
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Context-aware code review catches what traditional tools miss: → Breaking changes across microservices → Code duplication across repos → Architectural drift before merge The difference? Full codebase context vs. code diff-only analysis.
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What actually moved the needle for engineering leaders in 2025? Post-AWS re:Invent, we're bringing together leaders who shipped real results. Join the Qodo roundtable: what worked, what didn't scale, and where we're placing bets for 2026. Dec 10th at 12pm ET
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Maish, Senior Dev Advocate at AWS closed out the last day at @AWSreInvent Qodo booth with a positive consensus about GenAI in software 🔥
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Highlights from the booth @AWSreInvent: Almog shares his thoughts on AI trends & enterprise challenges for dev workflows ⬇️
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