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Notes from the Curlscape team on building production AI: agents, LLMs, evaluation, and applying AI to engineering and industrial problems.
Putting Surrogate Models to the Test: GeoTransolver and AB-UPT on PLAID

October 26, 2026

Putting Surrogate Models to the Test: GeoTransolver and AB-UPT on PLAID

We tested GeoTransolver and AB-UPT on five PLAID engineering benchmarks in Curlscape Sift and compared them with six published surrogate models.

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A Comprehensive Review of Different Surrogate Architectures

October 9, 2026

A Comprehensive Review of Different Surrogate Architectures

Which AI surrogate model fits best for your design cycle and goal? Compare nine architectures, their computational costs and trade-offs, and where each works best in engineering.

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Evaluating AI agents for Engineering Workflows

September 29, 2026

Evaluating AI agents for Engineering Workflows

What does it take to trust an AI agent with engineering simulation? We evaluate an agentic-workflow using a public benchmark and walk through the evaluation process, results, and what we learned.

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Neural Operators for Engineering Simulation

September 18, 2026

Neural Operators for Engineering Simulation

Learn how neural operators learn mappings between physical fields, exchange information across spatial domains and scale to large engineering meshes with changing geometries and discretizations.

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Overcoming Automation Bottlenecks with Agentic AI

September 7, 2026

Overcoming Automation Bottlenecks with Agentic AI

Explore how agentic AI extends conventional engineering workflows, improving automation and adaptability while introducing new trade-offs in cost, control, and verification.

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Why surrogate models fail when the geometry changes

August 21, 2026

Why surrogate models fail when the geometry changes

The node count of the training mesh becomes a dimension of a learned weight matrix. Why conventional CFD surrogate models break when the geometry changes.

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Surrogate models: where millisecond predictions can be trusted

August 4, 2026

Surrogate models: where millisecond predictions can be trusted

A surrogate trained on a few hundred solver runs predicts your quantity of interest in milliseconds. It is reliable inside the envelope you sampled, and not outside it.

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Automation without verification just ships wrong answers faster

July 28, 2026

Automation without verification just ships wrong answers faster

A sign-convention error flipped a force-and-torque result in an automated simulation study. A verification agent caught it before the report shipped.

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Mistral API Pricing 2026: The Overlooked Budget Powerhouse

July 21, 2026

Mistral API Pricing 2026: The Overlooked Budget Powerhouse

July 2026 Mistral API pricing for every model — text, reasoning, code, vision, voice, and OCR — up to ~90% cheaper than OpenAI and Anthropic. See the breakdown.

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Google Gemini API Pricing Guide 2026: Flash, Pro, and Vertex AI

July 13, 2026

Google Gemini API Pricing Guide 2026: Flash, Pro, and Vertex AI

Current Google Gemini API pricing for 2026: Gemini 3 generation (3.1 Pro, 3.5 Flash, 3.1 Flash-Lite), what changed since 2.5, image generation with Nano Banana, and how Vertex AI costs compare.

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Anthropic Claude API Pricing Guide 2026: Opus, Sonnet, and Haiku Compared

March 11, 2026

Anthropic Claude API Pricing Guide 2026: Opus, Sonnet, and Haiku Compared

Complete Anthropic Claude API pricing for March 2026. Compare Opus, Sonnet 4.6, and Haiku 4.5 with batch discounts, prompt caching savings, rate limits, and real-world cost breakdowns.

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Fine-tuning open models in the real world: Unsloth, Axolotl, and the case for Docker

March 3, 2026

Fine-tuning open models in the real world: Unsloth, Axolotl, and the case for Docker

Production lessons from fine-tuning open models and why Curlscape uses Docker to ensure GPU training environments are reproducible and reliable.

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