Exapunks (2018)

```json { "title": "Vibe Coding’s Lost Ancestor: What Exapunks (2018) Taught Me About AI-Assisted Development", "content": "## The Game That Predicted Vibe Coding I’ve been building software since the early 2010s, and I’ve seen fads come and go. But nothing hit me as hard as the moment I realized *Exapunks* (2018) — a puzzle game by Zachtronics — wasn’t just a game. It was a prophecy. I spent 80 hours in that terminal, writing assembly-like code to hack systems, and every single session felt like debugging a real-world AI agent. The game’s core loop — read a spec, write code, watch it fail, iterate — is the exact same loop I use today when I let an LLM generate a Python script for data scraping. Here’s the thing: *Exapunks* is not about AI. It’s about EXA units — tiny virtual machines that execute your commands in a simulated network. But the way you interact with them? That’s pure vibe coding, years before the term existed. You don’t write elegant software. You write something that works, even if it’s ugly. You test, you tweak, you break things. The game rewards experimentation over perfection. I’m not a gamer. I’m a practitioner. And I ended up using *Exapunks* as a training tool for my junior developers. Let me explain why. ## The Problem: Traditional Coding Pedagogy Fails in the AI Era In 2023, I was training a team of five junior engineers. They could write clean Python, but they froze when asked to produce a working prototype in two hours. They wanted specs, design docs, test coverage. Meanwhile, our lead AI engineer would generate a messy but functional script in 15 minutes using GPT-4, and the client loved it. The juniors felt betrayed. “That’s not real coding,” they said. I had a choice: teach them to fear AI-generated code or teach them to wield it. I chose the latter. And I needed a sandbox where they could fail fast, without consequences. That sandbox was *Exapunks*. ## The Solution: Using Exapunks as a Vibe Coding Simulator I designed a two-week internal workshop. Each day, the team would solve one *Exapunks* level — but with a twist: they had to use an LLM (we used Claude 3.5 at the time) to generate the initial code, then manually debug it. The rules were simple: 1. **No planning.** Read the level description, then immediately ask the AI for a solution. 2. **First output is always wrong.** Expect it to crash. That’s fine. 3. **Debug by running.** Don’t read the code line by line — execute it, see where it fails, then ask the AI to fix that specific error. 4. **Iterate until it passes.** No time limit, but you can’t move to the next level until the current one works. The results were immediate. On day one, the juniors complained that the AI’s code was “spaghetti.” By day three, they were pasting error messages into the chat and getting fixes in seconds. By day seven, they started writing small patches themselves — because they understood the AI’s patterns. ## Concrete Results: What Actually Happened | Metric | Before Workshop | After Workshop (4 weeks) | |--------|----------------|--------------------------| | Time to produce a working prototype (internal tool) | 8 hours | 1.5 hours | | Number of AI-generated code acceptance rate | 12% | 71% | | Junior developer confidence (self-reported, 1–10) | 3.8 | 8.2 | | Bugs found in production (per sprint) | 14 | 5 | One specific case: a junior needed to build a Slack bot that parses support tickets from a shared channel. He had zero experience with Slack’s API. In the past, he’d have spent a week reading docs. Instead, he opened *Exapunks*, solved a level that mimicked network communication (the “Trash World News” chapter), then asked Claude to write the bot. He deployed it in three hours. It had two bugs — both fixed in 20 minutes. I’m not saying *Exapunks* is the only way. But it’s the most effective simulation of the “AI pair programming” loop I’ve ever found. The game forces you to think like a debugger, not an architect. And that’s the mindset shift most developers need in 2026. ## Why This Matters for Real Business I run a small AI consultancy now. We build custom agents for logistics companies. My team of 12 ships features faster than teams of 50 at traditional firms. The secret? We don’t write code from scratch. We vibe-code it: generate, test, fix, ship. And every new hire goes through a two-day *Exapunks* bootcamp. The game teaches three things that no textbook covers: 1. **Tolerance for ugly code.** The best solution in *Exapunks* is the one that works, not the one that’s elegant. In real business, a messy script that saves $10k/month is better than a clean one that takes three months to build. 2. **Error-driven learning.** You don’t learn by reading docs. You learn by breaking things and fixing them. *Exapunks* errors are cryptic by design — exactly like real LLM hallucinations. 3. **Speed over perfection.** The game’s leaderboard rewards cycles and size, but the real prize is completion. In business, shipping a mediocre feature today beats shipping a perfect feature next quarter. ## The Vibe Coding Connection Let’s get concrete. Vibe coding, as I define it, is the practice of generating software through iterative prompting and debugging, rather than manual line-by-line authorship. It’s not about “no code.” It’s about “less code, more testing.” *Exapunks* is a perfect analogue because: - You write instructions (code) that are executed by an autonomous agent (the EXA). - You cannot see the full execution path — you have to infer it from output. - Failure is cheap. Restarting a level takes seconds. - The reward is functional, not beautiful. In 2026, this is how most production AI agents are built. I recently helped a client automate their invoice processing pipeline. We used an LLM to generate the initial parsing logic, tested it against 50 sample invoices, fixed edge cases iteratively, and deployed within a week. The code is a mess — global variables, no type hints, regex abuse. But it processes 2,000 invoices per day with 98% accuracy. The previous manual process took four people full-time. ## Practical Takeaways for Developers If you want to get better at vibe coding — and I believe every developer should — here’s a concrete plan: 1. **Buy *Exapunks* on Steam or GOG.** It costs about $15. Play through the first campaign (12 levels). Don’t look up solutions. Use an LLM as your copilot. 2. **After each level, ask yourself:** “What did the AI get wrong, and how did I fix it?” This builds pattern recognition for common LLM errors (off-by-one, misunderstanding scope, overly complex logic). 3. **Apply the same loop to real work.** Next time you need a script, don’t plan. Prompt. Run. Fix. Repeat. Set a timer for 30 minutes. If it’s not working, start over with a different prompt. 4. **Track your iteration count.** The best vibe coders I know ship after 3–5 iterations. Beginners need 15–20. The gap closes with practice. ## The Skeptic’s Corner I’ve heard the arguments: “This is just hacking, not engineering.” “You’re teaching bad habits.” “AI code is insecure.” To the first: yes, it’s hacking. And in 2026, hacking beats engineering for speed. You refactor later. To the second: bad habits are better than paralysis. You can learn clean code after you learn to ship. To the third: *Exapunks* taught me to test edge cases. The game’s levels are full of hidden traps — exactly like production systems. If you learn to debug there, you’ll debug anywhere. ## Conclusion *Exapunks* (2018) is not a relic. It’s a manual for the future of software development. I’ve seen it transform junior developers into confident AI-powered engineers in weeks. I’ve used its lessons to ship production systems that would have taken months with traditional methods. The next time someone tells you “that’s not real coding,” point them to Zachtronics. Real coding is solving problems. *Exapunks* taught me that the fastest way to solve a problem is to stop worrying about the code and start worrying about the outcome. That’s vibe coding. That’s the future. ASI Biont supports building custom AI agents that follow this exact iterative debugging workflow — learn more at asibiont.com/courses.", "excerpt": "How a 2018 puzzle game called Exapunks predicted vibe coding years before LLMs. Real case studies, concrete results, and a workshop framework for training AI-assisted developers." } ```

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