Manu | 🥥

Building with AI → Marketing-first brain | Game loops 🚀|

Prev: WoW Hunter 🏹 | @V3nturebuilders | @bondefi_launch | #AI

🇪🇸 🇬🇧

[Manu | 🥥 @ManuAF6]

Most Web3 creators aren’t building a brand

All you need is a good prompt and AI

Meanwhile, companies are dropping thousands on motion design and identity work

I’ve been testing different video tools...

@MedievalEmpires is one of my best

The Result and the Prompt🧵

[Manu | 🥥 @ManuAF6]

I'm not a freak… I promise…

AI transforms me into this

I bought a replica of what everyone thinks is @elonmusk ‘s head

[Manu | 🥥 @ManuAF6]

@donutgrillfish Amazing creativity! hahaha I love it.

[Manu | 🥥 @ManuAF6]

I'm not a freak… I promise…

AI transforms me into this

I bought a replica of what everyone thinks is @elonmusk ‘s head

[Manu | 🥥 @ManuAF6]

https://t.co/BjpEDWUF2j

[Manu | 🥥 @ManuAF6]

Amazon just launched Alexa for Shopping

Most people will use it like a search bar

That is the wrong way

The old prompt: "Running shoes."

The right prompt:
"I need running shoes for 3 times a week, I weigh 78kg, I run on asphalt, I have knee pain, I want something durable, max $130, prioritize comfort over speed, give me 3 options with real pros, cons and differences."

That is not a search. That is a delegated buying decision.
And Alexa for Shopping is built for exactly that.

▪️It compares products dynamically.
▪️Tracks up to a year of price history.
▪️Creates price alerts.
▪️Pulls your purchase history and preferences.
▪️And with Buy for Me, it can execute the purchase automatically when conditions are met.

Stop treating it like Google

Treat it like a buyer you are briefing

Context => Objective => Restrictions => Decision criteria => Format => Action

The more you give, the better the output.

There is also a big shift for sellers.

@amazonnews SEO is becoming AIO
Keywords are no longer enough
Your product listing needs to be understandable, comparable and justifiable to an AI agent.

Titles, bullets, FAQs, images. All of it needs to answer the questions an agent will ask on behalf of a buyer.

If Alexa cannot explain why your product fits, it will recommend the one that can

One rule before you use it:
Delegate research, comparison and alerts.
Review before any important purchase.
The agent optimizes for Amazon. You optimize for yourself.

[Manu | 🥥 @ManuAF6]

Amazon just launched Alexa for Shopping

Most people will use it like a search bar

That is the wrong way

The old prompt: "Running shoes."

The right prompt:
"I need running shoes for 3 times a week, I weigh 78kg, I run on asphalt, I have knee pain, I want something durable, max $130, prioritize comfort over speed, give me 3 options with real pros, cons and differences."

That is not a search. That is a delegated buying decision.
And Alexa for Shopping is built for exactly that.

▪️It compares products dynamically.
▪️Tracks up to a year of price history.
▪️Creates price alerts.
▪️Pulls your purchase history and preferences.
▪️And with Buy for Me, it can execute the purchase automatically when conditions are met.

Stop treating it like Google

Treat it like a buyer you are briefing

Context => Objective => Restrictions => Decision criteria => Format => Action

The more you give, the better the output.

There is also a big shift for sellers.

@amazonnews SEO is becoming AIO
Keywords are no longer enough
Your product listing needs to be understandable, comparable and justifiable to an AI agent.

Titles, bullets, FAQs, images. All of it needs to answer the questions an agent will ask on behalf of a buyer.

If Alexa cannot explain why your product fits, it will recommend the one that can

One rule before you use it:
Delegate research, comparison and alerts.
Review before any important purchase.
The agent optimizes for Amazon. You optimize for yourself.

[Amazon News @amazonnews]

https://t.co/8AwnDMcwYu

[Manu | 🥥 @ManuAF6]

After hundreds of hours with @cursor_ai , I built a setup that actually works

Most people skip the hardest part
They jump straight to implementation.
They type "build me a login system" and let Cursor run.
Then they wonder why it drifts, overwrites things it shouldn't, and produces code they can't review.

The problem is the missing layer before the model.

There are 5 agents that cover the complete development cycle

Most setups have one.

The best setups have all five, in the right order.

Full breakdown in the article

[Manu | 🥥 @ManuAF6]

@JaysonCrypto @cursor_ai My pleasure! hope you find it usefull mate!

