If you’re hunting for a remote job, you just need to figure out how Reddit works, and you’ll never be unemployed for a long time.
Here’s a list of subreddits you should bookmark right now:
Google Brain founder Andrew Ng:
"Prompting will be dead in 6 months"
"Loops and graphs are replacing it"
In just 2 hours, he shows how to build agents that work, learn, and improve on their own
LLMs → Agents → Loops → Graphs → Self-Improving Systems
The first 15 minutes alone are more valuable than most $500 AI courses
Most people are still learning prompts while AI engineering is already moving beyond them
Watch the lecture first
Then read the full guide to loops and graphs below ↓
I learned basic system design.
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Drew a client, server, and database.
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"Looks scalable enough."
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Added 1 million users to the question.
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Server died.
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Added another server.
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"Wait, how does traffic know where to go?"
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Learned load balancers.
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Database became the bottleneck.
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Added read replicas.
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Writes were still slow.
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Learned indexing.
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Added a cache because everyone kept saying "use Redis."
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"Wait, what happens when the cache is stale?"
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Learned cache invalidation.
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One service started taking 8 seconds.
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Added a message queue.
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"Wait, what if the message gets processed twice?"
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Learned idempotency.
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Users started uploading huge files.
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Stopped storing them in the database.
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Learned object storage and CDNs.
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One region went down.
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Learned replication and failover.
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Realized every new box creates another problem.
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Finally understood system design.
Jokes aside.
Beginner system design feels overwhelming because people throw around terms like sharding, Kafka, Redis, CDNs, queues, replicas, and microservices.
You do not need to memorize all of them.
Start with one simple system:
Client → Server → Database
Then keep asking: "What breaks if traffic becomes 10x?"
WhatsApp Status disappears after 24 hours.
2 billion users post daily.
You can’t run a cron job to delete them. It’ll kill the DB.
How would you design it?
this is f*cking gold
How to build your first AI agent (Full guide)
if I had this a year ago, I would've shipped my first agent in a day instead of 2 weeks in the right hands, this changes everything:
If I were in my 30s or 40s right now and wanted to leverage AI to retire within 10 years, here's what I'd do:
1. Immediately form an LLC company. Not next month. Not once you're 'ready.' This week.
CANCEL your weekend plans.
You NEED to:
• Learn golden dataset design for regression testing AI systems
• Build 2-3 LLM-as-a-judge pipelines with bias calibration
• Set up grounding and citation quality metrics for RAG
• Learn adversarial evals for hallucination and jailbreak resistance
• Master cost-quality tradeoff analysis across model versions
• Build your own human eval framework that scales beyond one-off reviews
• Create automated eval gates in CI/CD for AI deployments
• Experiment with shadow deployments for output comparison
• Try DeepEval, RAGAS, TruLens for different eval dimensions
• Learn how to measure user trust in AI outputs quantitatively
• Build evals that detect drift in model behavior over time
• Run evals on competitor AI products to benchmark your own
• Learn to communicate eval results to non-technical stakeholders
• Use LangSmith/LangFuse for eval tracking and visualization
• Build one public eval report comparing models or architectures
• Read eval research instead of model release announcements
• Start sharing your eval methodology and findings publicly
• Learn how evaluation actually drives product decisions in AI teams
You have way too much to do.
@suraj_sharma14
#AIEvaluation #LLMOps #ReliableAI #July2026
Anthropic engineer:
"You're not supposed to prompt Claude. You're supposed to build a system that prompts itself."
In 45 minutes she shows exactly how to build an agent that improves itself.
Most people are still doing all of this by hand.
Watch the session, then save the guide below.
Anthropic just paid millions to hire Andrej Karpathy.
He gave you the same knowledge for $0 the same week.
Co-founder of OpenAI. Former head of AI at Tesla. The man who coined vibe coding.
No recruitment fee. No exclusive access. Just a link and 29 minutes.
LLMs are ghosts not animals.
Vibe coding is dead.
Software 3.0 is here.
Watch it.
Then read this.
Because Karpathy tells you what Software 3.0 is.
This shows you how to build one - a software factory with Claude Code that ships features while you sleep.
The full build guide is below.
Anthropic pays $750,000+ a year for engineers who can build LLM architectures from scratch.
This 2-hour Stanford lecture gives you the exact pipeline LLM engineers get paid $750K/year for.
Data + architecture + scaling laws + post-training.
Bookmark it & watch today. Then read article below.
🚨 Anthropic's own team just showed how to actually use Claude Code properly.
30 minutes. free. the person who created Claude Code.
watch the workshop. bookmark it.
worth more than every $500 course you almost bought.
you've been using Claude without knowing 40 of its commands.
Then read the guide below.