The Era of Context Engineering
We went from 'every generative AI startup is a ChatGPT wrapper' back in 2023, to 'every agentic AI startup is a Claude wrapper.'
And yet, this marked a key shift, something much deeper than the architectural change from prompt engineering to context engineering.
A couple of days ago, in a post on X, Andrej Karpathy highlighted something quite important.
This observation captures more than just a shift in criticism—it reveals a fundamental transformation in how AI applications are built.
The journey from simple prompt optimization to complex context engineering represents one of the most significant architectural evolutions in modern software.
The dismissive "wrapper" label persists, but the reality has evolved far beyond what critics understand.
We've moved from applications that simply format and relay prompts to sophisticated systems that orchestrate entire information architectures.
This isn't about writing better questions anymore—it's about building the cognitive infrastructure that enables AI to operate autonomously and effectively.
This analysis synthesizes Andrej Karpathy's mental model of context engineering with Gennaro Cuofano's observations on the evolution of AI applications, incorporating the architectural impact of the Model Context Protocol (MCP). The shift from prompt to context engineering, now accelerated by standardized protocols, represents not just a technical evolution but a fundamental transformation in how we architect intelligent systems.
