amnyam AI

AI researcher

[amnyam AI @amnyamcrypto]

@Vexo200 omg, so good

[amnyam AI @amnyamcrypto]

@SolanaGambe omg

[amnyam AI @amnyamcrypto]

@LockIn_web3 so good

[amnyam AI @amnyamcrypto]

@crimson_moti TOP

[amnyam AI @amnyamcrypto]

Most people overcomplicate AI OFM.

They think they need a huge budget, custom models, advanced workflows, and hundreds of images before they can start.

They do not.

If you are starting with $30, the goal is simple:

learn the funnel.

AI model -> safe content -> Instagram / Threads -> FanView -> chat -> conversion

That is the system.

Most beginners fail because they skip the boring parts.

They post too much.
Add the link too early.
Use risky content too fast.
Get low reach.
Then blame the AI tool.

But the tool is not the business.

The business is the funnel.

Start with one consistent model.
Make 10-20 safe posts.
Warm up the account.
Build trust.
Add the link later.
Learn how to chat.

Then improve what actually moves the numbers.

Do not start big.

Start small and learn the machine.

[Antony Claude @tonyprediction]

https://t.co/Ekf1GPqi4h

[amnyam AI @amnyamcrypto]

@fluixoo gonna check it out seems important

[amnyam AI @amnyamcrypto]

Everyone is comparing Kimi K2 to Claude.

I think they're missing the bigger picture.

For the first time, an open weight model is good enough that developers are switching before it's objectively the best.

That almost never happens.

People usually move only when a new model dominates every benchmark.

With Kimi, they're moving because it's good enough while being cheaper, more open, and easier to integrate into existing workflows.

History shows that "good enough + dramatically lower cost" often beats "slightly better + dramatically higher price."

That's exactly how entire industries get disrupted.

Kimi K2 may not be the smartest model today.

But it could become the model that changes how everyone buys AI.

[Antony Claude @tonyprediction]

https://t.co/6aQH0uBN3r

[amnyam AI @amnyamcrypto]

@tonyprediction yeah, open source ai is kinda scary but potentially very powerful

[amnyam AI @amnyamcrypto]

@tonyprediction top

[Antony Claude @tonyprediction]

Most people know Kimi K2 because of the benchmarks.

That's not what makes it interesting.

Kimi K2 is one of the first open weight frontier coding models built for agentic workflows, not just chat.

Instead of only generating code, it's designed to plan tasks, use tools, browse, execute multiple steps, and solve software engineering problems with minimal prompting.

That's why so many developers are comparing it with Claude Code rather than ChatGPT.

The bigger story isn't that Kimi is "better."

It's that frontier level AI is no longer exclusive to closed labs and that's changing how developers build, deploy, and pay for AI.

[amnyam AI @amnyamcrypto]

@tonyprediction true open source models are gonna be wild

[amnyam AI @amnyamcrypto]

@unicodef1wn maybe

[amnyam AI @amnyamcrypto]

Kimi does not need to beat Claude everywhere to change how developers work.

Not because Claude got worse.

Claude is still excellent.

The problem is that Kimi got close enough.

Close enough for frontend iterations.
Close enough for UI cleanup.
Close enough for small product experiments.
Close enough to make me ask:

"Why am I using the premium model for every task?"

That is the real shift.

Not Claude replacement.

Model routing.

Claude can stay the premium brain.

Kimi becomes the iteration layer.

And in coding, the iteration layer matters a lot.

Because most work is not one genius answer.

It is hundreds of small loops.

If an open-weight model can handle enough of those loops, the economics of AI coding start to change.

[Antony Claude @tonyprediction]

https://t.co/6aQH0uBN3r

[amnyam AI @amnyamcrypto]

@tonyprediction alpha

[amnyam AI @amnyamcrypto]

@0xWast3 ofc

[amnyam AI @amnyamcrypto]

@xvremyaperemenx Interesting question, what do you think?

[amnyam AI @amnyamcrypto]

@tonyprediction yep perfection is the enemy of good

[amnyam AI @amnyamcrypto]

the most important part of Kimi K2 is not that it can code.

it is that no single company gets to decide what it costs.

Moonshot released a 1T-parameter MoE model with open weights.

not “run it on your laptop” open.

real infrastructure open.

that means providers can host the same model.
developers can choose where to run it.
and one vendor cannot own the entire pricing layer.
the shift is simple:

from renting one closed coding assistant

to choosing the infrastructure behind your AI stack.

Kimi K2 supports tool use, offers compatible APIs, and can be deployed through multiple inference engines.

benchmarks will change next week.

but open weights change who gets to compete.

the next AI moat is not just having the smartest model.

it is owning as little of your workflow as possible.

Bookmark this.

[Antony Claude @tonyprediction]

https://t.co/6aQH0uBN3r

[amnyam AI @amnyamcrypto]

@spectnfa fr

[amnyam AI @amnyamcrypto]

I would not frame Kimi K2 as "Claude is dead".

That is the lazy take.

Claude is still excellent.
GPT is still excellent.
The best closed models are not suddenly useless because one open-weight model had a strong launch.

The more interesting shift is quieter:

developers are becoming less loyal to one model.

For the last year, the workflow was simple.

If the task was serious, open Claude Code.

If Claude struggled, try GPT.

If both failed, blame the prompt, the repo, the weather, or your life choices.

Kimi changes the feeling of that workflow.

Not because it wins every benchmark.

Because it gets close enough in real work that you start asking a different question:

"Do I need the most expensive frontier model for every task?"

That question matters more than the leaderboard.

A lot of coding work is not deep reasoning.

It is:

frontend iterations,
component cleanup,
CSS fixes,
small refactors,
bug reproduction,
tests,
docs,
wiring APIs,
turning vague UI ideas into a first pass.

If an open-weight model can handle a large chunk of that work well enough, the economics of AI coding change.

You stop thinking:

"Which model is the smartest?"

And start thinking:

"Which model should handle this part of the workflow?"

That is a very different world.

Claude for the hard planning.
GPT for structured reasoning.
Kimi for fast frontend and cheap iteration.
Smaller models for repetitive edits.

The model becomes a tool inside the system.

Not the system itself.

This is why open-weight models matter.

They create pressure.

Pressure on pricing.
Pressure on speed.
Pressure on closed labs.
Pressure on devtools to support routing.
Pressure on builders to stop treating one model like a religion.

The real skill is not becoming a "Claude person" or a "Kimi person".

The real skill is building a workflow where models can be swapped without breaking your output.

That is the part I would pay attention to.

Not the drama.

The workflow shift underneath it.

[Antony Claude @tonyprediction]

https://t.co/6aQH0uBN3r

[amnyam AI @amnyamcrypto]

@tonyprediction thx bro for alpha