There is, currently, a tension between memory, and context pressure on the coding agent. There have been multiple studies now that tools like codex and claude code get worst at coding as their context window fills up.
As you start adding skills, memory systems, plugins and then a large code base on top of it, I've personally seen the agent start to flounder pretty quickly.
We need a way for agents to pull adhoc memory as they are going along, in the same way we do, rather than trying to front load all the context they might need.
We have been building agents for code review workflow for nearly two years. Our Code Review Knowledge base today serves more than 3 million repos. We pack more than 40 different points of information into the same LLM context, such as MCP Servers, Rule files, etc. We understand context poisoning/rot and how it creating problems.
We are now bringing the same learning/context engine to SDLC and Slack.
Please give it a try!