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๐Ÿš‚ Introducing Agent Prompt Train ๐Ÿš‚ An open-sourced high-performance proxy that works with Claude Code to help turn it from a single-developer tool into a collaborative development platform. Claude Code changed the game. Now, Agent Prompt Train is here to help teams: โœ… Log every conversation for review โœ…...

21,539 ๆฌก่ง‚็œ‹ โ€ข 1 ๅนดๅ‰ โ€ขvia X (Twitter)

32 ๆก่ฏ„่ฎบ

evin ็š„ๅคดๅƒ
evin1 ๅนดๅ‰

๐Ÿ‘€๐Ÿ‘€

Maelstrom ็š„ๅคดๅƒ
Maelstrom1 ๅนดๅ‰

Claude Code was already a beast, now it's giving it a team to run with. Game changer for devs.

TraviSKrypto ็š„ๅคดๅƒ
TraviSKrypto1 ๅนดๅ‰

Big

e4kr ็š„ๅคดๅƒ
e4kr1 ๅนดๅ‰

built for the prompt meta game

Mardis Joye_Reddio ็š„ๅคดๅƒ
Mardis Joye_Reddio1 ๅนดๅ‰

finally a team prompt workflow that scales with claude code

THEDEFIGURU ็š„ๅคดๅƒ
THEDEFIGURU11 ไธชๆœˆๅ‰

Super cool... feels like it levels up teamwork around AI instantly.

Crya ็š„ๅคดๅƒ
Crya1 ๅนดๅ‰

That's great

Bob ็š„ๅคดๅƒ
Bob1 ๅนดๅ‰

Game changer for prompt ops

Mustang L ็š„ๅคดๅƒ
Mustang L1 ๅนดๅ‰

agent prompts get smarter how will you guard privacy

meliscinar ็š„ๅคดๅƒ
meliscinar1 ๅนดๅ‰

this could change team workflows way beyond coding curious how it handles scaling with larger groups

Ema26โค๏ธ ็š„ๅคดๅƒ
Ema26โค๏ธ1 ๅนดๅ‰

Team prompts leveled up

Bala_balami ็š„ๅคดๅƒ
Bala_balami1 ๅนดๅ‰

Well explained

Creatooor ็š„ๅคดๅƒ
Creatooor1 ๅนดๅ‰

Interestingly bullish!

0xTimAllen12 ็š„ๅคดๅƒ
0xTimAllen121 ๅนดๅ‰

This looks cool, will take a look. FYI the AI video gives off major scam vibes though. might be making people skip over it before they see what you actually built.

omid ๐Ÿฆˆ ็š„ๅคดๅƒ
omid ๐Ÿฆˆ10 ไธชๆœˆๅ‰

thatโ€™s interesting ๐Ÿ‘€

Muqadas ็š„ๅคดๅƒ
Muqadas1 ๅนดๅ‰

That's great

yomi ็š„ๅคดๅƒ
yomi11 ไธชๆœˆๅ‰

Really great initiative

โค๏ธ CryptoConnect ๐Ÿ”—Hub ๐Ÿš€ ็š„ๅคดๅƒ
โค๏ธ CryptoConnect ๐Ÿ”—Hub ๐Ÿš€8 ไธชๆœˆๅ‰

ok

Aส™แดœ ส€แด€สสœแด€ษด ็š„ๅคดๅƒ
Aส™แดœ ส€แด€สสœแด€ษด1 ๅนดๅ‰

Sounds like a powerful tool for team collaboration with Claude! Great for streamlining prompt management and knowledge sharing. ๐Ÿ‘

Thoth๐Ÿ‚๐Ÿ€„ ็š„ๅคดๅƒ
Thoth๐Ÿ‚๐Ÿ€„10 ไธชๆœˆๅ‰

sounds like a wild game of fee dodgeball!

Stormbringer ็š„ๅคดๅƒ
Stormbringer10 ไธชๆœˆๅ‰

Happy new year legend Would appreciate a follow back๐Ÿ™

Hanasata.eth ็š„ๅคดๅƒ
Hanasata.eth1 ๅนดๅ‰

Full steam ahead

รŠVร˜ร‡HRฬƒร˜ฦรŽร‡LรŠ ็š„ๅคดๅƒ
รŠVร˜ร‡HRฬƒร˜ฦรŽร‡LรŠ8 ไธชๆœˆๅ‰

๐Ÿ™‚

ะฒิฯ‰ฮน '3ัฮฌะผ ห›โ™ฅ ็š„ๅคดๅƒ
ะฒิฯ‰ฮน '3ัฮฌะผ ห›โ™ฅ1 ๅนดๅ‰

THIS COULD TURN DEV WORKFLOWS INTO A TEAM SPORT - HOW DO YOU HANDLE LOG ACCESS?

King Amslen(ร˜,G) ็š„ๅคดๅƒ
King Amslen(ร˜,G)1 ๅนดๅ‰

GMoonsong

RY6M RY6M ็š„ๅคดๅƒ
RY6M RY6M1 ๅนดๅ‰

So handsome

Popcorn.eth ๐ŸŒ ็š„ๅคดๅƒ
Popcorn.eth ๐ŸŒ10 ไธชๆœˆๅ‰

๐Ÿ”ฅ

MEVwitch ๐Ÿง™โ€โ™€๏ธ_dao ็š„ๅคดๅƒ
MEVwitch ๐Ÿง™โ€โ™€๏ธ_dao1 ๅนดๅ‰

so basically git history but for prompts

Ayush (Explorer) ็š„ๅคดๅƒ
Ayush (Explorer)1 ๅนดๅ‰

Agent Prompt Train: Boost teamwork with Claude Code! ๐ŸŒŸ

Thoth๐Ÿ‚๐Ÿ€„ ็š„ๅคดๅƒ
Thoth๐Ÿ‚๐Ÿ€„11 ไธชๆœˆๅ‰

opensea fees are a good point

UN Why ็š„ๅคดๅƒ
UN Why8 ไธชๆœˆๅ‰

Well explained

Karin Stone ็š„ๅคดๅƒ
Karin Stone7 ไธชๆœˆๅ‰

Check dm please

็›ธๅ…ณ่ง†้ข‘

Another insane Jev use case! Jev makes it incredibly cheap to evaluate and classify agent runs at scale. And finally, someone open-sourced a self-improving memory layer that can put that capability to work across agent harnesses. It turns your agent sessions into a compounding knowledge layer, where every successful run can make future agents smarter across: - Codex - Claude Code - Cursor - OpenCode and 20+ more Beacon by Asymptote Labs continuously builds a shared history across your agent harnesses and uses Jev to identify the runs worth learning from. It then turns the best workflows, corrections, and debugging patterns into reusable skills. GitHub repo: (donโ€™t forget to star it โญ) Most agent runs are messy. They contain exploration, failed commands, dead ends, and one-off fixes that should never become permanent memory. So Beacon preserves the full session history, while Jev helps decide what should be promoted, reviewed, or discarded. The recording below shows this in action. Beacon found 579 sessions across 5 coding-agent harnesses and normalized them into one consistent history. From there, Jev surfaces the lessons worth keeping and makes them available across your agent stack. - A pattern learned in Cursor can carry into OpenCode. - A lesson from Claude Code can improve the next Codex run. Every successful run adds to the shared knowledge layer, making future agents smarter. If you want to dive deeper into Jev, I also wrote a breakdown of how it works. The article is quoted below.

Akshay ๐Ÿš€

120,930 ๆฌก่ง‚็œ‹ โ€ข 1 ไธชๆœˆๅ‰