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Day 16 – Latency & Cost Optimization LLM latency and cost scale with tokens and calls. Batching, caching, and smaller models reduce overhead. Optimize early for production use. Efficiency matters. 🚀 #GenAI #BuildInPublic

Day 17 – Model Selection Different tasks need different models. Bigger models ≠ better results. Choose based on accuracy, latency, and cost. Right model, right job. 🚀 #GenAI #BuildInPublic

Day 18 – Multimodal Models Multimodal models handle text, images, audio, and video together. They enable cross-modal reasoning and richer interactions. Use cases go beyond chat: vision, voice, and agents. One model, many senses. 🚀 #GenAI

Day 19 – Streaming & Real-Time Responses Streaming sends tokens as they’re generated. Improves perceived latency and UX. Critical for chat, voice, and agent workflows. Speed feels smarter. 🚀 #GenAI

Day 20 – Orchestration Complex GenAI systems need orchestration layers. Manages models, tools, memory, and workflows. Enables scalable, multi-step pipelines. Systems > prompts. 🚀 #GenAI #BuildInPublic

Day 21 – Observability Production GenAI needs visibility. Logs, traces, and metrics reveal failures and costs. You can’t improve what you can’t observe. Debugging starts with insight. 🚀 #GenAI

All these for 1.8-2.4LPA. A company is visiting in my college for placement drive. It requires all these skills.🥺

Day 22 – Versioning & Experimentation Prompts, models, and pipelines must be versioned. A/B testing reveals what actually works. Reproducibility beats intuition. Ship, measure, iterate. 🚀 #GenAI #BuildInPublic

Day 23 – Data Quality Model performance depends on input quality. Clean, relevant data > more data. Bad data amplifies hallucinations. Garbage in, garbage out. 🚀 #GenAI

Day 24 – Privacy & Security GenAI systems must protect user data. PII handling, access control, and secure storage are critical. Security isn’t optional at scale. Trust is built, not assumed. 🚀 #GenAI #BuildInPublic

Day 25 – Human-in-the-Loop Critical decisions need human review. HITL reduces risk and improves quality. Automation works best with oversight. Humans close the loop. 🚀 #GenAI #BuildInPublic

Day 26 – Caching & Reuse Cache frequent prompts and responses. Reuse embeddings across queries. Reduces cost and latency at scale. Don’t recompute what you can reuse. 🚀 #GenAI #BuildInPublic

I am leaving this 100 days challenge, now everything is done for me. Thanks to all of you who supported me till this point.🙏🙏

May be there will be a world war now.AajTak ABP News NDTV BBC News Hindi

Started from 0. No audience. No support. Just consistency. I’m building my coding YouTube channel from scratch 💻 If you believe in growth, support me here👇 youtube.com/@technicallaun… One day this will be BIG 🚀 #buildinpublic #coding #startup

0/1 Matrix Problem Explained 🔥 | Multi Source BFS | Crack Interviews Fast youtu.be/CRMcPzapets?si… via YouTube

Solved: Surrounded Regions (LeetCode 130) Key Learning: Reverse thinking + DFS on boundaries 🔥 Next up: Even more powerful graph problems 🚀 Stay tuned 👇 youtu.be/f4fqx0jQlC4 #DSA #Graphs #CodingJourney #LeetCode

Surrounded Regions | LeetCode 130 | DFS Graph Problem | Full Explanation... youtu.be/f4fqx0jQlC4?si… via YouTube

Number of Enclaves Explained 🔥 | DFS Grid Problem | LeetCode | Step-by-S... youtu.be/sCuNWnSy2Ms?si… via YouTube