Schlagwort-Archive: Programming

Claude Code: If you’re still typing instructions into Claude Code like you’re asking ChatGPT for help, you’re missing the entire point

Source: https://diamantai.substack.com/p/youre-using-claude-code-wrong-and

If you’re still typing instructions into Claude Code like you’re asking ChatGPT for help, you’re missing the entire point. This isn’t another AI assistant that gives you code snippets to copy and paste. It’s a different species of tool entirely, and most developers are using maybe 20% of what it can actually do.

Think of it this way: you wouldn’t use a smartphone just to make phone calls, right? Yet that’s exactly what most people do with Claude Code. They treat it like a glorified autocomplete engine when it’s actually a complete development partner that lives in your terminal, understands your entire codebase, and can handle everything from architecture decisions to writing documentation.

The gap between casual users and power users isn’t about technical knowledge. It’s about understanding the workflow, knowing when to intervene, and setting up your environment so Claude delivers production-quality results consistently. This guide will show you how to cross that gap.

Your Development Partner Lives in the Terminal

Picture working with a senior developer who never gets tired, can read thousands of files in seconds, and has instant access to the entire internet. That’s Claude Code. It connects Anthropic’s AI models directly to your project through the command line. You describe what you need in plain language, and it plans solutions, writes across multiple files, runs tests, and implements features.

But here’s what makes it different from every other coding tool: it actually understands context. Not just syntax highlighting or function signatures. Real context. It reads your project structure, sees your existing patterns, runs your tools, and even fetches information from external sources when needed.

The catch is this: giving it instructions is a skill. A learnable skill, but a skill nonetheless. The difference between getting mediocre results and getting genuinely useful code comes down to how you communicate and how you structure your workflow.

The One Rule That Changes Everything

Here’s where most people go wrong immediately: they start coding right away. It’s like walking into a contractor’s office and saying “start building my house” without showing blueprints, discussing materials, or even agreeing on what kind of house you want.

The result? You’ll get a house. It might even have walls and a roof. But it probably won’t be what you imagined.

Always start in plan mode. Before giving any instructions, press shift-tab to cycle into planning mode. Tell Claude to explore your codebase first, but specifically tell it not to write anything yet. Let it read the relevant files, understand the architecture, and grasp the bigger picture.

Once it’s explored, ask for a proposal. Not the simplest solution, not the fastest solution. Ask it to think through options starting with the most straightforward approach. Then discuss that plan like you would with a colleague. Question assumptions. Refine the approach. Push back if something seems off.

Only after you’re confident it understands the task should you tell it to start coding.

This feels slower at first. Your instinct will be to just dive in and start building. Resist that instinct. Planning five minutes saves fixing broken implementations for an hour. Every single time.

Precision Beats Brevity Every Time

Vague instructions produce vague results. Say “fix the bug” and you might get a fix, or you might get a complete rewrite that breaks three other features. There’s no middle ground here.

Instead, be surgical with your instructions. Point to specific files. Reference exact functions. Mention line numbers if you have them. Compare these two approaches:

“Fix the authentication issue.”

versus

“In the login.js file in the auth folder, update the token validation function to handle expired tokens without crashing.”

The second version leaves no room for misinterpretation. It guides Claude exactly where to look and what to do.

This precision applies to style and patterns too. If you want code that matches your existing codebase, say so explicitly. Point Claude to well-written examples in your project. It can mirror patterns beautifully, but only when you show it the pattern you want.

Think of it like directing a movie. You wouldn’t tell an actor “do something emotional.” You’d say “show hesitation, then determination, with a slight smile at the end.” Same energy here.

Your Most Powerful Tool Is the Escape Key

Claude works best as a collaborative partner, not an autonomous robot. The Escape key keeps you in control.

See Claude heading down the wrong path? Hit Escape immediately. This stops it mid-process while keeping all the context intact. You can redirect without losing the work already done. It’s like tapping someone on the shoulder mid-sentence and saying “wait, different approach.”

Double-tap Escape to jump backward through your conversation history. This lets you edit a previous prompt and explore an alternative direction. You can iterate on the same problem multiple times, trying different solutions until one clicks.

If Claude makes changes you don’t like, just tell it to undo them. It can revert files instantly. Combined with regular checkpoints, this means you can experiment fearlessly. The safety net is always there.

Understanding the Different Modes

Claude Code has multiple modes, and knowing when to use each one separates beginners from experts.

Plan mode is for thinking, not doing. Use it when starting new features or untangling complex problems. It will architect solutions without touching your files. This is your strategy phase.

Code mode is for building. Once you have a solid plan, switch to code mode and let it implement. But stay alert. Watch what it’s doing and be ready to course-correct.

