The new frontier in AI isn’t prompt engineering — it’s context engineering. As agents become more capable, the difference between failure and success lies in what context they’re given — not how smart the model is.
💡 What is Context Engineering?
It’s the systematic design of everything a model needs to understand and solve a task — not just the prompt, but:
🧭 System Instructions
💬 Conversation History
🧠 Long-term Memory (preferences, past tasks)
📄 Retrieved Knowledge (docs, APIs, RAG)
🔧 Tool definitions
🗂️ Output formats
⚠️ Most agent failures today are not model failures — they’re context failures.
🔍 From Demo to Magic:
A “cheap demo” uses just a prompt. A “magical agent” builds context dynamically — calendar availability, past conversations, contact priority, tone — before calling the model.
🧠 Key Insight:
“The art is not in the code. It’s in giving the model exactly what it needs, when it needs it.”
🚀 Why this matters for businesses:
Context engineering enables AI systems that are more reliable, human-like, and task-complete. It’s a strategic capability for anyone serious about deploying agents in real workflows.
Context is the new code.
Engineering it well turns LLMs from tools into true assistants.
Company Details
- Founded
- -
- Industry
- Technology, Information And Internet
- Keywords
- IT Consulting.
- Competitors
- Agentic Engineering, skriptfabrik GmbH.
Context Engineering Questions
Context Engineering's website is https://www.danielmoll.com/ai/context-engineering
Context Engineering's LinkedIn profile is https://www.linkedin.com/company/context-engineer
Context Engineering's industry is
Technology, Information and Internet
Context Engineering's top competitors are
Agentic Engineering,
Skriptfabrik Gmbh.
Context Engineering's categories are Technology, Information and Internet
Context Engineering's founding year is 2025
