Context engineering for AI dev success
August 5, 2025
Many software development teams are benchmarking AI tools and deciding not to adopt them. They expect AI to work like a smart developer who understands their codebase intuitively. When the AI produces generic code that doesn’t match their patterns, generates bugs, or requires heavy modification, they conclude the technology isn’t ready. These teams have the wrong expectations. They’re evaluating AI assistants like human developers instead of understanding that AI needs comprehensive context to perform well.The key insight: Context engineering, alongside prompt engineering, determines AI assistant success.
With AI assisted software engineering, it feels like we are reaching that point in the adoption of many technologies, where we stop marvelling something can be done at all, and start recognising the shortcomings and addressing them.
The concept of context engineering is still emerging, but there’s an increasing consensus that managing context is the key to working well with LLMs for software engineering.
This piece by Guillaume Moigneu is a detailed and thoughtful overview of how context engineering can very much help Software engineering success when working with these systems.
