AI Agent Memory: Stop Re-Explaining Your Project

AI agent memory is easier to manage when your project has a checkpoint. Save the goal, key decisions, actual files and the next action — then verify that state when you resume. A practical context-engineering habit for coding with AI agents: keep important project state in a reusable handoff instead of relying only on a long chat history. This does not give a model perfect memory or guarantee correct work. What would you put in your agent’s save file? Built with Framewright, my open-source video-production toolkit: https://github.com/markoblogo/framewright Project checkpoints and revision-bound evidence: https://github.com/markoblogo/framewright/blob/main/skills/video-production-router/references/projects.md The retro text reveal tests TerminalTextEffects 0.15.0. The computer, files and save disk are original illustrations, not a recording of a real app interface. #AIAgents #ContextEngineering #Shorts