Aakash Gupta Profile picture
Apr 1, 2023 21 tweets 7 min read Read on X
Twitter revealed its algorithm to the world.

But what does it mean for you?

I spent the evening analyzing it.

Here’s what you need to know:
1. Likes, then retweets, then replies

Here’s the ranking parameters:

• Each like gets a 30x boost
• Each retweet a 20x
• Each reply only 1x

It’s much more impactful to earn likes and retweets than replies. Image
2. Images & videos help

Both images and videos lead to a nice 2x boost. Image
3. Links hurt, unless you have enough engagement

Generally external links get you marked as spam.

Unless you have enough engagement. Image
4. Mutes & unfollows hurt

All of the following hurt your engagement:

• Mutes
• Blocks
• Unfollows
• Spam reports
• Abuse reports Image
5. Blue extends reach

Paying the monthly fee gets you a healthy boost. Image
6. Misinformation is highly down-ranked

Anything that is categorized as misinformation gets the rug pulled out from under it.

Surprisingly, so are posts about Ukraine. Image
7. You are clustered into a group

The algorithm puts you into a grouping of similar profiles.

It uses that to extend tweet reach beyond your followers to similar people. Image
8. Posting outside your cluster hurts

If you do “out of network” content, it’s not going to do as well.

That’s why hammering home points about your niche works. Image
9. Making up words or misspelling hurts

Words that are identified as “unknown language” are given 0.01, which is a huge penalty.

Anything under 1 is bad.

This is really bad. Image
10. Followers, engagement & user data are the three data points

If you take away anything, remember this - the models take in 3 inputs:

• Likes, retweets, replies: engagement data
• Mutes, unfollows, spam reports: user data
• Who follows you: the follower graph Image
Shoutout to all the people analyzing:

@NFT_GOD
@amasad
@mxpoliakov
@0xCygaar
@xerocooleth
If you enjoyed this,

1. I write daily threads to help you grow. You may like to follow: @aakashg0

(But if you’re going to unfollow, go ahead and don’t!)

2. Consider RTing the first tweet so others can benefit:
As much as it's fun to analyze the Twitter algorithm, it's also fickle.

Most of my content doesn't make it to your feed.

Subscribe to the newsletter to get my best and deepest work: aakashgupta.substack.com
How to optimize for the algorithm:

Likes, then retweets, then replies
You are clustered - posting outside it hurts
Links hurt. Mutes & unfollows hurt
Misinformation is down-ranked
Images & videos help
Blue extends reach
Making up words or misspelling hurts
New learning: There’s also something known as “Heavy Ranker”

This heavily weights replies to replies and time spent on Tweet.
Additional learning:

Your follower to following ratio matters.

Following way more than follow you hurts.

Use lists. Image
The big open question is: what about bookmarks?

The predominant opinion right now is favcountparams() 30x multiplier's formula is:

Likes + Bookmarks = Favorites Count

It doesn't look to be in the code right now. Part of the problem here is what's on GitHub is incomplete.
Do you want to go the layer deeper to understand how all these code snippets and boosts work together?

I have spent the whole weekend going deeper than my Friday evening analysis.

Get the overall framework in today's newsletter: aakashgupta.substack.com/p/the-real-twi…
And here's why Twitter is the best place to get your information.

This thread was featured on the Reddit home page and Yahoo News: Image
Now that the algorithm is public, Elon Musk wants to update it every 24-48 hours.

Here's what he should do:

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Aakash Gupta

Aakash Gupta Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @aakashg0

Jul 21
Revealed: How to Succeed in Meta Product Manager Interviews.

Here's the exact doc Meta shares with candidates for its PM Interviews: Image
Image
Image
Read 7 tweets
Jul 1
Steal this template for your homepage: Image
1. Above the Fold

This is the most important part of the homepage. Too many people waste the space:

A. Convey the category of software your product is in, and how your solution differs
B. Add in wow logos from industries in your ICP (ideal customer profile)
2. Three Key Value Props

Remember the rule of threes.

Deliver on your hook above the fold and make your differentiators crystal clear.

Don't just tell, either. Show. Let people experience the product. Attio's videos move when you scroll.
Read 7 tweets
Jun 10
There’s a paradox of seniority: people get more messages, yet they are even more responsive.

This is especially true for important emails.

Here’s why: Image
THE IC LIFE

As an Individual Contributor, your work (outside of certain roles) mostly is internal to your company.

You can spend the vast majority of your day in Slack for responsive tasks.