[Manu | 🥥 @ManuAF6]

After hundreds of hours with @cursor_ai , I built a setup that actually works

Most people skip the hardest part
They jump straight to implementation.
They type "build me a login system" and let Cursor run.
Then they wonder why it drifts, overwrites things it shouldn't, and produces code they can't review.

The problem is the missing layer before the model.

There are 5 agents that cover the complete development cycle

Most setups have one.

The best setups have all five, in the right order.

Full breakdown in the article

[Manu | 🥥 @ManuAF6]

https://t.co/BjpEDWUF2j

[Manu | 🥥 @ManuAF6]

@poteto and.. reinvents the way to unleash creativity for non-technical people... That's what cursor does for me, hahaha

[Manu | 🥥 @ManuAF6]

@benln Of course! In fact, I sent a video to the Cursor community email explaining my application and sharing some ideas for its implementation in Spain and Andorra.

If you don't mind, I'll send you the link via direct message.

[Manu | 🥥 @ManuAF6]

https://t.co/BjpEDWUF2j

[Manu | 🥥 @ManuAF6]

GPT-5.5 Instant is the best model for everyday use right now

Not because of benchmarks

Because of what actually changed

OpenAI just made it the new default layer of ChatGPT
And the numbers are real:

- 52.5% fewer hallucinated claims vs GPT-5.3 Instant in sensitive prompts like medicine, law and finance.
- 37.3% fewer inaccurate claims in difficult conversations flagged by users.

Shorter answers
Better factuality
Better image understanding
Better context memory

But the feature that changes the most is Memory Sources

Before: "Write a proposal for this client."
ChatGPT guesses what it doesn't know.

Now: it pulls from previous conversations, uploaded documents, personal preferences and connected context.

And it shows you exactly what sources it used to answer.

That is a transparent, personalized, context-aware response.
- For content creators it means less re-explaining your style every session.
- For consultants it means proposals that actually remember the client.
- For everyday users it means fewer long answers, better image analysis and real continuity between conversations.

GPT-5.5 and GPT-5.5 Pro handle the complex stuff.
But for daily use, it is the one to have open.

[Manu | 🥥 @ManuAF6]

After hundreds of hours with @cursor_ai .. this is the one thing that changed everything

It's not a model. Not a rule.

It's an agent: The Planning Agent

Here's why it's the most important one in your setup:

Cursor doesn't fail because it can't write code
It fails because it receives vague requests

You type:
"Create a login system."

And Cursor starts building but...

that request doesn't define:

- What provider to use.
- How to manage the session.
- What routes exist.
- What files can be touched.
- What current behavior must be preserved.
- What tests are required.
- What's out of scope.
- What risks exist.
- What "done" means.

So Cursor infers. And inference creates drift.

The Planning Agent fixes this.

It converts vague intention into an executable specification.

It investigates the codebase, asks clarifying questions, creates a detailed plan with file paths and code references, and waits for approval before building anything.

Cursor calls planning "the most impactful change" for working better with agents.

I agree.

Without a plan, every other agent works on a weak foundation.

With a plan, you control scope, direction and risk before a single line of code is written.

That's the difference between vibe coding that ships and vibe coding that loops forever.

[Manu | 🥥 @ManuAF6]

After hundreds of hours with @cursor_ai .. this is the one thing that changed everything

It's not a model. Not a rule.

It's an agent: The Planning Agent

Here's why it's the most important one in your setup:

Cursor doesn't fail because it can't write code
It fails because it receives vague requests

You type:
"Create a login system."

And Cursor starts building but...

that request doesn't define:

- What provider to use.
- How to manage the session.
- What routes exist.
- What files can be touched.
- What current behavior must be preserved.
- What tests are required.
- What's out of scope.
- What risks exist.
- What "done" means.

So Cursor infers. And inference creates drift.

The Planning Agent fixes this.

It converts vague intention into an executable specification.

It investigates the codebase, asks clarifying questions, creates a detailed plan with file paths and code references, and waits for approval before building anything.

Cursor calls planning "the most impactful change" for working better with agents.

I agree.

Without a plan, every other agent works on a weak foundation.

With a plan, you control scope, direction and risk before a single line of code is written.

That's the difference between vibe coding that ships and vibe coding that loops forever.

[Manu | 🥥 @ManuAF6]

@cursor_ai Man.. cursor is improving everyday.. congrats

[Manu | 🥥 @ManuAF6]

@benln Madrid.. I'll be there for sure.

[Manu | 🥥 @ManuAF6]

@OpenClawTips @OpenAI I agree... at least for now, haha