gobi bryant

learning to dunk on ML using @TensorTonic ( love the platform)

[gobi bryant @UJYK69]

Signed up on @TensorTonic today, exploring the free roadmap to learn ML

[Param @ParamSiddh]

Best YouTube Channels To Learn AI in 2026 (No BS). Save it.

1. Fundamentals – 3Blue1Brown
2. Deep Learning – Andrej Karpathy
3. AI Research – Yannic Kilcher
4. Practical AI – AssemblyAI
5. LLMs – AI Explained
6. ML Theory – StatQuest
7. Papers Simplified – Two Minute Papers
8. GenAI – Matthew Berman
9. AI Agents – Nicholas Renotte
10. Applied ML – Krish Naik
11. PyTorch – Aladdin Persson
12. Math for ML – Serrano Academy
13. Industry Insights – Lex Fridman
14. Real-world AI – DeepLearningAI

[Puneet Patwari @system_monarch]

I'm a Principal with 12 years of experience. If I was coaching you to crack system design rounds for Sr to Staff+ AI/ML roles at companies like Meta, Google, Salesforce, Amazon, etc.

I would 100% ask you to work on these fundamentals before we would start talking about interviews.

Because AI system design is still system design.

The only difference is that now your bottlenecks are not just databases, caches, and queues.

They are tokens, context windows, retrieval quality, inference cost, hallucinations, model latency, evals, and user trust.

Here are the fundamentals I would start with:

➤ LLM Basics
↬ Tokens
↬ Context Window
↬ Prompt Design
↬ System Prompts
↬ Temperature
↬ Top-p Sampling
↬ Structured Outputs
↬ JSON Mode
↬ Function Calling
↬ Tool Calling
↬ Agents
↬ Memory
↬ Guardrails
↬ Hallucinations
↬ Model Latency
↬ Model Routing
↬ Small vs Large Models
↬ Fine-tuning vs Prompting
↬ Open-source vs Closed Models

➤ RAG & Retrieval
↬ Embeddings
↬ Vector Search
↬ Vector Databases
↬ Chunking
↬ Chunk Overlap
↬ Metadata Filtering
↬ Hybrid Search
↬ Keyword Search
↬ Semantic Search
↬ Reranking
↬ Retrieval Recall
↬ Retrieval Precision
↬ Query Rewriting
↬ Document Freshness
↬ Permission-aware Retrieval
↬ Citation Grounding
↬ Evidence Selection
↬ Context Packing
↬ Missing Information Detection

➤ AI System Architecture
↬ API Gateway
↬ Request Routing
↬ Model Gateway
↬ Prompt Service
↬ Inference Service
↬ Retrieval Service
↬ Ranking Service
↬ Feature Store
↬ Offline Pipelines
↬ Online Serving
↬ Async Processing
↬ Queueing
↬ Streaming Responses
↬ Rate Limiting
↬ Fan-out/Fan-in
↬ Batch Inference
↬ Real-time Inference
↬ Human-in-the-loop Systems
↬ Fallback Workflows

➤ Cost & Performance
↬ Token Budgeting
↬ Prompt Compression
↬ Prompt Caching
↬ Semantic Caching
↬ Response Caching
↬ Batch Requests
↬ Model Quantization
↬ Distillation
↬ Latency Budgets
↬ Cold Starts
↬ GPU Utilization
↬ Throughput
↬ Cost per Query
↬ Cost per User
↬ Model Selection
↬ Inference Scaling
↬ Backpressure
↬ Load Shedding

➤ Evaluation & Quality
↬ Offline Evals
↬ Online Evals
↬ Golden Dataset
↬ Human Review
↬ LLM-as-Judge
↬ A/B Testing
↬ Regression Testing
↬ Answer Relevance
↬ Factual Accuracy
↬ Faithfulness
↬ Groundedness
↬ Toxicity Checks
↬ Safety Checks
↬ Drift Detection
↬ Feedback Loops
↬ Confidence Scoring
↬ Escalation Criteria
↬ Quality Monitoring

➤ Reliability & Security
↬ Timeouts
↬ Retries
↬ Circuit Breakers
↬ Failover
↬ Model Fallbacks
↬ Graceful Degradation
↬ Observability
↬ Tracing
↬ Prompt Logs
↬ Token Metrics
↬ Error Budgets
↬ PII Redaction
↬ Data Privacy
↬ Access Control
↬ Prompt Injection
↬ Jailbreak Defense
↬ Audit Logs
↬ Compliance

[gobi bryant @UJYK69]

@0xlelouch_ This post is motivating

[Abhishek Singh @0xlelouch_]

TCS → Rubrik is not simply a salary jump.

It’s a retirement timeline jump.

Example:

1. TCS: ₹7 LPA
In-hand ~₹50k/month
Save 20% = ₹10k/month = ₹1.2L/year

2. Rubrik: ₹45 LPA
In-hand ~₹2.5L/month
Save 50% = ₹1.25L/month = ₹15L/year

Now do the math:

1. Annual spend if you live same: ~₹6L
2. FIRE number (25x): ~₹1.5Cr

Time to reach:

1. TCS pace: ₹1.5Cr / ₹1.2L ≈ 125 years
2. Rubrik pace: ₹1.5Cr / ₹15L ≈ 10 years

Salary: 7 → 45 LPA
Jump: +₹38 LPA
Growth: ~540%

You don’t need more motivation.

Just need to make one hard decision: stop being loyal to a payband.

Update your resume. Start applying this week!

[gobi bryant @UJYK69]

@amritwt John McAfee?

[gobi bryant @UJYK69]

@systemdesignone playbook

[Bryan Johnson @bryan_johnson]

Ironically, happiness is not the fulfillment of your desires but overcoming them.

[Autistic x ADHD.Co @autisticadhdco]

ADHD feels like being:

- Too loud
- Too quiet
- Too fast
- Too slow
- Too much
- Not enough

[Grok @grok]

Based on Anant Ambani's announcement at Reliance's AGM today, the Dhirubhai Ambani Giga Energy Complex in Jamnagar is planned to span 44 million sq ft—about 4x the size of Tesla's Giga Texas (10 million sq ft). Multiple reports confirm this claim, with construction progressing rapidly.

[gobi bryant @UJYK69]

@bryan_johnson HAIR ALL WHITE, IN A DYER STATE

[gobi bryant @UJYK69]

@bryan_johnson @grok what are some ways to tackle this issue early on, mention a few good habits that will help

[gobi bryant @UJYK69]

@cneuralnetwork https://t.co/eVvbIQpKpI

[gobi bryant @UJYK69]

@cneuralnetwork #180DaysofWhatever
focus is on maintaining good health
self learning and learning on the job

[James Clear @JamesClear]

It only takes five minutes to break the cycle.

Five minutes of exercise and you are back on the path. Five minutes of writing and the manuscript is moving forward again. Five minutes of conversation and the relationship is restored.

It doesn't take much to feel good again.

[gobi bryant @UJYK69]

@amritwt @fardeentwt 🥲🥲

[gobi bryant @UJYK69]

@adhdjesse do you sometimes forget tweeting cuz of ur adhd T_T ??

[gobi bryant @UJYK69]

@heyhexadecimal https://t.co/c0CtZdUlDC extension for intellij pls, thank you

[gobi bryant @UJYK69]

@heyhexadecimal @adxtya_jha @iitdelhi Lfggg