In celebration of the Walrus Prompt Jam, our team is showcasing a selection of standout community initiatives centered around portable agent memory. Our first feature is Markov, a solution crafted by @/dun999 over on Github.
Transitioning among terminal agents, Claude Code, and Codex traditionally forces users to reconstruct their prompt context right from the beginning. Markov eliminates this friction by retaining the active state of a task across different #AI coding applications, which enables programmers to seamlessly and instantly transfer their pending work.
If you are currently shifting between AI coders or developing cross-agent tools for developers, please share your routine with us below.
Review the exact prompt at the following link: https://github.com/dun999/markov/blob/main/PROMPT.md
Read the entire submission here: https://www.deepsurge.xyz/projects/f8b0e24c-05cb-4b3a-be61-8246daca26cd
Transitioning among terminal agents, Claude Code, and Codex traditionally forces users to reconstruct their prompt context right from the beginning. Markov eliminates this friction by retaining the active state of a task across different #AI coding applications, which enables programmers to seamlessly and instantly transfer their pending work.
If you are currently shifting between AI coders or developing cross-agent tools for developers, please share your routine with us below.
Review the exact prompt at the following link: https://github.com/dun999/markov/blob/main/PROMPT.md
Read the entire submission here: https://www.deepsurge.xyz/projects/f8b0e24c-05cb-4b3a-be61-8246daca26cd