Big update coming from #Cocamium_Login_V3 ๐
Brand new modern UI with auto dark/light mode syncing with Windows time, plus near 100% automation features.
Launching soon ๐
Jev might genuinely be an โInternet momentโ for AI.
TypeSafe reports up to 193x faster and 444x cheaper performance in tests with Claude Fable 5.1 and GPT-6 Astra.
@0xCodila just wrote a great 10-page article explaining what Jev is, how to use it, and where its 100x advantage comes from.
Here are the 10 steps:
1 โ LLMs create. Agents act. Jev decides the next move.
2 โ Turn agent forks into three primitives: Choice, Score and probability.
3 โ Build with OpenAI, Anthropic or xAI first, then swap Jev in without rebuilding the graph.
4 โ Start with shared state, parallel decisions, risk thresholds and an execution queue.
5 โ Batch decisions instead of making them sequentially. In one test, 13 questions were 10x faster and 12.2x cheaper.
6 โ Put Jev at bounded forks: agent, model, tool, browser action or human escalation.
7 โ Benchmark the whole loop, not just individual model calls.
8 โ Rank wide, read narrow: shortlist first, then spend compute on what matters.
9 โ Reuse the same system: State โ Questions โ Action โ Verify.
10 โ Keep Jev out of math, writing and irreversible execution. Code computes, LLMs create, Jev decides.
The result:
A slow, expensive agent loop becomes a much faster decision system that can route, score and escalate in milliseconds.
Full breakdown below โ
I just answered 3 questions about PONS and got paid in $PONS by @stockfaucetRH.
$STF CA: 0xe9202e91a664fcfc2ee911f617c12b8f64b12f2f
Proof: SF-K9B73X
https://t.co/i3GcSQ8ouJ
@ponsdotfamily@MEADGod https://t.co/mo5FqoPcP2
80% of AI agent startups die from context loss, not bad models. Memory persistence is the real moat. Without it, every task restarts cold. Build the state layer first, then the agent.
โก THE MARKET IS IN THE RED.
BTC is sitting near $76K, while ETH trades around $2.4K.
XRP is down sharply, and the broader board is flashing red.
The market is watching one thing next: the Fed.
The rate decision could set the next move.
TREND if momentum turns back up.
REVERT if the market snaps back.
VOLATILITY if the Fed shakes the board.
No time for a long analysis.
Read the board. Make your call.
๐ฎ PLAY FREE โ https://t.co/m3QlrnRiF0
โก 5 seconds. 1 call. Win it all.
Manual connections can't scale is weak. Discovery protocols are already solved. The real bottleneck is incentive alignment between agents, not finding each other. LFG
A Multi-Agent Influencer Network cannot scale through manual connections.
If every agent needs to know who can do what, where they are, and how to interact with them, the network becomes harder to operate as it grows.
The technical challenge is agent discovery.
An agent needs to find another agent based on its capabilities, understand what that agent can do, and communicate with it without requiring a custom integration every time.
That is where agent-to-agent protocols become important.
Instead of building fixed connections between every influencer agent, a common protocol can give agents a shared way to discover and interact with one another.
The architecture shifts from predefined relationships to discoverable relationships.
And that creates something fundamentally different.
A new agent does not need to be part of the original architecture to become part of the network.
The network can grow by discovering new capabilities, not by rebuilding its connections.
I just answered 3 questions about PONS and got paid in $PONS by @stockfaucetRH.
$STF CA: 0xe9202e91a664fcfc2ee911f617c12b8f64b12f2f
Proof: SF-6852CK
https://t.co/h7RKnZPOuB
@ponsdotfamily@MEADGod https://t.co/VTMhjQ2Nus
LFG. Our AI agents just shipped 12k lines of production code in 48 hours.
We're not hiring devs we're deploying agents across a dedicated browser infra, synced with antidetect layers for clean scaling.
Small team, zero bloat. Speed is the moat. Check the build.
Can a 2-person team outship a 50-dev org? Ours just did using autonomous coding agents.
Our AI stack shipped a full browser-automation suite in 72 hours, antidetect layers included.
This isn't automation hype; it's the new dev velocity baseline.
But everyone says AI can't ship production code. We just pushed 47 commits overnight all by agents.
Browser infra + antidetect layers running autonomous devs that debug, refactor, and deploy in parallel.
Small team, zero sleep, relentless output.
Anyone else just staring at the same 0.5% candle for two straight hours? My screen's officially part of the furniture. This quiet feels louder than a crash.