WTF is AI context engineering

it's replacing prompt engineering

The AI Second Brain

What you need to know to put AI to work better, simple explained.

Deep dive in the NEW HOT “Context Engineering”:

think of prompt engineering like shouting a single order through a restaurant kitchen window: "make me something delicious!"

The NEW HOT context engineering is like being a chef who knows your dietary restrictions, what you ordered last time, the restaurant's signature dishes, and what's fresh today

The difference is massive:

prompt engineering = crafting perfect individual prompts context engineering = building intelligent information systems

It's like the difference between being good at asking questions vs building a smart assistant that already knows what you need

why this matters:

Instead of writing "write a marketing email" every time, you build a system that knows:

- your brand voice

- your audience

- your product details

- your previous campaigns

- what worked and what didn't

The AI becomes your actual marketing teammate, not just a tool

The 4 pillars of context engineering:

- memory management - short and long-term knowledge

- information architecture - how you structure context

- tool integration - connecting AI to external resources

- adaptive feedback loops - learning from each interaction

Practical example:

bad: "write a blog post about AI"

good: "you're writing for entrepreneurs aged 25-45 who are curious about ai but not technical experts. tone should be optimistic but realistic. this is part of our 'AI for small business' series."

see the difference? The AI has context, not just a task.

The context stack technique:

layer 1: system context (who you are, what you do)

layer 2: audience context (who you're serving)

layer 3: brand context (how you communicate)

layer 4: current context (what's happening now)

layer 5: task (what you want done)

Progressive context building is like having a real conversation:

session 1: "i'm launching a productivity app for freelancers"

session 2: "remember my app? let's brainstorm features"

session 3: "using our feature list, write user stories"

session 4: "based on everything we've discussed, create a launch plan"

Real-world use cases where this changes everything:

- customer support that knows purchase history and previous issues

- content creation that remembers your style and audience

- code development that understands your project structure

- email management that knows sender relationships and urgency

See how we helped other founders and teams at Google, Volvo and HeyGen put AI to work:

Getting started is easier than you think:

1. pick something you do regularly with AI

map what context is always relevant

2. create a template with role, context, objective, constraints, style

3. test for a week and refine

4. add dynamic elements over time

The future is multi-agent systems:

instead of one AI doing everything, you'll have teams:

- research agent gathers info

- analysis agent processes data

- writing agent creates content

- editor agent reviews and refines

like having a whole team that never sleeps

Why this matters for your career:

context engineering is becoming the most valuable AI skill because:

it's about systems thinking, not just writing

it creates compound value over time

it's the foundation of autonomous AI agents

most people are still stuck in prompt engineering mindset

2 things to try this week:

create a context template for your most common AI tasks

start building progressive context in your AI agents

Thanks for reading my little guide to stay on top of AI and new video is out:

BONUS: Master AI prompting in 33 min, free mini course ⬇️

Arrivederci!

- Alex Northstar, your human guide to success with AI 🌟

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