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Harness Engineering Is Here. Is Prompt Engineering Dead?
🚀 From basic prompts to building full LLM harnesses, AI development has evolved. In this video, we trace the shift from Prompt Engineering to Context Engineering, and finally to the frontier of Harness Engineering.
Is prompt engineering dead? Absolutely not. Don't fall for the clickbait! While writing simple prompts isn't enough anymore, the core principles of instructing AI have simply evolved into designing robust contexts and comprehensive evaluations.
We break down a real-world problem and solve it using all three approaches side-by-side so you can see exactly how they compare.
What we cover:
🧠 Prompt Engineering: Structuring raw instructions and zero/few-shot prompts.
🗂️ Context Engineering: Dynamic data retrieval, RAG architectures, and vector databases.
🏗️ Harness Engineering: Building evaluation frameworks, automated testing, and guardrails for production agents.
⚖️ Pros & Cons: The exact tradeoffs between cost, complexity, and performance for each tier.
Whether you're vibe coding or building production-grade AI agents, this guide will help you architect more reliable AI systems.
🔔 Don't forget to Like, Subscribe, and hit the bell for more AI trends, agentic workflows, and developer tools!
#AI #PromptEngineering #ContextEngineering #HarnessEngineering #VibeCoding #LLMs #AIAgents
---------------
Links:
Vibe Coding Sessions: https://www.youtube.com/playlist?list=PL9iLtz3CXQMtiOpXBrbeAijh2pL8_nKBI
Full Learn AI Playlist: https://www.youtube.com/playlist?list=PL9iLtz3CXQMuXYz8e1uirPsau7rZNIXMw
Stay Connected: https://www.linkedin.com/in/gauravbehere/
---------------
For collaborations, ad placements, suggestions or feedback, reach out to coderashwithgaurav@gmail.com
---------------
Timestamps
00:00 - Introduction: Is Prompt Engineering Dead?
01:10 - The Three Layers of AI Engineering (The Analogy)
02:26 - Why Prompt Engineering is Evolving
04:22 - Deep Dive: What is Prompt Engineering? (Core Techiques)
07:03 - The Limits of Prompt Engineering
07:33 - Deep Dive: What is Context Engineering?
08:50 - Context-Engineered Chatbots vs. Naive Chatbots
09:30 - RAG (Retrieval-Augmented Generation) & Memory Systems
11:39 - Multi-Turn Context Management (Context Compression)
12:15 - The Limits of Context Engineering
12:45 - Deep Dive: What is Harness Engineering? (The 4 Pillars)
15:25 - Real-World Use Case: AI Code Review Pipeline
16:37 - The Harness Engineering Tools & Ecosystem
17:26 - Summary: How the 3 Layers Stack Together
18:21 - Final Take: The Future of AI Systems Engineering
---------------
Search keywords:
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Видео Harness Engineering Is Here. Is Prompt Engineering Dead? канала CodeRash with Gaurav 🚀
Is prompt engineering dead? Absolutely not. Don't fall for the clickbait! While writing simple prompts isn't enough anymore, the core principles of instructing AI have simply evolved into designing robust contexts and comprehensive evaluations.
We break down a real-world problem and solve it using all three approaches side-by-side so you can see exactly how they compare.
What we cover:
🧠 Prompt Engineering: Structuring raw instructions and zero/few-shot prompts.
🗂️ Context Engineering: Dynamic data retrieval, RAG architectures, and vector databases.
🏗️ Harness Engineering: Building evaluation frameworks, automated testing, and guardrails for production agents.
⚖️ Pros & Cons: The exact tradeoffs between cost, complexity, and performance for each tier.
Whether you're vibe coding or building production-grade AI agents, this guide will help you architect more reliable AI systems.
🔔 Don't forget to Like, Subscribe, and hit the bell for more AI trends, agentic workflows, and developer tools!
