I Pushed GPT-6 Astra’s Computer Use to Its Limits

TL;DR: The creator tests GPT-6 Astra's new computer-use capabilities by delegating real-world tasks across 10 different applications, from creative software to simulation tools, evaluating its ability to operate interfaces like a human. ## Testing Astra's Computer Operation Across 10 Apps Since the release of GPT-6 Astra, its computer operation functionality represents a major leap. Unlike previous, slow and unreliable AI tools, Astra can be trusted with real tasks in actual software. The creator tested this across 10 applications, including video editing, image creation, 3D modeling, LEGO design, and even playing instruments in GarageBand. All tests were conducted using the Codex feature within the ChatGPT desktop app, showcasing its ability to click, type, and drag like a human. ## Google Earth Studio: Complex Animation from a Prompt The first test used Google Earth Studio to create a complex flyover animation of Utah. The prompt detailed a path from the State Capitol, over Salt Lake City, through to Arches National Park and through the Delicate Arch. The first attempt took 11 minutes and 49 seconds, producing a solid but slow result with some directional issues. After three follow-up iterations over approximately 23 additional minutes, the final animation was deemed "basically perfect." The takeaway is that with a more detailed initial prompt, Astra could achieve near-perfect results on the first try, saving time for only minor manual tweaks later. This workflow—sending a prompt, working on other things, and adjusting the result—optimizes Astra's strength. ## Canva: Creative Illustration Generation A purely creative test in Canva asked Astra to draw an original, complex idea without copying existing works. The process involved iterative prompting to increase complexity: - First attempt (3 min 57 sec): "The Wandering Greenhouse" - Second attempt (7 min 14 sec): "The Clockwork Nightwatch" - Third attempt (20 min 47 sec): "The Colorful Caravan" The final result, with more colors and small details, was impressive. Astra was also asked to turn the drawing into a photorealistic image, which it did successfully. ## Adobe Photoshop: Automated Thumbnail Creation Astra was tasked with creating a video thumbnail from scratch in Photoshop, using provided photos. It performed background removal, changed the creator's shirt color, generated separate elements, and added text and effects, all with creative freedom. - First attempt (25 min): Produced a good start with all necessary layers. - Follow-up modifications (14 min + 20 min): Refined the design. The total time was about an hour, which could be slower than doing it manually. However, the key advantage was delegation—the creator could walk away and perform follow-ups remotely from a phone while Astra worked in the background. The final thumbnail is used for the video. ## Adobe Premiere: Adding Text and Animation For video editing in Premiere, Astra was asked to add title text with animation to an existing clip and then add pop-and-wobble animations to images on the timeline. - First attempt (12 min): Completed the text animation. - Second request (13 min): Included searching for and adding appropriate sound effects. The result was good, effectively handling the tedious work of manual keyframing and sound synchronization. ## Adobe Illustrator: A Challenging Vector Recreation A complex challenge in Illustrator was to recreate a specific graphic using clean vector shapes and paths, not the "Image Trace" feature. A crucial constraint was applied: the prompt explicitly forbade using code, scripts, APIs, or MCPs to force Astra to use the computer-use interface instead of Illustrator's Python API. - Computer-Use Path: Two attempts (40 min + 52 min) yielded poor results. - Python API Path (no constraint): A first attempt (20 min) was significantly better. Two more follow-ups (10 min + 15 min) produced a superior result, though still not a perfect match to the original. For complex vector projects, Astra's computer-use method may not be ideal, whereas allowing it to use the most efficient method (Python API) works better. ## LEGO, Rocketry, and Rube Goldberg Simulations Astra also tackled specialized simulation and design software it had likely never used before: - **BrickLink Studio**: Designed a 257-piece LEGO model of the Delicate Arch, organized into 27 assembly steps. - **Open Rocket**: Designed a stable rocket capable of reaching 1,000 meters and safe recovery, running and iterating on simulations until it passed both constraints. - **Algadoo**: Built interactive Rube Goldberg-style machines, first a simpler one with 5 interactions, then a more complex version. ## Blender: 3D Modeling and Iterative Improvement The Blender test, using computer-use mode, aimed to recreate the Delicate Arch in 3D. The process highlighted Astra's iterative learning: - First attempt (15 min): Poor result. - Subsequent iterations involved Astra opening a browser to compare with real photos, rebuilding the model, accessing Blender's node system for textures, and refining the surrounding landscape. - After about 50 minutes, a much-improved result was achieved. A final push for perfection resulted in extensive additional work. The creator noted that Astra can visually critique its own output and loop iterations, but it's often better to limit this to prevent excessive token consumption. The Arch's organic, asymmetric shape made this a particularly challenging test. ## Conclusion: A Practical Tool for Delegation The tests demonstrate that Astra's computer-use function is reliable for delegating real tasks, especially for automating tedious work in familiar software or tackling unfamiliar applications. Its strength lies in handling background work, freeing the user for other activities. For optimal use, detailed initial prompts and a "prompt-then-tweak" workflow are recommended. Source: [https://www.youtube.com/watch?v=2hTtpFVZE5A](https://www.youtube.com/watch?v=2hTtpFVZE5A)