Auto-accept mode removes the approval step for each change. It’s fantastic for straightforward tasks but dangerous for anything complex or important. For critical work, stay manual and review everything.

Bash mode lets you run terminal commands and feed the output directly into Claude’s context. This is debugging gold. Run your tests, capture the failures, and immediately ask Claude to fix them without copying error messages around.

Each mode has its place. The trick is recognizing which situation calls for which mode.

Managing Context Before It Manages You

Claude Code’s biggest weakness is context window limits. As sessions grow longer, it starts forgetting earlier information. Power users have strategies to handle this.

Use the /compact command regularly. It clears old execution results while keeping the important conversation history. Think of it like cleaning your desk: you keep the critical documents but toss the scrap paper.

For complex projects, create a CLAUDE.md file in your project root. This becomes permanent memory. Put your project overview, architecture decisions, coding standards, and common patterns there. Claude reads it automatically and uses it as context for every task. It’s like giving every session a primer on how your project works.

For massive tasks, use a checklist file. Create a markdown document with all the steps needed to complete the task. Tell Claude to use it as a scratchpad, checking off items as it progresses. This keeps the main conversation clean while giving Claude a progress tracker.

Divide Complex Work with Subagents

When facing a genuinely complex problem, break it apart and assign pieces to different subagents. Tell Claude to spin up a subagent for the backend API while the main agent handles the frontend. Or have one subagent research documentation while another writes implementation code.

You can even mention subagents directly with the @ symbol to guarantee they activate. You can also specify which model each subagent should use. Opus 4 handles complex planning and architecture. Haiku 3.5 knocks out simple, fast tasks.

This approach tackles problems in parallel and keeps context focused. Each subagent deals with one slice of the problem without getting overwhelmed by the full complexity. It’s like having multiple specialists working on different parts of a project simultaneously.

Show, Don’t Tell

Claude Code can interpret visual information. Drag screenshots directly into your terminal. Show it UI mockups, error messages, or architecture diagrams. It will understand the visual context and use it to guide implementation.

This is especially powerful for debugging interface issues. Instead of describing what’s wrong with your layout, just show a screenshot. For replicating designs, provide the mockup and let Claude figure out the implementation details.

Visual context often communicates more than words ever could. A single screenshot can replace three paragraphs of explanation. Use this liberally.

Automate Everything, Then Automate the Automation

Claude Code excels at repetitive tasks. But power users go further: they automate the automation itself.

Set up custom slash commands for tasks you repeat constantly. Create a command that loads your project context, runs your test suite, and generates documentation in one go.

Use hooks to trigger actions automatically. Run tests after every code change. Lint before commits. Update documentation when finishing features. These small automations compound into massive time savings.

For data processing pipelines, integrate Claude directly into your workflow. Pipe data in, let it transform or analyze the data, and pipe the output to the next step. This turns Claude into a powerful processing node in your toolchain.

Extended Thinking for Complex Problems

For genuinely difficult problems, use extended thinking commands like /think or /ultrathink. These increase Claude’s reasoning budget, giving it more time to work through complicated challenges.

Yes, it takes longer. But the quality difference is dramatic for debugging, architecture planning, and design decisions. It’s the difference between asking for a quick answer versus asking someone to really think through a problem thoroughly.

The ultrathink command is particularly powerful. It provides the maximum thinking budget, perfect for architectural decisions or bugs that have stumped you for hours. Use it sparingly, but when you need it, you really need it.

Git Workflows That Keep You Safe

Never work directly on your main branch with Claude Code. Always create a feature branch first. This gives you a safe sandbox to experiment in.

Even better, use Git worktrees. This lets you maintain multiple working directories for different branches, so you can have Claude working on several features in parallel without interference.

When Claude finishes a task, have it commit changes with a clear message explaining what was done. Then review the commit diff carefully before merging. This workflow gives you the safety of version control while letting Claude work autonomously.

Embed Your Standards in Documentation

Instead of reminding Claude about coding standards in every conversation, embed them directly in documentation files. Create a QUALITY.md file with your coding standards, testing requirements, and review checklist.

Claude will read this automatically and follow your standards without being told. It becomes part of the project context, like a senior developer who knows the house rules and follows them instinctively.

For teams, this ensures consistency across all Claude Code sessions. Everyone gets the same quality bar, regardless of who’s running the tool.

The MCP Revolution

Model Context Protocol servers extend Claude Code’s capabilities dramatically. Connect it to your Slack, Figma, Google Drive, or custom data sources. This transforms Claude from a code assistant into a genuine team member that can pull information from anywhere.

Need to check the latest design mockup? Claude fetches it from Figma. Need to understand a business requirement? It pulls it from Slack.

