Frontend Developer ๐ฅ๐งhere for a good time not a long time.Superstar @superdayos
Enugu, Nigeria
Joined August 2012
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Hey guys I am starting a 100 Days Javascript Challenge where I get to build Javascript projects each day.I am tweeting this to keep myself accountable and learn with others along the way.
#100Devs #100DaysOfCode #100daysofcodechallenge
Michael Anazodo retweeted
Data Scientists: Your next career upgrade isn't another machine learning certification.
It's learning how to ENGINEER AI systems.
Right now, there are 2 types of people building with AI:
1. The API Caller
Knows how to connect to OpenAI, Claude, and other LLMs.
2. The AI Architect
Understands how LLMs actually work. And can build the systems behind them.
Both have value.
But the second skill set is a serious competitive advantage.
And Stanford just gave you a FREE way to learn it.
CS336: Language Modeling from Scratch (Spring 2026)
18 lectures covering the engineering behind modern LLMs:
โ Architecture: Tokenization, Transformers, MoE
โ Hardware: GPUs, TPUs, memory, FLOPs
โ Performance: Triton, FlashAttention, parallelism
โ Training: Scaling laws, data pipelines, distributed training
โ Deployment: Inference and evaluation
โ Post-training: SFT, RLHF, reinforcement learning
And here's the part I love.
You don't just WATCH someone build AI.
You actually:
โ
Build a Transformer from scratch
โ
Implement your own tokenizer and optimizer
โ
Write FlashAttention2 in Triton
โ
Engineer distributed training systems
โ
Turn raw web data into LLM training datasets
โ
Train a model to solve mathematical problems
This is the kind of hands-on engineering that separates knowing AI from understanding how it's built.
My advice to data scientists:
โStop collecting certifications.
โ
Start building things that force you to understand the technology.
You already have a foundation in data, statistics, Python, and ML.
Now it's time to turn that foundation into AI engineering skills.
Stanford CS336. 18 lectures. FREE.
(YouTube playlist in the comments)
โป๏ธ Repost for a data scientist who wants to become an AI engineer.
๐จ Want to learn how to build + ship AI and Data Science projects (that businesses actually want in 2026)?
On October 21st, I am hosting a free workshop to help you get started with AI + DS projects in Python (free).
Register here (500 seats): learn.business-science.io/aiโฆ
Michael Anazodo retweeted
Don't apologize for your convictions!
Don't be shameful of what is gainful!
Amen somebody?
Michael Anazodo retweeted
But moving through life, dating people within your age bracket (especially in your 20s) and dealing with them with this "provider" mentality is crazy tho'.
The lines are getting blurred between sex work and romantic relationships. Some thing are simply unrealistic, especially in
Michael Anazodo retweeted
CCI AGO, ARE YOU READY? ๐
Our Lead Pastor, Apostle Emmanuel Iren, will be live with us this Wednesday for our Special Midweek Service! ๐ฅ
And thatโs not all! Pastor Femi Okunuga will also be ministering! ๐๐ฝ
If youโre in Ago and its environs, this is your invitation! You already know this is one service you shouldnโt miss!
๐
Wednesday, 21st October 2026
โฐ 6PM
๐ Hillcrest Event Centre, Ago Palace Way
See you on Wednesday!
#CCIAgo #SpecialMidweekService #ApostleIsComing
Michael Anazodo retweeted
An epic journey unlike anything you've seen before.
Watch the exclusive official trailer for #Ramayana, coming to theaters worldwide November 5. Tickets are on sale now at Fandango - fandan.co/Ramayana
Michael Anazodo retweeted
10 books I can't recommend enough:
On your way to Software Architect
Here's the order I'd read them in again ๐
๐ญ. ๐ง๐ต๐ฒ ๐ฃ๐ฟ๐ฎ๐ด๐บ๐ฎ๐๐ถ๐ฐ ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐บ๐ฒ๐ฟ (Andy Hunt, Dave Thomas)
โณ The habits that keep you useful at every career stage.
