How Expectations from Software Developers Have Changed—And What Hasn’t

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In the 1980s and 1990s, writing software was the realm of a relatively small group of people—mostly computer science students and professionals. If you were working on a program that stretched beyond a few dozen lines, it often meant you had spent weeks poring over documentation, sketching flowcharts, and manually debugging every little detail.

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Fast forward to 2025, and we live in a completely different coding environment. A 100+ line Python script—like the tree.py example shared on Reddit—might still be considered “small” by modern standards. But what’s changed dramatically is how such code comes to life.

Then vs. Now

Back then:

• Every single line was typed by hand.
• There was no autocomplete, no Stack Overflow, and certainly no AI assistant.
• Debugging often meant hours of tracing logic with pencil and paper.
• A working program of this size was a clear marker of skill and persistence.

Now:

• We have rich standard libraries, frameworks, and open-source projects that can save hundreds of lines of code.
• AI can scaffold programs, suggest fixes, and even write initial versions of entire modules.
• Collaboration tools, forums, and real-time chat help solve problems in minutes, not days.
• Many more people have the opportunity to attempt projects that were once out of reach.

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The Accessibility Shift

AI and online resources have democratized programming. You don’t need to spend years learning before you can build something functional—you can start experimenting on day one. Even without writing code from scratch, you can take an existing script, walk through it line by line, and learn what’s happening.

This accessibility is a double-edged sword:

• Pro: More people can participate, experiment, and innovate.
• Con: Without deliberate practice, it’s easy to rely too much on “copy-paste” solutions without deeply understanding them.

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What Hasn’t Changed

No matter the tools, the core challenge of programming is still the same:

• Understanding problems deeply.
• Designing logical, maintainable solutions.
• Adapting code to fit real-world constraints.

AI can hand you a finished program, but only you can ensure it’s correct, efficient, and fit for purpose.

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Dissecting the tree.py Example

The Reddit post features a Python program for representing and printing a tree structure. While just over 100 lines, it demonstrates several timeless programming skills:

1. Object-Oriented Design

• A Node class stores values and references to children.
• Special methods like __str__ control how the tree is displayed.

2. Recursion

• Functions call themselves to traverse the tree tier by tier.
• This mirrors “classic” algorithm design from decades ago.

3. Data Structure Manipulation

• Lists and dictionaries are used to group nodes by tiers.
• Index math is used to determine where each node appears visually.

4. String Formatting & Visualization

• The program doesn’t just store data—it formats it into a readable diagram.
• This involves spacing, alignment, and handling variable-width node values.

Why it Feels ‘Old-School’:

• No third-party libraries—only Python’s built-in features.
• Logic-heavy: The code’s complexity is in thinking through how to arrange and print nodes.
• Easy to imagine this being ported to C, Pascal, or BASIC in the ’80s.

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Visual Walkthrough: From Code to Diagram

Here’s an example of what tree.py might output for a small binary tree:

      A
     / \
    B   C
   / \    \
  D   E    F

Step-by-step mapping of code to output:

1. Creating Nodes root = Node("A") root.add_child(Node("B")) root.add_child(Node("C")) → This builds the root and its immediate children.
2. Expanding the Tree root.children[0].add_child(Node("D")) root.children[0].add_child(Node("E")) root.children[1].add_child(Node("F")) → This fills in lower levels, just like expanding branches on a real tree.
3. The __str__ Method
   • Groups nodes by “tier” (level of depth).
   • Calculates spacing so that parent and child nodes align visually.
   • Joins lines into a complete string with '\n'.join(...).
4. Printing the Tree print(root) → Runs the formatting logic and produces the structured diagram.

Key takeaway:
Even though the code is 100+ lines, the visual result feels simple. The “hidden” complexity lies in spacing, alignment, and traversal logic—things that computers now help us with, but still require careful thought if written by hand.

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Final Thought

Yes—expectations have changed. We’re no longer in an era where producing a 100-line program proves you’re a top-tier developer. But the heart of programming—clarity, creativity, and problem-solving—remains timeless.

Today, the playing field is bigger, the tools are sharper, and the entry barriers are lower. The best programmers are those who use these advantages not as a crutch, but as a launchpad to go further than ever before.