# Stop Prompt Engineering, Start Context Engineering

> Source: <https://dev.to/naimulkarim/stop-prompt-engineering-start-context-engineering-2gf5>
> Published: 2026-08-03 04:32:35+00:00

AI agents get talked about a lot, but most explanations stay abstract. Here's a short, practical breakdown of what actually makes an agent work — plus a simple example.

```
Chat:   You ask ──> Model answers ──> You act
Agent:  You set goal ──> Agent plans → acts → checks ──> Result delivered
```

Every agent — no matter the platform — runs the same loop:

```
   ┌─────────┐
   │ OBSERVE │  read context, current state
   └────┬────┘
        ▼
   ┌─────────┐
   │  THINK  │  decide next action
   └────┬────┘
        ▼
   ┌─────────┐
   │   ACT   │  execute, then loop again
   └────┬────┘
        │
        └──────► repeats until task is done
```

An agent = **LLM (brain) + Loop + Tools + Context**. The "harness" (Claude Code, Cowork, Codex, etc.) is just the app that runs this loop.

```
┌────────────────────────────┐
│ 5. Skills   → reusable SOPs │
├────────────────────────────┤
│ 4. Tools    → via MCP       │
├────────────────────────────┤
│ 3. Memory   → memory.md     │
├────────────────────────────┤
│ 2. Context  → agents.md     │
├────────────────────────────┤
│ 1. Loop     → observe→think→act │
└────────────────────────────┘
```

`agents.md`

/ `Claude.md`

)`memory.md`

)**Prompt engineering → Context engineering.** Rich context turns a 2-word prompt into a great result.

A solo creator automating their weekly newsletter:

`agents.md`

— newsletter's audience, tone, format, connected tools (Notion, Docs, social)`memory.md`

— learns preferences over time ("shorter subject lines," etc.)`weekly-newsletter`

skill → schedule it for every ThursdaySame shape every time: **context + memory + tools set up once → simple prompts → consistent results.**

`agents.md`

(role, business, tools, preferences)`memory.md`

This isn't about cleverer prompts — it's front-loading context once so every future ask can stay simple.