โณ Curiosity and the will to keep learning.
๐ฎ. ๐ง๐ต๐ฒ ๐๐น๐ฒ๐ฎ๐ป ๐๐ผ๐ฑ๐ฒ๐ฟ (Robert C. Martin)
โณ How to own a mistake and defend an estimate.
โณ The professional habits that outlast any framework.
๐ฏ. ๐๐ฒ๐ฎ๐ฑ ๐๐ถ๐ฟ๐๐ ๐๐ฒ๐๐ถ๐ด๐ป ๐ฃ๐ฎ๐๐๐ฒ๐ฟ๐ป๐ (Eric Freeman, Elisabeth Robson)
โณ Patterns explained in an easy way.
โณ You stop memorizing names and start seeing where they fit.
๐ฐ. ๐๐ฒ๐ฎ๐ฑ ๐๐ถ๐ฟ๐๐ ๐ฆ๐ผ๐ณ๐๐๐ฎ๐ฟ๐ฒ ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ (Raju Gandhi, Mark Richards, Neal Ford)
โณ Your first step from features to systems.
โณ Made for devs moving into architecture.
๐ฑ. ๐ฃ๐ฎ๐๐๐ฒ๐ฟ๐ป๐ ๐ผ๐ณ ๐๐ป๐๐ฒ๐ฟ๐ฝ๐ฟ๐ถ๐๐ฒ ๐๐ฝ๐ฝ๐น๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ (Martin Fowler)
โณ The reference for problems you hit in almost every app.
โณ After it, you'll spot these patterns in code you own.
๐ฒ. ๐๐ผ๐บ๐ฎ๐ถ๐ป-๐๐ฟ๐ถ๐๐ฒ๐ป ๐๐ฒ๐๐ถ๐ด๐ป (Eric Evans)
โณ How to model messy business rules without drowning.
โณ It changes how you talk to business people.
๐ณ. ๐๐๐ถ๐น๐ฑ๐ถ๐ป๐ด ๐๐๐ผ๐น๐๐๐ถ๐ผ๐ป๐ฎ๐ฟ๐ ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ๐ (Neal Ford, Rebecca Parsons, Patrick Kua)
โณ Design for change. Requirements never sit still.
โณ Fitness functions keep your architecture honest as it grows.
๐ด. ๐๐ฒ๐๐ถ๐ด๐ป๐ถ๐ป๐ด ๐๐ฎ๐๐ฎ-๐๐ป๐๐ฒ๐ป๐๐ถ๐๐ฒ ๐๐ฝ๐ฝ๐น๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ (Martin Kleppmann)
โณ Databases, replication, and scale in plain language.
โณ The clearest system design book I've read.
๐ต. ๐๐๐ถ๐น๐ฑ๐ถ๐ป๐ด ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ฒ๐ฟ๐๐ถ๐ฐ๐ฒ๐ (Sam Newman)
โณ Read this when you're sure you actually need them.
โณ Every chapter ends in a trade-off.
๐ญ๐ฌ. ๐๐ป๐๐ฒ๐ฟ๐ฝ๐ฟ๐ถ๐๐ฒ ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ ๐ฃ๐ฎ๐๐๐ฒ๐ฟ๐ป๐ (Thierry Perroud, Reto Inversini)
โณ Architecture solutions across a whole company.
โณ For the day your scope grows past one system.
๐ ๐ข๐ป๐ฒ ๐๐ถ๐ฝ ๐ณ๐ฟ๐ผ๐บ ๐บ๐ ๐ฒ๐
๐ฝ๐ฒ๐ฟ๐ถ๐ฒ๐ป๐ฐ๐ฒ:
Pick one idea per book and ship it in your next project.
Just by reading you won't get that far.
Which of these have you read, and which one helped you the most?
