Conversational Development With Claude Code — Part 4
TL;DR — Claude Code is not powered by perfect prompts, but by well‑designed context. To work with intention and precision, you must understand five pillars: the context window, subagents, the Model Context Protocol (MCP), the CLI, and context engineering. Together, they explain how Claude thinks, remembers, and collaborates — and how you can build reliable systems without micromanaging an LLM.
Why Context Beats Prompts
Most failures with AI tooling do not come from weak models, but from poorly designed context. Developers chase the mythical “perfect prompt” when the real leverage lies elsewhere: in what the system can see, remember, and prioritize.
Claude Code is designed for engineers who think in systems, not incantations. It rewards structure, references, and intent — not verbosity.
The Context Window: Claude’s Working Memory
The context window is Claude Code’s working memory. It contains everything the model can reason about at once: source code, conversations, command outputs, and intermediate results.
By default, Claude Code operates with ~200,000 tokens, with an optional 1M‑token window for larger projects. That scale is enough to analyze medium‑to‑large codebases without artificial fragmentation.
Key properties of the context window:
- It holds code, conversation, and execution results together
- It prioritizes relevance over chronology
- It automatically evicts low‑value information when space is constrained
This is not long‑term memory. It is active cognition.
When the window fills, Claude does not panic — it compresses. Your job is to ensure what remains is what matters.
Memory Hygiene: References Over Copy‑Paste
The fastest way to poison context is to paste massive blocks of code.
Instead, Claude Code is designed around references:
- Reference files using
@path/to/file - Let Claude load only what it needs
- Re‑anchor decisions explicitly when starting new sessions
If Claude begins to “forget,” the fix is not repetition — it is reset and refocus.
Open a new session. Re‑reference the critical files. Restate architectural constraints. Continue.
Clean context beats persistent noise.
Subagents: A Modular Team, Not a Monolith
Subagents are where Claude Code stops feeling like a tool and starts behaving like a team.
Each subagent operates with:
- Its own isolated context
- Specialized instructions
- Dedicated tools
Think of them as focused collaborators:
- Architecture agent — analyzes system structure and constraints
- Backend agent — designs and implements APIs
- Frontend agent — builds UI components and state flows
- QA agent — validates behavior, tests, and edge cases
The main session becomes a coordinator, not a bottleneck.
This mirrors real engineering teams: specialization without fragmentation.
When to Invoke Each Subagent
Use subagents deliberately:
- Backend agent → endpoints, schemas, integrations
- Frontend agent → components, UX flows, state management
- QA agent → tests, regressions, validation
- Architecture agent → refactors, boundaries, long‑term decisions
If your main conversation feels crowded, you waited too long.
MCP and the CLI: The Nervous System
Claude Code lives in the terminal. MCP (Model Context Protocol) extends its reach.
Together, they form a tight loop:
- MCP connects Claude to real tools
- The CLI executes commands and returns truth
- Claude interprets, not guesses
With MCP, Claude can:
- Query databases
- Run automated tests (e.g. Playwright)
- Inspect GitHub issues and pull requests
- Interact with tools like Figma or Zapier
Once configured, these integrations feel native — not bolted on.
Using the CLI Without Breaking Flow
The CLI is not a side channel; it is the execution layer.
Best practices:
- Prefix commands with
!to execute - Let Claude read and interpret outputs
-
Keep roles clear:
- Terminal → execution
- Editor → writing
- Browser → validation
Claude reasons after commands run. That distinction matters.
Context Engineering: Designing Shared Thought
Context engineering is not prompt engineering.
It is the discipline of shaping a shared thinking space.
In practice:
- Define purpose before action
- State constraints explicitly
- Reference files instead of pasting code
- Specify quality bars and anti‑patterns
- Remove irrelevant information aggressively
Avoid vague instructions. Ambiguity creates noise.
Precision creates leverage.
Final Thoughts
Claude Code does not replace judgment — it amplifies it.
When you treat context as an architectural artifact, not a side effect, the system becomes predictable, composable, and trustworthy.
You stop chasing prompts.
You start designing cognition.
That is the real upgrade.
— Written by Cristian Sifuentes
Senior Software Engineer · AI‑Driven Architecture
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