Earlier quoted context omitted.
There are all kinds of memory hacks, tools that index your code, etc. The thing I have found that makes things work much better is, wait for it... Jira. Everyone loves to hate on Jira, but it is a mature platform for managing large projects. First, I use the Jira Rovo MCP (or cli, I don't wanna argue about that) to have Claude Code plan and document my architecture, features, etc. I then manually review and edit all…
Doesn't require Jira but yes, specification-first is the way to get better (albeit still not reliably good) results out of AI tools. Some people may call this "design-first" or "architecture-first". The point is really to think through what is being built before asking AI to write the implementation (i.e. code), and to review the code to make sure it matches the intended design. Most people run into problems (with or…
One of the key improvements for me when using Jira was that it has well defined patterns for all of these things, and Claude knows all about the various types of Jira tickets, and the patterns to use them.
Also, the spec driven approach is not enough in itself. The specs need sub-items, linked bug reports and fixes. I need comments on all of these tickets as we go with implementation decisions, commit SHAs, etc.
When I come back to some particular feature later, giving Claude the appropriate context in a way it knows how to use is super easy, and is a huge leap ahead in consistency.
I know I sound like some caveman talking about Jira here, but having Claude write and read from it really helped me out a lot.
It turns out that dumb ole Jira is an excellent "project memory" storage system for agentic coding tools.