#AI #PromptEngineering #ContextEngineering #HarnessEngineering #VibeCoding #LLMs #AIAgents
---------------
Links:
Vibe Coding Sessions: https://www.youtube.com/playlist?list=PL9iLtz3CXQMtiOpXBrbeAijh2pL8_nKBI
Full Learn AI Playlist: https://www.youtube.com/playlist?list=PL9iLtz3CXQMuXYz8e1uirPsau7rZNIXMw
Stay Connected: https://www.linkedin.com/in/gauravbehere/
---------------
For collaborations, ad placements, suggestions or feedback, reach out to coderashwithgaurav@gmail.com
---------------
Timestamps
00:00 - Introduction: Is Prompt Engineering Dead?
01:10 - The Three Layers of AI Engineering (The Analogy)
02:26 - Why Prompt Engineering is Evolving
04:22 - Deep Dive: What is Prompt Engineering? (Core Techiques)
07:03 - The Limits of Prompt Engineering
07:33 - Deep Dive: What is Context Engineering?
08:50 - Context-Engineered Chatbots vs. Naive Chatbots
09:30 - RAG (Retrieval-Augmented Generation) & Memory Systems
11:39 - Multi-Turn Context Management (Context Compression)
12:15 - The Limits of Context Engineering
12:45 - Deep Dive: What is Harness Engineering? (The 4 Pillars)
15:25 - Real-World Use Case: AI Code Review Pipeline
16:37 - The Harness Engineering Tools & Ecosystem
17:26 - Summary: How the 3 Layers Stack Together
18:21 - Final Take: The Future of AI Systems Engineering
---------------
Search keywords:
prompt engineering, context engineering, harness engineering, coderashwithgaurav, AI agents, LLM agents, prompt engineering tutorial, context engineering LLM, is prompt engineering dead, prompt engineering real examples, harness engineering AI deployment, building AI agents, prompt vs context engineering, prompt engineering evolution, RAG vs context engineering, vector database context, agentic AI frameworks, AI application architecture, large language models tutorial, generative AI engineering, how to build an AI agent, prompt optimization, AI context management, AI model evaluation frameworks, few-shot prompting tutorial, prompt engineering best practices, dynamic data retrieval LLM, context windows AI, evaluating AI agents, agent deployment strategy, AI development workflow, developer guide prompt engineering, prompt engineering tools 2024, context engineering tools, LangChain context engineering, vector DB for AI context, prompt architecture, debugging LLM outputs, automated prompt testing, systematic prompt engineering, prompt engineering jobs, future of AI development, AI software engineering, structured output LLM, AI reasoning capabilities, prompt engineering for developers, full-stack AI development, operationalizing AI, context retrieval strategies, semantic search LLM, data engineering for AI context, agent-based architectures, RAG pipeline tutorial, function calling AI agents, fine-tuning vs context engineering, evaluating LLM performance, AI security guardrails, AI development best practices, scalable AI systems, AI context management, intelligent AI agents, prompt programming, context design LLM, software architecture AI, enterprise AI solutions, prompt engineering logic, structured prompting, context window optimization, evaluating RAG performance, building reliable AI, multi-agent systems AI, task automation AI agents, developer productivity AI, context vs RAG, AI agent tools, context retrieval efficiency, effective prompt writing, LLM prompt design, advanced prompt techniques, vector embeddings AI context, dynamic prompts LLM, RAG system design, debugging AI agents, robust AI applications, scalable LLM systems, prompt engineering framework, context aware applications, building production AI, prompt data engineering, software engineering principles AI, designing intelligent agents, context handling in LLMs
Видео Harness Engineering Is Here. Is Prompt Engineering Dead? канала CodeRash with Gaurav 🚀
prompt engineering context engineering harness engineering coderashwithgaurav AI agents LLM agents prompt engineering tutorial context engineering LLM is prompt engineering dead prompt engineering real examples harness engineering AI deployment building AI agents prompt vs context engineering prompt engineering evolution RAG vs context engineering vector database context agentic AI frameworks AI application architecture
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