Michael Anazodo retweeted
10 more books I can't recommend enough:
On your way to Software Architect (Part 2)
Here's the order I'd read them in again ๐
๐ญ. ๐๐๐ป๐ฑ๐ฎ๐บ๐ฒ๐ป๐๐ฎ๐น๐ ๐ผ๐ณ ๐ฆ๐ผ๐ณ๐๐๐ฎ๐ฟ๐ฒ ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ (Mark Richards, Neal Ford)
โณ The map of architecture styles and the "-ilities" behind them.
โณ First law: everything in software architecture is a trade-off.
๐ฎ. ๐ฃ๐ฎ๐๐๐ฒ๐ฟ๐ป๐ ๐ผ๐ณ ๐๐ป๐๐ฒ๐ฟ๐ฝ๐ฟ๐ถ๐๐ฒ ๐๐ฝ๐ฝ๐น๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ (Martin Fowler)
โณ The reference for problems you hit in almost every app.
โณ After it, you'll spot these patterns in code you own.
๐ฏ. ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ฒ๐ฟ๐๐ถ๐ฐ๐ฒ๐ ๐๐ฒ๐๐ถ๐ด๐ป ๐ฃ๐ฎ๐๐๐ฒ๐ฟ๐ป๐ ๐ถ๐ป .๐ก๐๐ง (Trevoir Williams)
โณ Saga, CQRS, and API Gateway in real .NET code.
โณ The new edition is updated for .NET 10 and C# 14.
๐ฐ. ๐๐ผ๐บ๐ฎ๐ถ๐ป-๐๐ฟ๐ถ๐๐ฒ๐ป ๐ฅ๐ฒ๐ณ๐ฎ๐ฐ๐๐ผ๐ฟ๐ถ๐ป๐ด (Alessandro Colla, Alberto Acerbis)
โณ How to apply DDD to the legacy monolith you already have.
โณ Step by step: from a big ball of mud to modules and microservices.
๐ฑ. ๐ฃ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฎ๐น ๐๐๐ฒ๐ป๐-๐๐ฟ๐ถ๐๐ฒ๐ป ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ฒ๐ฟ๐๐ถ๐ฐ๐ฒ๐ ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ (Hugo Filipe Oliveira Rocha)
โณ The real pain of events: ordering, duplicates, eventual consistency.
โณ Shows how to keep data in sync when every service owns its own.
๐ฒ. ๐ฆ๐ผ๐ณ๐๐๐ฎ๐ฟ๐ฒ ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ: ๐ง๐ต๐ฒ ๐๐ฎ๐ฟ๐ฑ ๐ฃ๐ฎ๐ฟ๐๐ (Neal Ford, Mark Richards, Pramod Sadalage, Zhamak Dehghani)
โณ How to split a system and its data when there's no best answer.
โณ Sagas, data ownership, and service size, with clear trade-off tables.
๐ณ. ๐ฆ๐๐๐๐ฒ๐บ ๐๐ฒ๐๐ถ๐ด๐ป ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐, ๐ฉ๐ผ๐น. ๐ญ (Alex Xu)
โณ A 4-step framework to design any system.
โณ Rate limiter, URL shortener, chat. Classic problems, clear diagrams.
๐ด. ๐ฆ๐๐๐๐ฒ๐บ ๐๐ฒ๐๐ถ๐ด๐ป ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐, ๐ฉ๐ผ๐น. ๐ฎ (Alex Xu, Sahn Lam)
โณ Harder cases: payment system, digital wallet, stock exchange.
โณ Worth reading even if you never plan to interview.
๐ต. ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐ถ๐ป๐ด ๐ณ๐ผ๐ฟ ๐ฆ๐ฐ๐ฎ๐น๐ฒ (Lee Atchison)
โณ How to keep high availability as traffic and teams grow.
โณ Teaches you to measure and manage risk, not hope it away.
