@JamisonHal13@LeoATracker Ok just to be clear what happens is that you make billions and billions of dollars? Cuz that’s what he did this year even with the “catastrophic” draw down. Hold his nuts.
As an AI Engineer. Please learn
>Harness engineering, not just prompt engineering
>Context engineering, not just long prompts
>Prompt caching vs. semantic caching tradeoffs
>KV cache management, eviction, reuse, and memory pressure at scale
>Prefill vs. decode latency and why they optimize differently
>Continuous batching, paged attention, and throughput optimization
>Speculative decoding vs. quantization vs. distillation tradeoffs
>INT8, INT4, FP8, AWQ, GPTQ, and when quantization hurts quality
>Structured output failures, schema validation, repair loops, and fallback chains
>Function calling reliability, tool contracts, argument validation, and idempotency
>Agent guardrails, loop budgets, tool budgets, and termination conditions
>Model routing, graceful fallback logic, and degraded-mode UX
>RAG architecture: chunking, embeddings, hybrid search, reranking, and freshness
>Retrieval evals: recall, precision, grounding, attribution, and citation quality
>Evals: golden sets, regression tests, adversarial tests, LLM-as-judge, and human evals
>LLM observability as a first-class discipline: traces, spans, tokens, latency, errors, and drift
>Cost attribution per feature, workflow, tenant, and user journey not just per model
>Safety engineering: prompt injection defense, data leakage prevention, and permission boundaries
>Multi-tenant isolation, cache safety, and cross-user context contamination prevention
>Fine-tuning vs. in-context learning vs. RAG vs. distillation and when each is the wrong tool
>Latency, quality, cost, and reliability tradeoffs across the full inference stack
>Production failure modes: hallucinated tool calls, malformed JSON, stale retrieval, runaway agents, and silent eval regressions
🚨 ULTIMA HORA: China lleva 43.000 millones gastados y sigue sin fabricar una sola máquina de litografía EUV.
Son 100.000 piezas, 5.000 proveedores y 60 países. ASML fabrica el 15% y es la única que sabe ensamblarla.
La distancia real ronda los 15 años.
Imagine a guy who knocks on your door every single day offering to buy your house.
Monday: "I'll give you $500k!"
Tuesday: "Actually... $430k."
Wednesday: "MARKET'S CRASHING. $350k, final offer!"
Thursday: "Never mind. $520k."
Same house. Nothing changed. He's just manic.
You'd never let that lunatic decide what your house is worth...
But that's EXACTLY what people do with stocks.
The price on your screen is just Mr. Market's mood that day... not what the company is worth.
The earnings decide what it's worth. His panic prices are just offers.
& when he shows up terrified offering me a great company at a stupid discount?
That's the day I take his deal.
Buy shares. Sell portfolio secured puts, Buy LEAP calls.