Master Agentic Context Engineering: ACE framework achieving +10.6% on benchmarks, RAG architecture, multi-agent systems, production patterns. Includes technical guide, code examples, and reach out for interview prep roadmap for OpenAI, Anthropic, Google.
Despite $30-40 billion in corporate GenAI spending, 95% of organizations report no measurable P&L impact. The culprit isn’t model capability – GPT-5 and Claude Sonnet 4.5 demonstrate remarkable reasoning prowess. The bottleneck is context engineering: these powerful models consistently underperform because they receive an incomplete, half-baked view of the world.