๐ญ๐ฌ. ๐ฆ๐ถ๐๐ฒ ๐ฅ๐ฒ๐น๐ถ๐ฎ๐ฏ๐ถ๐น๐ถ๐๐ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด (Betsy Beyer, Chris Jones, Jennifer Petoff, Niall Richard Murphy)
โณ How Google keeps huge systems running: SLOs and error budgets.
โณ Architecture doesn't end at deploy. This book starts there.
๐ ๐ข๐ป๐ฒ ๐๐ถ๐ฝ ๐ณ๐ฟ๐ผ๐บ ๐บ๐ ๐ฒ๐
๐ฝ๐ฒ๐ฟ๐ถ๐ฒ๐ป๐ฐ๐ฒ:
Before you read about a pattern, find where your project needs it.
Books stick when you have a real problem to solve.
Which of these have you read, and which one helped you the most?
Michael Anazodo retweeted
System design interviews test more than whether you know individual technologies.
In this course, youโll learn a five-step framework for designing scalable systems and working through vague requirements.
Youโll apply it to systems like Spotify, Booking.com, and WhatsApp while going over architectural trade-offs.
freecodecamp.org/news/learn-โฆ
Michael Anazodo retweeted
Finished Hyperion & I cannot recommend it enough. A jewel of American sci fi. Dan Simmons was a giant & I regret discovering him on the year of his passing.
Even in a year where I have read Dune, Starship Troopers, Canticle for Leibowitz & Shadow of the Torturer-it stands tall!
Michael Anazodo retweeted
Sun Eater is a great series, btw, but you guys are not going to gaslight me into thinking itโs better than Red Rising! And remember, this is my OWN opinion: The Kingkiller Chronicles and Malazan Book of the Fallen are better than Sun Eater.
Michael Anazodo retweeted
Sunday watch? I sat with the team at @Zikoko_Mag Overthinkers Anonymous to discuss โMoney,โ including when you stop feeling poor and how money alters you.
youtu.be/qdWokvOm64k?si=fVqrโฆ
Michael Anazodo retweeted
getting ahead in life is easy with habits that protect your attention:
- start your day by journalling to organize your thoughts
- write down 3-5 things you need to do for the day.
- delete social media on your phone, or limit usage to 1hr a day
- check messages or notifications only in batches: like at 12pm and 6pm for 15 minutes
- spend 1-2 hours a day doing deep, uninterrupted work (math, coding, writing, editing, music etc)
- take breaks without screens. go for a walk, get some sunlight, or just do nothing
- use website blockers and keep your phone away when working
- read books for 20 minutes instead of scrolling before bed
I do the first 6 and it's crazy how much more intentional you become. you just get things done.
Michael Anazodo retweeted
20 things to know about AI Engineering before reading Advanced course:
- context engineering (prompt caching, KV cache, context rot)
- structured outputs (JSON schema, constrained decoding)
- tool calling & MCP
- agent loops, handoffs, termination conditions
- orchestration (LangGraph, checkpointing, HITL)
- workflow patterns (chaining, routing, parallelization)
- document parsing (OCR, layout, tables)
- chunking (recursive, semantic, overlap)
- embeddings (bi-encoders, dimensionality, MTEB)
- vector indexes (HNSW, IVF, pgvector, Qdrant)
- hybrid search (BM25 + vector, metadata filters)
- query transformation (HyDE, step-back, multi-query)
- reranking (cross-encoders)
- GraphRAG & knowledge graphs
- evals (golden sets, LLM-as-judge, Ragas)
- observability (tracing, OpenTelemetry, Langfuse)
- guardrails (OWASP LLM01, least privilege, sandboxing)
- caching & routing (semantic cache, cascades, fallbacks)
- fine-tuning (LoRA, QLoRA, DPO, distillation)
- inference serving (vLLM, quantization, continuous batching)
i am going to release this new article approximately on Monday/Tuesday
spent there already ~10 days of deep research, collected 112 resources (it's not finalized even on half yet kek) and already 8,000 words
so, everybody who is interested to figure out in AI Engineering as me, turn on your notis for the next week ๐
