I’m hoping to gather different approaches people use when working with Claude in one thread. What methods do you use to keep track of information between different conversations? Do you have any special techniques that work well? How do you work with multiple AI assistants or specialized prompts? I’m curious to learn from everyone’s experience. Right now I just tell Claude to save updates in a markdown file called CLAUDE.md to track what we’ve discussed, but I’m sure there are better ways to do this.
screenshot method works great for me. I just grab important parts of conversations and dump them in a desktop folder. way faster than copying text everywhere. need context? quick scroll through screenshots, then type out what’s relevant. simple but effective - takes no time at all.
Manual tracking kills productivity. These approaches work, but you’re doing the AI’s job.
I automated this whole thing and never looked back. Set up triggers that grab conversation highlights, auto-categorize them, and inject relevant context into new sessions. Zero manual work.
The breakthrough came when I stopped treating Claude like a teammate and started treating it like what it is - a tool needing structured data. My system pulls context from past conversations using keywords, project tags, or conversation type. No more copying screenshots or manual management.
For complex projects, I’ve got automated workflows maintaining context across multiple AI sessions. The system decides what matters and formats it for each new conversation. No guessing what to include.
Best part? Works with multiple AI assistants simultaneously. Same context management, different endpoints. I switch between Claude, GPT, and others while keeping project context synced.
Took 2 hours to set up initially, but I save hours weekly not managing conversation files manually.
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I treat Claude conversations like API calls, not ongoing chats. Each interaction needs to be self-contained. I keep a ‘context bank’ - organized snippets of background info, requirements, and conventions that I can quickly mix and match based on what I need. The game-changer was being surgical about context. Don’t dump everything into each conversation. I categorize info by relevance and only include what directly affects the current task. Debugging code? I’ll include the error, relevant code sections, and coding standards - but skip the project history. Give Claude a specific role upfront rather than trying to steer mid-conversation. Instead of ‘help me with this code,’ I say ‘act as a senior developer reviewing this function for performance issues, focus on algorithmic efficiency.’ Biggest time-saver? Conversation templates for recurring work patterns. Different projects get different starter prompts - I just fill in the variables.
I’ve found that creating a prompt template at the start of each conversation beats trying to maintain files across sessions. I frontload the context with a quick summary of previous discussions and any specific parameters I want Claude to remember for that task. Here’s what I discovered: consistency in how you frame requests matters way more than complex tracking systems. I use standardized opening phrases for different work types - coding, writing, analysis, whatever. It creates a predictable interaction pattern. For complex projects spanning multiple conversations, I break them into separate, self-contained sessions instead of trying to maintain continuity. Each conversation gets a clear objective and all the background info upfront. No more frustration when Claude forgets crucial details, and every interaction becomes more reliable and focused.
I built a simple context injection system that saved me tons of time. Don’t rely on Claude to remember stuff - just keep a running doc with key decisions, code snippets, and project context. Paste it into new conversations when you need it.
Game changer: treat each Claude session like a new teammate joining mid-project. I always drop in a quick “project state” summary - current goals, constraints, and any specific terms or patterns we’re using.
For technical work, I use three parts: current context, specific ask, and expected output format. Cuts out most of the back-and-forth clarification.
Biggest breakthrough? Stop trying to make Claude remember everything. Be intentional about what context actually matters for each task. Usually you only need 20% of the previous discussion to get quality responses.
I keep different “persona prompts” ready for different work types - code reviews, architecture discussions, etc. Way faster than explaining the same role every time.
This video covers advanced conversation techniques that’ll give you more ideas beyond basic tracking.