# Flexcompute Engineering > Essays, tutorials, and case studies on AI engineering, computational physics, photonics, and simulation from Flexcompute. This site publishes essays, tutorials, and case studies from Flexcompute engineering. Use the canonical article URLs for citation and the Markdown mirrors for lightweight machine ingestion. ## Feeds - RSS: https://engineering.flexcompute.com/feed.xml - JSON Feed: https://engineering.flexcompute.com/feed.json - Sitemap: https://engineering.flexcompute.com/sitemap-index.xml ## Index Pages - Home: https://engineering.flexcompute.com - Articles: https://engineering.flexcompute.com/articles/ - Authors: https://engineering.flexcompute.com/authors/ - Tags: https://engineering.flexcompute.com/tags/ - Series: https://engineering.flexcompute.com/series/ ## Articles - Title: Learning Auto-Routing by Building: From Brute Force to an Auto-Design Agent Canonical URL: https://engineering.flexcompute.com/articles/electrical-routing-agents/ Markdown URL: https://engineering.flexcompute.com/articles/electrical-routing-agents.md Published: 2026-04-20 Updated: 2026-04-20 Kind: Essay Authors: Prash Kharel Topics: AI Engineering, AI Agents, Photonics Summary: How I learned auto-routing for photonic chips — a failed brute-force attempt, AI as a learning partner, interactive HTML arenas, a PhotonForge router, and an agent that iterates 27 designs in under three minutes. - Title: Predicting Peak Memory for an Electromagnetic Mode Solver Canonical URL: https://engineering.flexcompute.com/articles/mode-solver-memory-calibration/ Markdown URL: https://engineering.flexcompute.com/articles/mode-solver-memory-calibration.md Published: 2026-04-15 Updated: 2026-04-15 Kind: Case Study Authors: Momchil Minkov Topics: Photonics, Tidy3D, Verification Summary: How we replaced a heuristic memory estimate with a calibrated model for Tidy3D mode solver workloads, eliminating under-predictions across the calibration set. - Title: Can AI Agents Autonomously Design Components on Photonic Chips? Canonical URL: https://engineering.flexcompute.com/articles/autoresearch-photonic-design/ Markdown URL: https://engineering.flexcompute.com/articles/autoresearch-photonic-design.md Published: 2026-04-13 Updated: 2026-04-13 Kind: Essay Authors: Tyler Hughes Topics: Photonics, Inverse Design, Optimization, AI Agents Summary: We gave AI agents a photonic simulator, a DRC engine, and four design challenges. They autonomously designed waveguide bends, crossings, splitters, and demultiplexers — some reaching near-perfect performance. - Title: Designing a Photonic Chip Component with ~45 Lines of Python Canonical URL: https://engineering.flexcompute.com/articles/photonic-inverse-design-45-lines/ Markdown URL: https://engineering.flexcompute.com/articles/photonic-inverse-design-45-lines.md Published: 2026-03-05 Updated: 2026-03-05 Kind: Tutorial Authors: Tyler Hughes Topics: Photonics, Inverse Design, Optimization, Tidy3D Summary: A compact introduction to photonic inverse design with Tidy3D, using a pre-built simulation and a ~45-line optimization loop. - Title: "What Should We Work On Next?" Canonical URL: https://engineering.flexcompute.com/articles/what-should-we-work-on-next/ Markdown URL: https://engineering.flexcompute.com/articles/what-should-we-work-on-next.md Published: 2026-02-26 Updated: 2026-02-26 Kind: Case Study Series: AI Engineering Authors: Yannick Augenstein, Frederik Schubert Topics: AI Engineering, Autodiff, Verification Summary: The story of building an 80,000-line autodiff library almost entirely through AI agents — and the verification infrastructure that made it possible. - Title: The Agent Control Loop — Engineering for Tolerance Canonical URL: https://engineering.flexcompute.com/articles/agent-control-loop/ Markdown URL: https://engineering.flexcompute.com/articles/agent-control-loop.md Published: 2026-01-19 Updated: 2026-01-19 Kind: Essay Series: AI Engineering Authors: Frederik Schubert, Yannick Augenstein Topics: AI Engineering, AI Agents, Verification Summary: Why agent reliability isn't magic model behavior — it's an environment where correctness is continuously verified. A framework for deciding when and how to delegate to AI agents.