LLMs shine when acting as a 'knowledge extruder'—shaping well-documented, 'in-distribution' concepts into specific code. They fail when the core task is novel problem-solving where deep thinking, not code generation, is the bottleneck. In these cases, the code is the easy part.
The next IDE evolution will transform the codebase into a dynamic 'metadata backbone'. By capturing a continuous history of edits and conversations, it will allow all context—discussions, decisions, feedback—to be permanently anchored to specific lines of code, unlike today's static, snapshot-based Git workflows.
Despite the rise of terminal-based AI, IDEs remain essential because source code is meant for human consumption. Visual interfaces are the best way for developers to review, understand, and build context around what AI agents produce, preventing the 'death of the IDE'.
The IDE Zed was built for synchronous, Figma-like human collaboration to overcome asynchronous Git workflows. This foundation of real-time, in-code presence serendipitously created the perfect environment for integrating AI agents, which function as just another collaborator in the same shared space.
Zed founder Nathan Sobo's first IDE, Atom, used web technologies (creating Electron) for maximum extensibility. This drove rapid adoption but hit a performance wall that required a complete rewrite. Performance cannot be added later; it's baked into the initial architecture choice.
Future coding interfaces will move beyond read-only chat logs. They will treat the AI conversation as an editable 'multi-buffer'—a new type of document that aggregates code snippets from across a project. This will allow developers to directly manipulate code within the conversational flow itself.
A new risk for engineering leaders is becoming a 'vibe coding boss': using AI to set direction but misjudging its output as 95% complete when it's only 5%. This burdens the team with cleaning up a 'big mess of slop' rather than accelerating development.
Instead of building a walled-garden AI, the Zed IDE created the Agent Client Protocol (ACP), allowing any coding agent to integrate. This 'Switzerland' strategy, modeled after the Language Server Protocol, lets Zed benefit from all AI innovation rather than competing against it, even attracting competitors like JetBrains to adopt the standard.