The AI Engineering Report Q3 2026 is now available! Read the latest research:
The Speed Trap
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AI Engineering Report Q3 2026: The Speed Trap is now available

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AI Engineering Report 2026: The Speed Trap is now available

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Leah McGuire

Leah McGuire

Leah McGuire has spent the last two decades working on information representation, processing, and modeling. She started her career as a computational neuroscientist studying sensory integration and then transitioned into data science and engineering. Leah worked on developing AutoML for Salesforce Einstein and contributed to open-sourcing some of the foundational pieces of the Einstein modeling products. Throughout her career, she has focused on making it easier to learn from datasets that are expensive to generate and collect. This focus has influenced her work across many fields, including professional networking, sales and service, biotech, and engineering observability. At Faros, she develops the platform’s native AI capabilities.

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Latest posts by Leah McGuire

Research
18
min
11/8/24

Mastering Domain-Specific Language Output: Getting an LLM to Perform Reliably without Fine-tuning

See how real-world user insights drove the latest evolution of Faros AI’s Chat-Based Query Helper—now delivering responses 5x more accurate and impactful than leading models.
AI
Data Engineering
18
MIN READ
AI Industry
15
min
2/12/24

Lessons from Implementing LLMs Responsibly at Faros AI

How we used GenAI to make querying unfamiliar data easier without letting the LLM take the wheel
A banner image of Leah McGuire, machine learning engineer at Faros AI, with the article title "Lessons from implementing LLMs responsibly at Faros AI."
AI
Data Engineering
15
MIN READ
Red and dark purple abstract logo with geometric shapes representing Faros.
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