Coach•Ayòbámi 👑 ™️🇳🇬

Agentic AI

Don’t be like “me”😅

If anyone can successfully copy the link on this post I will buy you a Tesla

A HARVARD psychologist says: “if you’ve achieved nothing by 25, you’ve avoided the most destructive illusion of youth”

If you want to become a 10x software engineer, read these 10 books: 1 The Pragmatic Programmer 2 Designing Data-Intensive Applications 3 The Mythical Man-Month 4 Refactoring 5 Software Architecture - The Hard Parts 6 Working Effectively with Legacy Code 7 Database Internals 8 A Philosophy of Software Design 9 Clean Code 10 Why Programs Fail What else would you add? === 💾 Save this for later & RT to help others become good software engineers. 👤 Follow @systemdesignone + turn on notifications.

Major problem

Cyber Security Expert Roadmap

"I'm a full-stack developer" the stack:

Top 20 Excel Formulas👇

No corner, no goal. #ARSENAL #ARSMCI

BACK-TO-BACK WINNERS OF THE SUBWAY WOMEN'S LEAGUE CUP!! 🏆

@ChelseaFCW Guro is not finished. She has a lot more to offer. Sonia is not just using her right and no enough playing time. Reiten is the best

Welcome to the CFCW Oscars... 👀 The latest episode of #WeAreChelsea is out now as Erin and Guro award their teammates. 🏆

🚨 119𝐆𝐁+ 𝐆𝐎𝐎𝐆𝐋𝐄 𝐃𝐑𝐈𝐕𝐄 — 𝐀𝐋𝐋 𝐏𝐀𝐈𝐃 𝐂𝐎𝐔𝐑𝐒𝐄𝐒 🚨 𝐌𝐢𝐬𝐬𝐞𝐝 𝐢𝐭 𝐥𝐚𝐬𝐭 𝐭𝐢𝐦𝐞? 𝐈’𝐦 𝐝𝐫𝐨𝐩𝐩𝐢𝐧𝐠 𝐢𝐭 𝐚𝐠𝐚𝐢𝐧. The systems inside helped agencies secure $9K+ clients. Inside the Drive: - Machine Learning - DevOps + CI/CD - Docker & Kubernetes - Blockchain - Power BI - React + Node - Cloud Security - Linux - Pen Testing - Data Analytics - Data Science - AI & Automation - Ethical Hacking - Cybersecurity - Prompt Engineering - Google Cloud - Big Data - SQL Tableau - Python - AWS - Java Everything organized. Everything premium. 119GB+ value. Get it: ✔ Follow @Hey_Aivetra [MusT] ✔ Like & RT ✔ Comment “ Drive ” To Get Auto DM.

"Frontend is easy" The Frontend:

Is software development still worth learning in this era of AI?

As a programmer, should beginners start with Python or suffer with C first?

SQL: Database Enumeration Fundamentals Databases rarely get breached first. They get mapped first. Before any data is touched, attackers and analysts alike try to understand what databases exist, how they’re structured, and what accounts have access. Enumeration is not exploitation. It’s observation, and it’s where most beginners should start. Many people think SQL skills mean writing complex queries. In reality, the most important early skill is learning how to list databases, tables, and users safely in a controlled environment. Just seeing database names can already reveal what kind of application you’re dealing with and where sensitive information might live. In the terminal below, we connect to a MySQL database using valid credentials and perform basic enumeration. This is exactly what happens after an application compromise or during a routine audit. No injection, no tricks. Just understanding what’s there.

Starship is the largest flying object ever made and it will continue to grow

🚨 AI can now build Excel formulas like Microsoft's Power BI consultants (for free). Here are 15 insane Claude prompts that replace $150/hour spreadsheet specialists (Save for later)

How Airflow Actually Executes Your Data Pipeline (Quick Guide) 👨🏻‍💻 Most people say: “I’ve worked on Airflow.” Cool. But can you explain what actually happens after you trigger a DAG? Here’s where most engineers get exposed. Airflow is not just writing Python files. It has 3 core parts: -> Webserver. -> Scheduler. -> Metadata DB. That’s it. ==The Webserver? == Just UI - It shows graphs, logs, task status. - It does NOT run your tasks. ==The Scheduler? == This is the real brain. - It reads your DAG file. - Figures out dependencies. - Decides what should run. - Pushes tasks to the executor. No scheduler = nothing runs. Now the important part. == Executor == This decides how tasks are executed. SequentialExecutor → One task at a time. Good for learning. Bad for production. LocalExecutor → Parallel tasks. Same machine. CeleryExecutor → Distributed workers. Real production setup. KubernetesExecutor → Each task runs in its own pod. Highly scalable. Same DAG. Different executor. Completely different performance. ================================ Example: You deploy Airflow on one EC2 instance. -> Using SequentialExecutor. -> Your DAG has 15 tasks. -> They run one by one. -> Your pipeline takes 40 minutes. You switch to CeleryExecutor. Now tasks run across multiple workers. Same logic -> 10 minutes. This is what interviewers care about. Not “I used Airflow.” But: ✅ How does it schedule tasks? ✅ Where is metadata stored? ✅ How does scaling work? ✅ What happens if the scheduler dies? That’s the difference between beginner and production engineer. If you’re preparing for interviews, learn architecture. Not just DAG syntax. Want me to break down a real-world production Airflow setup next? Comment “AIRFLOW”.