Columns:
| # | Tweet | User | Followers | Views ▼ | Ratio | Engagement | Posted |
|---|---|---|---|---|---|---|---|
| 1 | [video] To God be the glory.
I’m grateful to have completed my MSc in Data Science.
Now it’s time to use what I’ve learned to solve blockchain problems through data. | @Ola_Crrypt ✓ | 64.9K | 29.2K | 0.5x | 1.7K | Jul 27 |
| 2 | [image] My friends think this is what I was taught during my Master’s in Data Science in the UK.
It wasn’t, survival taught me this.
Build something that can solve a real problem.
Build something that can at least make me money daily.
This used to feel impossible.
Until I started | @Ola_Crrypt ✓ | 65.3K | 11.4K | 0.2x | 142 | Jul 1 |
| 3 | [image] Guess who just followed me ? 👀 | @Ola_Crrypt ✓ | 65.0K | 9.2K | 0.1x | 212 | Jul 18 |
| 4 | [image] The richest man on Earth is launching Starship Flight 14.
Global attention, new narrative
Money follows attention 👌 | @Ola_Crrypt ✓ | 64.2K | 8.0K | 0.1x | 121 | Sep 23 |
| 5 | [image] A moving man will surely meet his luck.
Another day of yapping what I built. | @Ola_Crrypt ✓ | 65.2K | 7.8K | 0.1x | 87 | Jul 4 |
| 6 | [image] When @AxisRobotics announced the AXIS Points snapshot, I was genuinely excited.
After the recent $12M funding announcement, I thought we were about to see another major spike in contributors and trajectory submissions.
As someone who enjoys studying on-chain behaviour, it felt | @Ola_Crrypt ✓ | 64.9K | 7.8K | 0.1x | 111 | Jul 29 |
| 7 | [image] After reaching a milestone with my Telegram alert bot and seeing promising win rates, I became obsessed with a different question:
What actually makes a token become a runner?
The deeper I went into on-chain data, the more I realized there were many behaviors happening every | @Ola_Crrypt ✓ | 65.4K | 7.4K | 0.1x | 70 | Jun 24 |
| 8 | [text] One of the new philosophical analyses Aladdin will be testing is IFAGRITHM.
I’ve spent this week researching IFA, not from a religious perspective, but from the perspective of information systems.
From what I’ve studied, Ifá isn’t interesting because it claims to predict the | @Ola_Crrypt ✓ | 64.8K | 7.3K | 0.1x | 96 | Aug 6 |
| 9 | [text] Another research hypothesis I’ve been exploring since the weekend:
Some wallets consistently take less risk while capturing a good amount of upside asymmetries.
So I started finding the humans behind some of these wallets through social engineering.
And what did I notice? | @Ola_Crrypt ✓ | 64.8K | 7.1K | 0.1x | 82 | Aug 11 |
| 10 | [text] I think I might be obsessed with data.
Or maybe it’s the upside asymmetry hidden in the trenches.
Every day, thousands of tokens launch.
Most fail, some don’t.
I’ve become less interested in finding the next winner and more interested in this question:
Can repeatable | @Ola_Crrypt ✓ | 65.3K | 6.4K | 0.1x | 43 | Jun 27 |
| 11 | [image] Great evening at @SuperteamUK, diving into @solana’s technical roadmap and connecting with brilliant people from @SolanaFndn, @triton_one and the wider ecosystem 🇬🇧
I also shared the data vision behind @TradeAladdin, asked questions and received valuable insights that gave me | @Ola_Crrypt ✓ | 64.5K | 6.3K | 0.1x | 233 | Aug 31 |
| 12 | [text] Looking at one wallet is research.
Looking at 100,000 wallets is analytics.
Building labels others use is infrastructure.
Think of a supermarket.
100,000 customers walk into your shop.
Some only buy when there’s a discount.
Some always buy premium products.
Some buy every | @Ola_Crrypt ✓ | 65.8K | 6.3K | 0.1x | 166 | May 31 |
| 13 | [image] The spirit of the addiction provides for the addiction
I’m addicted to only one thing.
What are you addicted to? | @Ola_Crrypt ✓ | 64.8K | 6.1K | 0.1x | 91 | Aug 15 |
| 14 | [image] I analyzed 10,797 wallets across 155 migrated tokens on Pumpfun in last 30 days.
I wasn’t looking for “smart money.”
I was testing a different idea:
Can wallet behavior be used to identify repeatable trading strategy ?
Using a behavior-based labeling framework, I identified | @Ola_Crrypt ✓ | 65.7K | 5.6K | 0.1x | 112 | Jun 6 |
| 15 | [text] If you’ve been stuck looking for a job for months, stop looking for more advice.
Treat your career like an experiment.
Write down at least five competing hypotheses for how opportunities are created in your field.
