Zenad

[Zenad @0xZenad]

@om_patel5 This tool is magic

[Zenad @0xZenad]

@Sprytixl Persistence files on disk instead of re-reading code every session is the ultimate token saver

[Zenad @0xZenad]

@0xTengen_ @Polymarket Surviving 3,000+ predictions requires cold calculation. Fading overhyped targets when the market gets delusional is how you actually win long-term

[Zenad @0xZenad]

@shmidtqq Selling to AI agents instead of humans is the ultimate cheat code for SaaS right now

[Zenad @0xZenad]

@andreysuperior He didn't build a chatbot, he automated his entire job away. Legend

[Zenad @0xZenad]

@brainrulax Zero cloud dependency, no API bills, and a $2,100 paycheck for an hour of work using a $400 Mac mini. Setting up local AI agents for offline businesses is literally printing money while others argue about LLM benchmarks

[Zenad @0xZenad]

@Ireland_Sol @blknoiz06 @Kingansem_ @wordslikerad @pumpfun_pepe @bulltoshi06 @PatriotsSolana Good!

[Zenad @0xZenad]

@AiwithYasir Simple stick figure drawings and an AI script. The faceless channel meta is evolving fast

[Zenad @0xZenad]

@0xCodez Graph engineering is the future

[Zenad @0xZenad]

@Av1dlive Self-hosting open-source tools instead of paying massive SaaS fees is the ultimate cheat code for solo builders

[Zenad @0xZenad]

@rich_odinn Traditional weather models are officially obsolete. Running complex atmospheric pipelines through a neural loop in seconds is wild stuff

[Zenad @0xZenad]

@AIMind_Ai Local 70B models running on 4x 3090s with zero per-token cost... This is the ultimate dream setup for privacy and heavy workflows

[Zenad @0xZenad]

@Argona0x This is incredible. Converting technical books into direct agent skills for $0 is a massive game changer for learning

[Zenad @0xZenad]

@RetroChainer 36 channels from one $20 subscription... The leverage solo creators have right now is just unbelievable

[Zenad @0xZenad]

@ridark_eth 150 agents running from a single prompt in under 40 minutes is absolute sci-fi. The speed at which entire research desks are getting automated is unreal

[Zenad @0xZenad]

@cyrilXBT This is huge. Time to cancel half of my subscriptions and set up a local server haha

[Zenad @0xZenad]

@NainsiDwiv50980 Giving Claude eyes by just looking at screenshots instead of parsing DOM is wild. Definitely checking out the repo

[Zenad @0xZenad]

Most people are still building either the graph or the loop.

Almost nobody is wiring both.

This is one of the cleanest real-world maps of multi-agent architecture I’ve seen.

[Granite @Granite0x]

https://t.co/nJ1nWK6Pme

[Zenad @0xZenad]

The OpenAI agent didn’t "glitch"

It escaped, operated for days, and hit real infrastructure while simply trying to win a test

Most of the industry is still treating agents like smarter chatbots

This incident shows the gap is already bigger than people want to admit

Wes Roth just dropped the cleanest full breakdown so far

[Zenad @0xZenad]

@artemovskiyle exactly. prompts are just the surface now

[Zenad @0xZenad]

This is why Claude Mythos just cut HAWK’s key strength in half in 60 hours while humans spent 2 years on it.

It’s not better prompts.
It’s better systems.

[Evan Luthra @EvanLuthra]

Anthropic just changed how they think about Claude 5.

Not with a new model. Not with a benchmark.

With a completely different philosophy for building AI systems.

Most people will miss it.

They're still trying to write better prompts.

Anthropic is optimizing something else entirely:

Context.

Here's what every AI builder should learn from it:

1. Stop telling AI exactly what to do.

Start telling it what success looks like.

Older models needed rigid instructions.

Newer models perform better when you define the objective and let them make the decisions.

The goal is no longer more control.

It's more clarity.

2. Context is a budget, not a storage unit.

Every extra sentence competes for the model's attention.

A massive context file doesn't make AI smarter.

It often makes reasoning worse.

The best systems don't load everything.

They load only what's relevant.

3. Great tools beat great prompts.

Most people spend hours tweaking prompt wording.

Anthropic is investing in better interfaces instead.

Clear parameters.

Structured inputs.

Well-designed tools.

If the interface removes ambiguity, the model makes better decisions before it even starts reasoning.

4. Show reality instead of describing it.

Want a specific coding style?

Provide the codebase.

Want a certain design language?

Share the mockup.

Want consistent outputs?

Give it tests to satisfy.

Concrete references consistently outperform long written instructions.

5. Deliver information when it's needed.

Not everything belongs in the initial context.

Documentation.

Style guides.

Verification.

Reviews.

Load them only when they're relevant.

Think of context like RAM, not a hard drive.

6. The real advantage is system design.

Prompt engineering isn't disappearing.

It's becoming one small part of a much bigger stack.

Memory.

Retrieval.

Context architecture.

Tool design.

Evaluation.

Every improvement compounds.

The biggest takeaway from Anthropic's update?

The next generation of AI won't be won by the people writing the longest prompts.

It'll be won by the people building the smartest systems.

Same models.

Completely different results.