Most people are using Claude wrong They open it. Prompt randomly. Lose context.
Start over again. Repeat the same instructions 50 times
After months of building directly inside Claude, here are some things that genuinely improved my workflow:
- Maintain project-wise CLAUDE + context setup
- Keep all important project files structured properly so Claude doesn’t reread everything again & again
- Use local artifacts only after achieving a desirable output
- Build a proper debug environment inside Claude
- Keep global files under ~800 lines to reduce context collision & memory loss
- Use Obsidian network for coding references and interconnected knowledge
- Use memory/context MCP servers so Claude can retain project understanding across sessions instead of repeatedly accessing .md files
- Use GitHub/context-memory setups like MCP Memory Keeper or Claude Context for persistent context workflows
- Use straightforward Git push workflows while writing instead of overcomplicating the setup
- And yes… sometimes I literally message “hey” a few hours before working just to reset limits and prep the environment
Biggest realization?
Claude performs insanely well when
- Context is structured
- Systems are clean
- Instructions are intentional
Most people blame the model.
But half the time the issue is messy
workflow management.
AI coding is slowly becoming less about prompting… and more about:
- context engineering
- memory systems
- workflow optimization
- decision making
I’m currently building:
- products
- design systems
- websites
- AI workflows
Almost entirely inside Claude now at OpenCore Group.
And honestly?
The difference between a bad and great result is usually the setup.
