Two days. That’s all it took to completely change how we work. In 48 hours of working with Claude by Anthropic, we shipped more real, working projects than we had in weeks of fighting with other AI tools. This is the story of what we built, what blew our minds, and why Claude has earned a permanent seat at the SolarBluSeth workstation. 🚀

⚡ What We Actually Built in 48 Hours

Let’s just get straight to the receipts. Here’s what we knocked out:

• ✅ A full VRM avatar pipeline — 90+ Mixamo FBX characters converted to working VRM files for Animaze, complete with face tracking, hand tracking, and blend shapes
• ✅ 96 individual Python scripts — one per character, auto-generated, each with custom settings for rotation and mesh joining
• ✅ A custom unicorn rig — a DAZ quadruped with no human bones, given a fake humanoid skeleton from scratch so she loads and moves in Animaze
• ✅ JSON data imports into Elementor — structured content pushed directly into WordPress page builder layouts
• ✅ SEO reports and analysis — full site audits with actionable recommendations
• ✅ Blog posts and articles — written, formatted, and ready to publish including the one you’re reading right now
• ✅ A custom startup configuration file — a .md skill file that primes Claude with our project context so every session starts smart instead of from scratch
• ✅ Blender scripting — bone renaming, orientation fixing, blend shape binding, humanoid assignment, all automated
• ✅ VRM file analysis and debugging — binary GLB parsing, JSON inspection, material property investigation

That’s not a weekend project. That’s a full sprint — and we did it in two days. 🔥

⏱️ The Moment That Sold Us: 5 Minutes vs 6 Hours

Here’s the one that really said it all.

We had a task that we’d previously taken to ChatGPT. After over 6 hours of back and forth, regenerating, fixing errors, explaining context over and over again, we gave up and moved on.

We brought the same task to Claude. Done in 5 minutes. Working. First try.

That’s not a small difference. That’s a completely different experience. Claude understood the context, held it across the conversation, reasoned through the problem, and just… solved it. No drama. No endless loops. No “I apologize for the confusion” followed by the exact same wrong answer.

🧠 Why Claude Hits Different

After 48 hours of heavy use, here’s what actually separates Claude from the competition:

It holds context like a pro. Claude remembers what you built three messages ago, what file you’re working on, what went wrong last time. You don’t have to re-explain your entire project every few messages. This alone saves enormous amounts of time on complex multi-step projects.

It reasons, not just retrieves. When something broke in our VRM pipeline, Claude didn’t just Google-dump generic answers. It actually thought through cause and effect — “the orientation check can’t find LeftUpperArm because bones haven’t been renamed yet at that point in the script.” That’s debugging logic, not keyword matching.

It writes real, working code. Not almost-working code. Not code that looks right but fails on line 47. We ran scripts directly from Claude’s output and they worked. When they didn’t, Claude read the error, understood it, and fixed it — not just tried a random variation.

It knows when simple beats clever. Multiple times Claude suggested removing complex logic in favor of a simpler approach. That kind of judgment — knowing when NOT to over-engineer — is rare even in human developers.

It works across everything. Same session: Blender Python scripting, binary file parsing, HTML formatting, blog writing, SEO analysis, JSON structuring. No switching tools. No context loss. One conversation, many skills.

📄 The Game Changer: Custom Startup Files

One of the most powerful things we discovered was building a custom .md skill file — a markdown document that loads at the start of a session and gives Claude instant context about our project.

Instead of spending the first 10 messages re-explaining our folder structure, our Blender version, our VRM addon, our file naming conventions — all of that lives in the skill file. Claude reads it and immediately knows:

• Where our files live (F:\3d\3dmodels\2026unity\)
• What version of Blender we’re running (5.0.1)
• What our bone naming conventions are
• What our output format needs to look like
• What tools and addons we have installed

It’s like giving Claude a project brief before the meeting starts. Every session begins informed instead of blind. For ongoing projects this is absolutely essential — it’s the difference between a new hire who has to be trained every day and a colleague who just knows the system. 💡

🆚 Claude vs ChatGPT: Real Talk

We’ve used both extensively. Here’s the honest comparison from our experience:

• Context retention: Claude holds a long, complex conversation together far better. ChatGPT starts drifting and forgetting after a while.
• Code quality: Claude’s code runs. ChatGPT’s code often needs several rounds of fixing before it actually works.
• Reasoning: Claude explains WHY something is wrong. ChatGPT often just tries a different variation and hopes.
• Honesty: Claude will tell you when something isn’t possible or when a simpler approach is better. ChatGPT sometimes just agrees with whatever you suggest even when it’s wrong.
• Complex projects: Claude thrives on multi-step, multi-file, multi-session projects. This is where the gap is biggest.
• Speed: As demonstrated — 5 minutes vs 6 hours speaks for itself.

