- Astrophysicist Chi-kwan Chan employs AI tool Codex to simulate black holes, advancing research on extreme physics and Einstein’s theory of relativity through innovative programming support.
Our Testing Process
How we create first-hand review signals.
- Run a real workflow end-to-end (plan → execute → verify) instead of single-shot prompts.
- Check reliability across multiple runs and document where it breaks.
- Validate pricing and feature claims, then update the page when changes ship.
- Publish at least one unique decision insight learned during testing.
What We Found
Real-world observations from testing.
- Decision shortcut: choose tools by workflow fit first (coding vs automation vs multi-agent), then optimize for autonomy under verification.
- Practical insight: the fastest teams pair an agent with a lightweight checklist (tests, diffs, and approvals) to prevent rework.
- Update habit: treat pricing and feature lists as versioned data, not one-time copy.
Newsletter
Weekly tactics, tool drops, and agent workflows. No spam.
Simulating black holes has long been one of the most formidable challenges in astrophysics. These cosmic phenomena challenge our understanding of physics due to their extreme gravity and the complex relativistic effects near their event horizons. Accurate simulations are crucial—they allow scientists to visualize, test, and validate theoretical models that probe the depths of gravity, spacetime, and quantum effects. However, building these simulations traditionally demands intricate coding knowledge, extensive data handling, and the ability to solve sophisticated equations representing general relativity.