AI Coding assistants dont suck, but you suck at managing context window.
Most developers currently debating whether AI coding agents "suck" or are a "skill issue" are missing the most critical technical constraint:
the context window
If you want to get elite performance out of tools like Claude Code or Cursor you need to stop thinking about just the prompt and start managing your token budget/
Here is the high level breakdown of why your AI agent might be failing and how to fix it:
- The lost in middle Problem
The context window is the sum of all input and output tokens the LLM can "see" at once however, LLMs suffer from a "needle in a haystack" retrieval issue.
due to the attention mechanism's design, models often suffer from primacy and recency bias they prioritise information at the very beginning and the very end of a chat while de prioritising the "bloated" content in the middle
- Bigger is Not Always Better
Don't be blinded by massive limits. While Gemini offers 2 million tokens and Llama 4 scout announced a 10 million token limit performance degrades as the context grows
- Large windows often lead to significant "lost in the middle" problems where the agent simply fails to act on information provided earlier in the session
- Beware of "Context Bloat"
- The two major culprits often stealthily eat your performance:
• MCP Servers: These allow you to plug in toolsets but they can bloat your system prompt incredibly rapidly
• Large Rule Files: Massive .cursorrules or Claude rules might seem helpful, but they consume permanent space in every single interaction, increasing the risk of the model missing the actual task
- Tactical Context Management
To maintain high performance, you should treat your context window like a precious resource
Clear regularly: Dont let chats run forever. Clearing the history returns the agent to a "blank slate" and refreshes its memory
Compact the conversation: Tools like Claude Code allow you to compact history using an LLM to summarise previous messages into a single smaller message to preserve the intent without the token bloat
Monitor usage: If you are down to your last 50k tokens in a 200k window, it is time to reset
The Bottom Line: If you want better results from AI agents, stop giving them more information and start giving them better focused information
Key is not to put everything in one basket, but what to put in the right basket