Email responsiveness matters, but it’s not the most important thing.
THE MIDDLE MANAGER LIFE

As you become a middle manager, email starts to matter more.

You’re hiring folks externally, making calls on agencies… And there’s lots of rapid decision-making to be done cross-functionally.

Responsiveness ramps accordingly.
Read 9 tweets
Jun 1
For a company founded in '93, Nvidia's ascent to $2.7T market cap has been FAST. But what really is Nvidia's moat?

Let's break it down.

PART 1 — SOFTWARE

The story starts all the way back in the early 2000s. That's when Jensen Huang, Nvidia CEO, and his team were out meeting researchers using their products.

Most researchers were hacking graphics packages to run complex parallel compute tasks. It was not ideal. To say the least.

So, when the Nvidia team met Ian Buck, who had the vision of running general purpose programming languages on GPUs, they funded his Ph.D. After graduation, Ian came to Nvidia to commercialize the tech.

Two years later, in 2006, Nvidia released CUDA.

C ompute
U nified
D evice
A rchitecture

CUDA made all those parallelization hacks the researchers were doing available to everyone. Over time, CUDA became the default choice for researchers.

CUDA allowed accessible customization of the low-level hardware. So developers loved it.

Nowadays, when startups like MosaicML evaluate the available technology vs CUDA, they inevitably choose CUDA.

The ecosystem around CUDA has grown so robust that its lead is virtually unbeatable. This software layer is at the core of Nvidia's moat.

PART 2 — HARDWARE

The other side of Nvidia's moat is hardware. But it's not graphics cards for crypto and gaming. The hardware that matters is AI supercomputers.

The story of these supercomputers begins in the late 2000s. As Nvidia was developing CUDA, Jensen asked the team to build a supercomputer to help him build better chips.

The result was a massive supercomputer that weighed 100 pounds and strung together many GPUs with world-class networking for ultra-fast computing.

In the early 2010s, Jensen gave a talk at a conference about this AI supercomputer. Elon Musk got wind of it and said, "I want one."

So, in 2016, Jensen actually donated one to Elon Musk's relatively unknown nonprofit, OpenAI. He hand delivered it, and there's photographic proof.

OpenAI quickly learned the supercomputer worked really well. Especially for training large neural networks. That 2016 Pascal architecture delivered an impressive 19 TFLOPS of FP16 operations.

That's 19 trillion floating point operations per second. It's a massive amount. But that was just the beginning.

Since then, Jensen and the Nvidia team have been lapping the industry in delivering more TFLOPS, growing them at an exponential rate.

The latest Blackwell architecture delivers a massive 5000 TFLOPS. That's >260x AI computer in 8 years. And sells for more than $75K. But buyers like Meta, OpenAI, Google, and Amazon just can't get enough, as their internal ASICs are nowhere near Nvidia's level.

As a result, Nvidia's profits and market cap continue to soar, cementing its position as a leader in the AI hardware and software space.Image
Jensen is one of the most impressive entrepreneurs alive.

He spotted the AI revolution before any other semiconductor CEO and bet the company on it.

That's a rare trait.
And he has a rare management style as well.

He has over 60 direct reports, and doesn't have 1:1s with any of them.

He believes in sharing feedback in public, so everyone can learn from it. And he also does it to remove layers.

Quite the maverick.
Read 5 tweets
May 25
There is no one-size-fits-all when it comes to GTM.

Maja Voje and I studied 12 leading B2B SaaS companies.

(including interviews with their teams)

Here’s what we learned: Image
1. PLG is eating the world

>80% of the companies in our study employ PLG in some fashion.

Even enterprise companies like Snowflake and Salesforce are adding free trials & freemium.

It’s the new normal.
Why is this working for them?

In 2024, the best marketing is often your product.

Users rarely want to lock in a $500K+ contract without trying the product first.

But you do need to layer on a strong product-led sales motion to make enterprise work.
Read 13 tweets
May 16
There's so many ways orgs mess up transforming the product team away from the feature factory.

Here's the top one's, as I see them: Image
1. Understanding and commitment

It's not enough to just have engineering, product, and design on board for transformation.

Transformation impacts marketing, sales, customer success, finance...

You need to drive top-down alignment from the CEO and Senior Leadership Team.
2. Shifting culture

Cultural shift is often the hardest element of a transformation:

• Sales is used to promising features
• Marketing is used to dates when features will arrive

The mistake people make is to gloss over the real tensions for the sake of meeting a schedule.
Read 7 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

:(