Engineering
Engineering
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Auto Approval: how iFood accelerated code review by 33% with automated risk assessment
From MR queues to automated risk analysis: how context, heuristics, and LLMs revolutionized code review at iFood At iFood, accelerating the engineering process without compromising security and quality is a constant challenge, especially when we consider the scale of our…
Visual regression with AI: the combination of automated testing, AI, and Figma that accelerated validations
Scaling quality in digital products is a challenge, especially with multiple platforms, integrated flows, and distributed teams working simultaneously. In Local Commerce, the area responsible for developing the app that connects consumers to restaurants, markets, and pharmacies at iFood, we…
IFDS: Inside the Engineering Patterns and Component Architecture of iFood Design System
How we connect design and code through rigorous engineering patterns to scale interfaces at iFood From Divergence to Convergence: The Real Problem At iFood, we faced a common problem in large-scale technology organizations: a growing divergence between design and code.…
Scaling Engineering with confidence: the role of AI, RAG and governance at iFood
Introduction: the real challenge behind technical onboarding In technology companies operating at scale, technical onboarding tends to be a sensitive point. The larger the organization, the greater the volume of standards, guides, architectural decisions, and security requirements that a developer…
Cost Optimization at Scale: The Impact of Kafka Topic Compression at iFood
In iFood's technology ecosystem, real-time data processing is the pillar that sustains everything from real-time driver location tracking to fraud detection in our marketplace. With the exponential growth in data volume, operational efficiency and financial sustainability have become strategic pillars…
