} .glass-effect { backdrop-filter: blur(10px); background: rgba(255, 255, 255, 0.05); border: 1px solid rgba(38, 208, 124, 0.2); } .gradient-text { background: linear-gradient(135deg, #26d07c, #1fa866); -webkit-background-clip: text; -webkit-text-fill-color: transparent; background-clip: text; } .container { max-width: 900px; padding: 2rem; text-align: center; } .title { font-size: 2.5rem; margin-bottom: 1rem; animation: fadeInDown 1s ease-out; } .subtitle { font-size: 1.2rem; margin-bottom: 3rem; opacity: 0.9; animation: fadeInUp 1s ease-out 0.3s both; } .partnership-visual { display: flex; justify-content: space-around; align-items: center; margin: 3rem 0; flex-wrap: wrap; gap: 2rem; } .engineering-box { background: rgba(255, 255, 255, 0.05); backdrop-filter: blur(10px); border: 2px solid rgba(38, 208, 124, 0.3); border-radius: 20px; padding: 2rem; width: 300px; height: 200px; display: flex; flex-direction: column; justify-content: center; align-items: center; transition: all 0.3s ease; cursor: pointer; animation: fadeInLeft 1s ease-out 0.6s both; } .engineering-box:nth-child(3) { animation: fadeInRight 1s ease-out 0.6s both; } .engineering-box:hover { transform: translateY(-10px) scale(1.05); background: rgba(38, 208, 124, 0.1); box-shadow: 0 20px 40px rgba(38, 208, 124, 0.2); border-color: #26d07c; } .engineering-icon { font-size: 3rem; margin-bottom: 1rem; } .engineering-title { font-size: 1.4rem; font-weight: bold; margin-bottom: 0.5rem; color: #26d07c; } .engineering-desc { font-size: 0.9rem; opacity: 0.8; } .plus-icon { font-size: 3rem; animation: pulse 2s infinite; color: #26d07c; } .key-points { display: grid; grid-template-columns: repeat(auto-fit, minmax(250px, 1fr)); gap: 1.5rem; margin: 3rem 0; } .point-card { background: rgba(255, 255, 255, 0.05); backdrop-filter: blur(10px); border: 1px solid rgba(38, 208, 124, 0.2); border-radius: 15px; padding: 1.5rem; transition: all 0.3s ease; animation: fadeInUp 1s ease-out calc(0.9s + var(--delay)) both; } .point-card:hover { transform: translateY(-5px); background: rgba(38, 208, 124, 0.08); border-color: #26d07c; box-shadow: 0 10px 30px rgba(38, 208, 124, 0.1); } .point-number { background: #26d07c; color: #000; width: 30px; height: 30px; border-radius: 50%; display: flex; align-items: center; justify-content: center; font-weight: bold; margin-bottom: 1rem; } .point-card h4 { color: #26d07c; margin-bottom: 0.5rem; } .bottom-line { background: rgba(38, 208, 124, 0.1); border: 2px solid #26d07c; border-radius: 20px; padding: 2rem; margin: 3rem 0; animation: fadeInUp 1s ease-out 1.5s both; } .bottom-line h3 { color: #26d07c; margin-bottom: 1rem; } .cta-button { display: inline-block; background: linear-gradient(45deg, #26d07c, #1fa866); color: #000; padding: 1rem 2rem; text-decoration: none; border-radius: 50px; font-weight: bold; font-size: 1.1rem; transition: all 0.3s ease; margin-top: 2rem; animation: fadeInUp 1s ease-out 1.8s both; } .cta-button:hover { transform: translateY(-3px) scale(1.05); box-shadow: 0 10px 25px rgba(38, 208, 124, 0.3); } @keyframes fadeInDown { from { opacity: 0; transform: translateY(-30px); } to { opacity: 1; transform: translateY(0); } } @keyframes fadeInUp { from { opacity: 0; transform: translateY(30px); } to { opacity: 1; transform: translateY(0); } } @keyframes fadeInLeft { from { opacity: 0; transform: translateX(-50px); } to { opacity: 1; transform: translateX(0); } } @keyframes fadeInRight { from { opacity: 0; transform: translateX(50px); } to { opacity: 1; transform: translateX(0); } } @keyframes pulse { 0%, 100% { transform: scale(1); } 50% { transform: scale(1.1); } } @media (max-width: 768px) { .partnership-visual { flex-direction: column; } .engineering-box { width: 100%; max-width: 300px; } .title { font-size: 2rem; } }
They're best friends, not foes!
π If you prefer wordsYou still need clear prompts β context just makes them richer!
Defines format, tone, and constraints no matter how much context is added
Even the best retrieval pipelines start with system prompts
Base Prompt: "Match candidates professionally"
+ Context: Job profiles, candidate data, salary info
= Final Prompt: "Match candidates professionally.
JOB: Python Dev $90-120k
CANDIDATE: Sarah Chen - 5yrs Python
Should we proceed?"
Base Prompt: "Provide compliant HR guidance"
+ Context: Employee data, policies, leave balance
= Final Prompt: "Provide compliant HR guidance.
EMPLOYEE: John Smith, Manager
QUERY: 3 weeks leave in December
POLICY: Max 2 weeks, Dec blackout
What should I tell him?"
Base Prompt: "Calculate accurate payroll"
+ Context: Timesheets, rates, deductions, YTD totals
= Final Prompt: "Calculate accurate payroll.
EMPLOYEE: Lisa Wang
HOURS: 40 reg + 8 OT
RATE: $28/$42 per hour
Calculate this pay period."
Tobi LΓΌtke (CEO of Shopify):
"I really like the term 'context engineering' over 'prompt engineering.' It describes the core skill better: the art of providing all the context for the task to be plausibly solvable by the LLM."
Endorsed by Andrej Karpathy, AI researcher and former Tesla AI Director
π Context Engineering Survey (160+ pages)Together, they make AI powerful and predictable. Prompt engineering and context engineering work hand-in-hand to create better AI experiences.