In AI products, context refers to the content, tools, and instructions provided to a model at any given moment. Because AI models have context limits, what's included (aka what a model is paying attention to) has a massive impact on results. So context management is key to letting people understand and shape what AI products produce.
In Context Management UI in AI Products I looked at UI patterns for showing users what information is influencing AI model responses, from simple context chips to nested agent timelines. This time I want to highlight two examples of automatic and manual context management solutions.
Augment Code's Context Engine demonstrates how automatic context management can dramatically improve AI product outcomes. Their system continuously indexes code commit history (understanding why changes were made), team coding patterns, documentation, and what developers on a team are actively working on.
When a developer asks to "add logging to payment requests," the system identifies exactly which files and patterns are relevant. This means developers don't have to manually specify what the AI should pay attention to. The system figures it out automatically and delivers much higher quality output as a result (see chart below).
Having an intelligent system manage context for you is extremely helpful but not always possible. In many kinds of tasks, there is no clear record of history, current state, and relevance like there is in a company's codebase. Also, some tasks are bespoke or idiosyncratic meaning only the person running them knows what's truly relevant. For these reasons, AI products also need context management interfaces.
Reve's creative tooling interface not only makes manual context management possible but also provides a consistent way to reference context in instructions as well. When someone adds a file to Reve, a thumbnail of it appears in the instruction field with a numbered reference. People can then use this number when writing out instructions like "put these tires @1 on on my truck @2".
It's also worth noting that any file uploaded to or created by Reve can be put into context with a simple "one-click" action. Just select any image and it will appear in the instruction field with a reference number. Select it again to remove it from context just as easily.
While the later may seem like a clear UI requirement, it's surprising how many AI products don't support this behavior. For instance, Google's Gemini has a nice overview panel of files uploaded to and created in a session but doesn't make them selectable as context.
As usual, AI capabilities keep changing fast. So context management solutions, whether automatic or manual, and their interfaces are going to continue to evolve.