The LLM Revolution and its "Context" Problem

The Age of the Genie: The "Magic" and "Madness" of LLMs.

12 July 2025

We've now entered the most transformative stage in the evolution of software creation: the Age of the Genie. With Large Language Models (LLMs), we can simply state our wish in a text prompt—"Build me an e-commerce site with a shopping cart and user reviews"—and watch as functional code appears in seconds.

The power is breathtaking. It feels like magic. LLMs have shattered the barriers of speed and accessibility in a way that makes even Low/No-Code seem slow. They are incredible tools for brainstorming, prototyping, and generating boilerplate code, accelerating development workflows everywhere.

But as with any magical genie, we must be careful what we wish for. We are quickly discovering the genie's nature: it is a brilliant but forgetful improviser. It has two fundamental weaknesses when it comes to building robust, complex systems:

1. The "Context" Problem: An LLM's memory is limited to its conversation window. It has no persistent, structured understanding of the application it's building. Ask it to add a new feature, and it might forget a critical detail from a previous step, leading to subtle bugs. Ask it to modify a complex system, and it may "hallucinate" functions that don't exist or create inconsistencies between different parts of the code. It's like an architect who can only see one room at a time, with no memory of the overall floor plan.

2. The "Black Box" Problem: The code an LLM generates is a static artifact. Once created, it is disconnected from the reasoning (the prompt and the model's internal state) that produced it. The "why" behind the code is lost. This makes debugging and long-term maintenance a nightmare. If a bug appears, you can't ask the system why it made a certain architectural choice.

LLMs are masters of language and pattern recognition. They can generate code that looks right with incredible fluency. But they lack a stable, living "world model" of the software they are creating. They give us unprecedented speed but at the cost of architectural coherence and long-term maintainability.

The genie can grant our wishes, but it doesn't understand them.

So, the ultimate question becomes: how do we combine the structural integrity of traditional architecture with the generative power of the LLM? How do we give the genie a memory and a world to operate in?

That is the synthesis we will explore in our next post.

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