Set up MCP servers for your most-used tools. The initial setup takes time, but the payoff is enormous. Claude becomes infinitely more capable when it can access your actual data sources.

Debugging Strategy

Claude Code is exceptional at debugging when you give it proper information. When you hit a bug, don’t just paste the error message. Use bash mode to run your tests and feed the full output to Claude. Tell it to analyze the stack trace, read the relevant files, and propose a fix.

For intermittent bugs, run the failing code multiple times and give Claude all the outputs. It can spot patterns in failures that humans miss.

If bugs involve external services, use Claude to fetch relevant documentation or logs. It can correlate error messages with API documentation to pinpoint exactly what’s wrong.

Self-Writing Documentation

One of Claude Code’s most underrated features is documentation generation. After finishing a feature, tell Claude to update the README, API docs, and changelog. It has full context of what was just built, so it writes accurate, comprehensive documentation without requiring explanation.

This is especially powerful after refactors, where documentation typically gets forgotten. Set up a hook to automatically generate documentation after every feature merge. Your docs will stay synchronized with your code effortlessly.

Managing Token Usage in Long Sessions

Long Claude Code sessions can get expensive as context grows. Smart users manage this proactively.

Break large tasks into smaller chunks. Complete one chunk, commit it, then start a fresh session for the next chunk. This keeps context size manageable and costs reasonable.

Use prompt caching for information that doesn’t change often. Load your project overview and standards once, then reference them in subsequent sessions. This dramatically reduces token usage.

For repetitive tasks across many files, use a script to process them in batches rather than one giant session. This parallel approach is both faster and more cost-effective.

The Checklist Method for Large Migrations

For migrations, massive refactors, or fixing hundreds of lint errors, the checklist method is unbeatable.

Create a markdown file listing every task that needs completion. Tell Claude to use this as its working document, checking off items as it completes them and adding notes about any issues.

This approach does two crucial things. First, it gives Claude a clear roadmap, preventing it from getting lost in complexity. Second, it lets you track progress and see exactly what’s been done.

For truly large codebases, break the checklist into sections and tackle them in separate sessions. This keeps each session focused and productive.

Accelerating Learning and Onboarding

Claude Code is an incredible learning tool. New team members can ask it to explain the codebase, trace through execution flows, and understand architecture decisions.

Have newcomers ask Claude to map out the project structure and identify key components. Then they can ask specific questions about how things work. This accelerates onboarding from weeks to days.

For existing team members exploring unfamiliar parts of the codebase, Claude provides guided tours. Ask it to explain the authentication flow or the data pipeline, and it will trace through the code, explaining each piece clearly.

Beyond the Code

Claude Code can do much more than write software. Use it for research tasks, like reading documentation and creating summaries for future reference. It can analyze logs, process data files, and generate reports.

Need to understand a new API? Have Claude read the documentation and create a usage guide. Working with a large CSV file? Pipe it into Claude and ask for analysis.

These non-coding tasks often consume huge amounts of developer time. Claude can handle them while you focus on the creative problem-solving that actually requires human intelligence.

Avoiding Common Traps

Even experienced users make mistakes. Here are the most frequent ones and how to sidestep them.

Trusting auto-accept mode for complex tasks is dangerous. Auto-accept is convenient but risky for anything affecting core functionality. Always review changes manually for important work.

Letting sessions run too long accumulates context and makes everything slower and more expensive. Refresh your session regularly, especially after completing major milestones.

Not using version control is asking for trouble. Always use branches, and always review diffs before merging.

Being too vague leads to assumptions. Those assumptions might not match your intent. Take time to be precise.

Ignoring the plan phase might feel faster, but it leads to rework. The few minutes spent planning save hours of fixing wrong implementations.

10 Programming Languages You Should Learn in 2014

10 Programming Languages You Should Learn in 2014

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Image: Mashable, Nina Frazier Hansen
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By Rebecca Hiscott

The tech sector is booming. If you’ve used a smartphone or logged on to a computer at least once in the last few years, you’ve probably noticed this.

As a result, coding skills are in high demand, with programming jobs paying significantly more than the average position. Even beyond the tech world, an understanding of at least one programming language makes an impressive addition to any resumé.

The in-vogue languages vary by employment sector. Financial and enterprise systems need to perform complicated functions and remain highly organized, requiring languages like Java and C#. Media- and design-related webpages and software will require dynamic, versatile and functional languages with minimal code, such as Ruby, PHP, JavaScript and Objective-C.

With some help from Lynda.com, we’ve compiled a list of 10 of the most sought-after programming languages to get you up to speed.

