Smarty

Agents | Research | Build | Beyond

[Smarty @0xSmartyx]

Anthropic Engineer Andrej Karpathy:

"The biggest mistake in AI right now - people are forcing agents to work instead of mastering the model first

We made that mistake in 2016 at OpenAI - It cost us 5 years "

what Karpathy actually means:

step 1 → stop forcing your agent to do everything, understand the model underneath first

step 2 → demos are easy - products take a decade. self-driving proved it - if you skip the foundation, everything breaks

step 3 → the agent is not the product. the foundation is. build that - and agents emerge on their own

"you building agents right now - you're at the forefront. not OpenAI. not DeepMind. you "

watch - bookmark, then read article below ↓

[Ricker @0xRicker]

https://t.co/uOmgGLD5IM

[Smarty @0xSmartyx]

@0xRicker wow mate

[Smarty @0xSmartyx]

@0xRicker wow, its gonna be banger

[Smarty @0xSmartyx]

Jev Engineering is what happens when agents stop using LLM calls for every tiny decision.

It doesn't write text. It returns typed decisions and calibrated probabilities your code can act on directly

~100 ms per call, $42 per billion tokens, and Vercel's CEO and CTO are already calling it extraordinary

in a 10-minute breakdown, Rob Shocks shows how it works live in the playground and gives the real speed and cost numbers, with the caveats

key moments:

2:08 - real speed, cost, and why this opens up so many use cases
3:31 - the three question types: Choice, Score, Noul
4:23 - where deterministic software meets AI agents

watch it no matter what, then start building with it

[Ricker @0xRicker]

Jev could become the control layer AI agents have been missing.

Instead of spending 5–20 seconds and expensive LLM calls deciding every next step, it can route actions in milliseconds at near-zero cost.

In this article, I break down how https://t.co/T9wU8CdOsj

[Smarty @0xSmartyx]

Anthropic engineer:

"99% of people use Claude Code like Google, and only 1% are running swarms of self-learning Claude agents

I'm running 100+ agents in a loop. I have Chief agent, PM agents - they manage the whole team"

In this 30-minute workshop, an Anthropic engineer shows a setup with 100+ agents running continuously

this is worth more than another $500 vibe-coding course

Watch the workshop, then read the article below on how to build self-improving agent systems with Fable ↓

[Ricker @0xRicker]

Jev could become the control layer AI agents have been missing.

Instead of spending 5–20 seconds and expensive LLM calls deciding every next step, it can route actions in milliseconds at near-zero cost.

In this article, I break down how https://t.co/T9wU8CdOsj

[Morty @0xMortyx]

Annie Wang (Senior Google Developer) spends 15 minutes showing how to wire up the Agent Development Kit

What is ADK → The agentic stack → How agents call tools → Live demo → Deploy

0:39 → Why you need an agent at all
4:20 → The full agentic stack
5:01 → A minimal agent in code
12:56 → Live run in the ADK web UI

One of the few guides that shows real code and architecture - from an empty project to a working MCP agent