🌟 The Bottom Line

AI tools are only as powerful as the work they actually help you ship. In 48 hours with Claude we built a production-ready avatar pipeline, automated 96 character conversions, solved problems that had stumped us for days, and still had time to write about it.

The skill file system, the context awareness, the reasoning quality, the code that actually runs — these aren’t small features. They’re the difference between an AI that assists and an AI that collaborates.

We’re just getting started. The pipeline is running, the avatars are live, and the next project is already queued up. If you’re still on the fence about which AI tool to invest your time in — we hope this answers that question. 💛

Stay curious. Build fearlessly. The tools are better than ever. 🌐✨

— SolarBluSeth | solarblu.net

If you read our last post about crafting virtual selves, you know we were just getting started. Well buckle up — because this time we didn’t just make a few avatars. We built a full automated pipeline that converts 90+ characters into working VRM avatars for Animaze. No errors. No crashes. Just vibes and virtual people. 🎮🔥

🧠 What We Were Trying to Do

Our goal was simple in theory: take a library of 3D characters in FBX format — knights, vampires, zombies, grannies, aliens, and yes, even a unicorn 🦄 — and convert them all into VRM files that work in Animaze with full face tracking, hand tracking, and body movement.

Simple in theory. Absolutely wild in practice.

🔧 The Tech Stack

• Blender 5.0 — our workhorse for 3D processing
• VRM Addon for Blender — handles the VRM0 format export
• Animaze — the real-time avatar software we’re feeding everything into
• Python — the glue that holds the whole pipeline together
• Mixamo FBX files — our source characters (140 of them!)

😤 What Went Wrong (Everything, At First)

The White Model Problem — our first big wall. Characters were exporting fine but showing up completely white in Animaze. Turns out Animaze doesn’t read the standard glTF PBR material block — it reads a totally separate VRM-specific section called materialProperties. The Blender VRM exporter was filling that section with VRM_USE_GLTFSHADER and empty texture references. Animaze sees that and goes… blank. 🤷

The fix? Stop post-processing the materials entirely and let the VRM exporter handle it natively. Sometimes the best fix is removing code, not adding it.

The Backwards Characters Problem — half our avatars were loading into Animaze facing the wrong direction. We spent way too long on fancy detection logic checking arm positions and bone coordinates. The real answer was embarrassingly simple: Mixamo exports characters facing -Z, and we were importing with axis_forward='-Z', so they cancelled out and everyone walked in backwards. One line fix. 😅

The Subprocess Crash Problem — early on we tried running Blender as a subprocess for each character to isolate crashes. This caused more problems than it solved. We scrapped it and went back to a simple try/except loop. Less clever, more reliable.

🏗️ How the Pipeline Works Now

We ended up with a clean, simple architecture. Every character gets their own .py file based on a working template. Each one has two settings at the top:

EXTRA_ROT_Z = 0    # set to 180 if character loads backwards
JOIN_MESHES  = False  # set to True if character has many mesh parts

That’s it. No magic detection. No complex batch logic. Just two knobs per character. A single run_all.py chains all the scripts together and runs them through Blender one by one. Set it going and walk away.

🎯 What We Learned

Animaze reads VRM materialProperties, not glTF PBR. If your character is white, this is why. Don’t post-process — let the VRM addon handle it natively.

Rename bones before checking orientation. We had a bug where orientation detection couldn’t find LeftUpperArm because bones still had their mixamorig: prefix at that point. Order matters.

Simple beats clever every time. We rewrote the orientation detection three times trying to be smart about it. A hardcoded 180-degree flag per character is faster, more reliable, and easier to understand six months from now.

Individual files are better than one mega-script. When one character crashes, the others keep running. When you need to tweak one character, you edit one file. Obvious in hindsight.

Auto-weights beat envelope weights for complex meshes. Learned this the hard way when the unicorn exploded into pieces. 🧩

🌟 The Results

• ✅ 90+ working VRM avatars loading in Animaze
• ✅ Full face tracking — expressions, blinks, mouth movements
• ✅ Hand tracking via Animaze’s Mediapipe open beta
• ✅ Zero import errors in Animaze
• ✅ A fully automated pipeline — drop in a new FBX, run one script, done

🚀 What’s Next

We’ve got 90 avatars ready to go — knights, vampires, zombies, soldiers, grannies, aliens, clowns, pirates. The plan is to start streaming with them, swap characters mid-session, and keep building out the collection.

This project started as “let’s try making an avatar” and turned into building a proper 3D conversion pipeline from scratch. That’s the SolarBluSeth way — start curious, go deep, figure it out. 💛

Stay tuned for videos, streams, and probably more chaotic deep dives into tech rabbit holes. The virtual world is ours. 🌐✨

— SolarBluSeth | solarblu.net