your agents just got the keys to your computer
every agent can write code. almost none of them can touch the machine where your actual work lives
CoreSpeed TIE fixes that. tie a computer once and any agent that speaks MCP can use it:
> shell and files, inside one folder you pick
> your signed-in browser and screen, off until you turn them on
> your local MCP servers, shared as tools
> a Mac mini on a shelf or a Linux box over SSH: pair it with a one-time code
> every call goes through your rules: reads pass, writes wait for your OK
Claude Code, Codex, Cursor, Gemini CLI or your own agent
one command: npx @corespeed/cs tie
"Diesel pretty much impacts every single thing that gets transported in the United States," says CBS News' Jill Schlesinger, adding that even with the diesel deal with Russia, as long as the war with Iran persists, so will prices.
Cheapest fix for your LLM bill is probably 9 repos you never installed
LMCache crossed 12,107 stars. Three of the nine pushed code today
9 open-source GitHub repos that cut your token spend:
52,787 combined stars, all MIT or Apache-2.0, newest push Oct 18 2026
ROUTE EVERY CALL
01. higress ★9,581: https://t.co/lCe618VtPX -> balance models, cap token rate
02. agent-router ★2,239: https://t.co/onMTawMy9B -> unified API, auto failover
03. semantic-router ★3,956: https://t.co/4AcSPkHT1B -> pick route before the call
REUSE ANSWERS
04. GPTCache ★8,213: https://t.co/Sngq7N5OwV -> cache answers by meaning. 10x cheaper (README)
05. redis-vl-python ★432: https://t.co/JsrBSSn47U -> semantic cache on Redis
SHRINK THE PROMPT
06. LLMLingua ★6,757: https://t.co/RYsm6BjtUb -> strip tokens, up to 20x (README)
REUSE THE KV CACHE
07. LMCache ★12,107: https://t.co/HX7eKoZ4h6 -> reuse KV state across requests
08. production-stack ★2,678: https://t.co/tSFlkSKuiu -> route to warm KV cache
09. Mooncake ★6,824: https://t.co/habQysk6Jt -> shared KV pool, idle hardware. Kimi +75% throughput (README)
pip install llmlingua
the stack:
request → gateway → route → answer cache → compress → KV reuse → model → response
Semantic caches return near-matches. Set the distance threshold tight
Gateway first. Cache and compress before KV reuse hits the model
Skip the model hunt. Fix the pipeline ↓