For instance;
One meaningful relationship beats 100 | @Ola_Crrypt ✓ | 64.8K | 5.6K | 0.1x | 114 | Jul 24 |
| 16 | [image] One of the best thing we can have in CT right now is if @axisrobotics can have Outlier type of campaign
Web3 is for everyone so training physical AI should be for everyone
I’ve been tracking contributor activities on chain and I can see how everyone has been performing | @Ola_Crrypt ✓ | 64.9K | 5.6K | 0.1x | 83 | Jul 28 |
| 17 | [text] I have come to the realization that Web3 experience is geographical, personal, and contextual.
Web3 works on a timing system, which makes it impossible for individuals to have the same experience.
People don’t experience the same market, even when looking at the same chart. | @Ola_Crrypt ✓ | 66.2K | 5.5K | 0.1x | 118 | May 9 |
| 18 | [image] One thing I’ve learnt from crypto/on-chain is this:
If you can track money movement, where it’s coming from, where it’s going, and where it finally lands, you’ll also land there too.
The difference is, you got there earlier and with a better entry than 90% of people.
And the | @Ola_Crrypt ✓ | 64.5K | 5.3K | 0.1x | 141 | Apr 16 |
| 19 | [image] Aladdin scanned all migrated tokens in past 24 hours.
Detected patterns based on volume that happened before migration.
What question would you like to ask @TradeAladdin in today’s market edge? | @Ola_Crrypt ✓ | 64.7K | 4.9K | 0.1x | 104 | Aug 17 |
| 20 | [text] Dont research merely to understand in web3
Research to see different opportunities
This is how you create an edge for yourself | @Ola_Crrypt ✓ | 64.2K | 4.7K | 0.1x | 78 | Sep 18 |
| 21 | [text] One of my strongest product hypotheses about @phantom App is that they may not have capitalized enough on Solana’s changing product behaviour.
From the public data I’ve studied, it feels like the competitive lens was too horizontal:
Wallet vs wallet.
Meanwhile, Solana became | @Ola_Crrypt ✓ | 64.3K | 4.4K | 0.1x | 51 | Sep 5 |
| 22 | [image] If you’re building or you’re a researcher
Read this ;
Explained Behavioral Foot Prints in old posts
You should have tapped some ideas, i implemented same strategy
If we have an On chain terminal, then we should have a social terminal too
These are private tools used by | @Ola_Crrypt ✓ | 64.3K | 4.3K | 0.1x | 97 | Sep 10 |
| 23 | [image] Analytical + behavioral
My edge ! | @Ola_Crrypt ✓ | 64.2K | 4.3K | 0.1x | 31 | Sep 27 |
| 24 | [image] What a Day
9-5 or 24/7 ? | @Ola_Crrypt ✓ | 64.2K | 4.2K | 0.1x | 54 | Sep 18 |
| 25 | [image] Some of us analyze everything on Solana
Some of us turn Solana into an Economy
Some of us trade on solana, build on solana and also work on solana!
But not all of us are students in Solana High School. | @Ola_Crrypt ✓ | 64.2K | 4.2K | 0.1x | 48 | Sep 22 |
| 26 | [image] Thank you @hund_0x for your feed back on Aladdin
It shows it’s not perfect and likely not fit for public use.
This answers some behaviors predict token migration
Kindly Tag your best traders I’ll love to invite them into Aladdin Group Chat. | @Ola_Crrypt ✓ | 64.6K | 4.2K | 0.1x | 71 | Aug 26 |
| 27 | [image] The trench looks random until you start filtering behavior instead of narratives.
Building datasets across market cap ranges is making one thing obvious:
The best runners leave different on-chain signals before the chart explodes. | @Ola_Crrypt ✓ | 66.1K | 4.1K | 0.1x | 114 | May 19 |
| 28 | [text] I realised this after studying the incentives created when people repeatedly make money from an activity.
Many people are extremely good at hosting Spaces, farming airdrops, building communities and creating attention for projects.
There is nothing wrong with this. But you | @Ola_Crrypt ✓ | 64.7K | 4.1K | 0.1x | 59 | Aug 21 |
| 29 | [text] One thing about crypto:
You can do research and fail.
You can do research and keep it a secret.
You can bring a model that predicts and gives insights to 90% of Web2 companies and still watch it fail in Web3.
I’ve had research ideas that looked brilliant at the start.
By the | @Ola_Crrypt ✓ | 65.7K | 4.1K | 0.1x | 97 | Jun 3 |
| 30 | [image] A research-led founder (Product & On-chain Analyst)
Building Aladdin on Solana
Entering the Crypto World’s Fair Hackathon with Colosseum.
Looking to connect with technical builders and research-minded people.
Say hi 👋 | @Ola_Crrypt ✓ | 64.3K | 4.0K | 0.1x | 72 | Sep 14 |
| 31 | [text] Now look at crypto.
Pump Fun made token creation frictionless.
That changed behaviour.
More tokens, more launches new behaviors.
Then GMGN, DexScreener, Photon, Axiom, Fomo and trading terminals made discovery and execution faster.
That changed behaviour again.