1. Java

Java

Image: Mashable composite. Image: Wikimedia Commons

What it is: Java is a class-based, object-oriented programming language developed by Sun Microsystems in the 1990s. It’s one of the most in-demand programming languages, a standard for enterprise software, web-based content, games and mobile apps, as well as the Android operating system. Java is designed to work across multiple software platforms, meaning a program written on Mac OS X, for example, could also run on Windows.

Where to learn it: Udemy, Lynda.com, Oracle.com, LearnJavaOnline.org.

2. C Language

C Language

Image: Mashable composite. Image: Wikimedia Commons

What it is: A general-purpose, imperative programming language developed in the early ’70s, C is the oldest and most widely used language, providing the building blocks for other popular languages, such as C#, Java, JavaScript and Python. C is mostly used for implementing operating systems and embedded applications.

Because it provides the foundation for many other languages, it is advisable to learn C (and C++) before moving on to others.

Where to learn it: Learn-C, Introduction To Programming, Lynda.com, CProgramming.com, Learn C The Hard Way.

3. C++

C Plus Plus

Image: Mashable composite. Image: Wikimedia Commons

What it is: C++ is an intermediate-level language with object-oriented programming features, originally designed to enhance the C language. C++ powers major software like Firefox, Winamp and Adobe programs. It’s used to develop systems software, application software, high-performance server and client applications and video games.

Where to learn it: Udemy, Lynda.com, CPlusPlus.com, LearnCpp.com, CProgramming.com.

4. C#

C Sharp

Image: Mashable composite. Image: Wikimedia commons

What it is: Pronounced „C-sharp,“ C# is a multi-paradigm language developed by Microsoft as part of its .NET initiative. Combining principles from C and C++, C# is a general-purpose language used to develop software for Microsoft and Windows platforms.

Where to learn it: Udemy, Lynda.com, Microsoft Virtual Academy, TutorialsPoint.com.

5. Objective-C

Objective-C

Image: Mashable composite. Image: Wikimedia Commons

What it is: Objective-C is a general-purpose, object-oriented programming language used by the Apple operating system. It powers Apple’s OS X and iOS, as well as its APIs, and can be used to create iPhone apps, which has generated a huge demand for this once-outmoded programming language.

Where to learn it: Udemy, Lynda.com, Mac Developer Library, Cocoa Dev Central, Mobile Tuts+.

6. PHP

PHP

Image: Mashable composite. Image: Wikimedia Commons

What it is: PHP (Hypertext Processor) is a free, server-side scripting language designed for dynamic websites and app development. It can be directly embedded into an HTML source document rather than an external file, which has made it a popular programming language for web developers. PHP powers more than 200 million websites, including WordPress, Digg and Facebook.

Where to learn it: Udemy, Codecademy, Lynda.com, Treehouse, Zend Developer Zone, PHP.net.

7. Python

Python

Image: Mashable composite. Image: Wikimedia Commons

What it is: Python is a high-level, server-side scripting language for websites and mobile apps. It’s considered a fairly easy language for beginners due to its readability and compact syntax, meaning developers can use fewer lines of code to express a concept than they would in other languages. It powers the web apps for Instagram, Pinterest and Rdio through its associated web framework, Django, and is used by Google, Yahoo! and NASA.

Where to learn it: Udemy, Codecademy, Lynda.com, LearnPython.org, Python.org.

8. Ruby

Ruby

Image: Mashable composite. Image: Wikimedia Commons

What it is: A dynamic, object-oriented scripting language for developing websites and mobile apps, Ruby was designed to be simple and easy to write. It powers the Ruby on Rails (or Rails) framework, which is used on Scribd, GitHub, Groupon and Shopify. Like Python, Ruby is considered a fairly user-friendly language for beginners.

Where to learn it: Codecademy, Code School, TryRuby.org, RubyMonk.

9. JavaScript

JavaScript

Image: Mashable composite. Image: Wikimedia Commons

What it is: JavaScript is a client and server-side scripting language developed by Netscape that derives much of its syntax from C. It can be used across multiple web browsers and is considered essential for developing interactive or animated web functions. It is also used in game development and writing desktop applications. JavaScript interpreters are embedded in Google’s Chrome extensions, Apple’s Safari extensions, Adobe Acrobat and Reader, and Adobe’s Creative Suite.

Where to learn it: Codecademy, Lynda.com, Code School, Treehouse, Learn-JS.org.

10. SQL

SQL

What it is: Structured Query Language (SQL) is a special-purpose language for managing data in relational database management systems. It is most commonly used for its „Query“ function, which searches informational databases. SQL was standardized by the American National Standards Institute (ANSI) and the International Organization for Standardization (ISO) in the 1980s.

Where to learn it: Lynda.com, SQLCourse.com, TutorialsPoint.com, SQLZoo.net.

Source. http://mashable.com/2014/01/21/learn-programming-languages