By skyforbes Crafting conversations for next-level results.
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“Most people hand AI a sticky note. Top performers hand it a briefing.”
You don’t need “magic prompts.” You need the proper context: your goal, your audience, your inputs, and the rules of the game. Give ChatGPT-5 (or any top model) that kind of fuel, and it works like a focused teammate — not a guessing machine.
Context is the steering wheel; the model is the engine.
What is “Context Engineering”
Context engineering provides AI with the correct information, in the proper format, at the right time, enabling it to solve the task effectively. Experts are shifting the language from “prompt engineering” to “context engineering” because results depend more on the brief and inputs than on clever phrasing.
Why it matters now:
- Bigger context windows. Models can read much more in one go — great for rich briefs. Anthropic’s Claude 3.5 Sonnet supports a 200K-token context window.
- Long-context experiments. Google’s Gemini 1.5 previewed up to 1 million tokens — enough for long docs, code, and video…