Wallets | @Ola_Crrypt ✓ | 64.4K | 4.0K | 0.1x | 63 | Sep 5 |
| 32 | [image] 𝐒𝐄𝐋𝐄𝐂𝐓 𝐛𝐥𝐞𝐬𝐬𝐢𝐧𝐠 𝐅𝐑𝐎𝐌 𝐥𝐢𝐟𝐞 𝐖𝐇𝐄𝐑𝐄 𝐫𝐞𝐜𝐢𝐩𝐢𝐞𝐧𝐭 = '𝐎𝐥𝐚' 𝐀𝐍𝐃 𝐛𝐥𝐞𝐬𝐬𝐢𝐧𝐠 = '𝐣𝐨𝐛_𝐚𝐭_𝐗';
But there is no SQL terminal for prayer. Prayer is by faith.
Then I started studying human behaviour and realised something:
Even if God answers | @Ola_Crrypt ✓ | 64.2K | 4.0K | 0.1x | 73 | Sep 26 |
| 33 | [image] Shoutout to @nansen_ai for the API credits 🤝
I’m currently researching Solana on-chain winners, identifying profitable wallets and studying how they actually make money across the ecosystem, beyond just memecoin trading.
The work involves segmenting wallets by behaviour: | @Ola_Crrypt ✓ | 64.8K | 4.0K | 0.1x | 94 | Aug 12 |
| 34 | [image] Still standing on this.
FOMO is proving why labeling is alpha.
The leaderboard is revealing identity, who is actually winning.
But identity is only the first layer.
Knowing who is good is valuable.
Knowing how they repeatedly behave when they win is the next alpha.
Token → | @Ola_Crrypt ✓ | 64.5K | 3.9K | 0.1x | 62 | Aug 29 |
| 35 | [text] Desire creates behaviour.
Behaviour creates action.
Action creates friction.
Friction creates positions where people provide value and collect money.
Whoever solves the friction captures the money machine in web3
You want a 10x. That is desire.
You trade. That is behaviour. | @Ola_Crrypt ✓ | 64.2K | 3.9K | 0.1x | 64 | Sep 21 |
| 36 | [image] Setting up my @colosseum account
Will you be there this time ? | @Ola_Crrypt ✓ | 64.3K | 3.7K | 0.1x | 84 | Sep 9 |
| 37 | [text] Unrelated
But anyone who gives out a BD job out in web3 is a bozo.
Bro why can’t you do it? | @Ola_Crrypt ✓ | 64.2K | 3.7K | 0.1x | 56 | Sep 28 |
| 38 | [image] Building >> | @Ola_Crrypt ✓ | 64.2K | 3.6K | 0.1x | 46 | Sep 21 |
| 39 | [image] Data in Web3 is only useful if it leads to better outcomes.
These are a few alerts and their outcomes (2x–3x+).
The goal isn’t to find every winner, but to reduce the chances of losing. | @Ola_Crrypt ✓ | 65.5K | 3.5K | 0.1x | 90 | Jun 12 |
| 40 | [image] My previous research reduced uncertainty and consistently found 2x–3x opportunities.
But I wasn’t satisfied.
I wanted to understand why some tokens stop at 2x while others become 5x, 10x, or much larger.
So I went back to the data.
Removed assumptions and refined my research. | @Ola_Crrypt ✓ | 65.5K | 2.3K | 0.0x | 72 | Jun 17 |
| 41 | [text] From my own on-chain analysis, one thing I’ve realized about “smart wallets” is that they’re only considered smart based on the platform labeling them.
Different analysts and data scientists are behind each platform, and each team defines “smart” differently.
For example, the | @Ola_Crrypt ✓ | 65.9K | 1.9K | 0.0x | 107 | May 25 |
| 42 | [text] not everything needs to be optimized for trading, sometimes convenience matters more, and @SimpleSwap_io fits that for me | @flyingmachine36 | 875 | 1.9K | 2.1x | 48 | Apr 3 |
| 43 | [image] One thing I discovered during my wallet research is that knowing a wallet is profitable doesn’t tell you why it’s profitable.
Knowing a wallet made money doesn’t tell you how it made money.
While researching profitable wallets, I kept running into the same problem.
I’d find a | @Ola_Crrypt ✓ | 65.4K | 1.7K | 0.0x | 65 | Jun 18 |
| 44 | [image] One thing trading taught me is that outcomes are rarely random.
Wallets repeat behavior., Tokens repeat behavior, Markets repeat behavior.
The goal isn’t predicting the future.
The goal is identifying structures that historically produced better outcomes than average.
A | @Ola_Crrypt ✓ | 65.4K | 1.7K | 0.0x | 51 | Jun 20 |
| 45 | [image] GM GM 💛
The mistake people make is thinking good bot predicts winners.
Reality:
Good bot finds situations where winners occur more often than average.
No model predicts the future.
The edge comes from identifying repeatable on-chain behaviors that historically lead to | @Ola_Crrypt ✓ | 65.5K | 600 | 0.0x | 47 | Jun 18 |
| 46 | [text] Startup research is useful when a claim can be traced to a public source.
For a token project, that can mean the contract address, deployment transaction, and current liquidity not just a dashboard screenshot.
What is the first source you check before assessing a project? | @CryptoPASSP0RT ✓ | 320 | 106 | 0.3x | 9 | Sep 22 |