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Reconstructed Slides: Make your LLM app a Domain Expert: How to Build an Expert System — Christopher Lovejoy, Anterior

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Make your LLM app a Domain Expert: How to Build an Expert System — Christopher Lovejoy, Anterior

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This deck is reconstructed from the existing video frame captures by detecting likely slide regions with OpenCV, cropping/upscaling those regions, deduplicating similar crops, and OCRing the cropped slide images locally. It is a cleaner companion to the full-stage frame deck.

Reconstructed Slides

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Own your vertical: A playbook for building a domain-native LLM application

Dr Christopher Lovejoy, MD

Head of Clinical AI

2025-06-04

Anterior

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Anterior

Were a New York-based, clinician-led

AIE reasoning tools andsolutions to accelerate andautomatehealthcare company thatprovides clinical

administration

BACKEDBY NEA SEQUOIA

andFOUNDERSOF

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Google ALUMRECE mMeta

Microsoft amazon MeKnecy &Company

IMPERIAL NHS

aws

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OUR BET FOR VERTICAL AI APPLICATIONS: system for incorporating domain insights > the sophistication of your models and pipelines

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Why is it hard to successfully apply LLMs to specialized industries?

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An example clinical case processed by Florence

AIE Doctor recommends a knee arthroscopy Presents with right knee pain 78-year-old female

Q: Is there documentation of unsu

conservative therapy for at least 6

Microsoft

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KLAS CASE STUDY

We achieved a baseline performance of 95% for approving care...

95.73%

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KLAS CASE STUDY

We achieved a baseline performance of 95% for approving care...

then iterated with a specific customer to >99% within 8 weeks

95.73%

99.24%

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AIE maintain a failure mode ontology (2) Empower domain experts to define citraetion Photo ortastion Tae

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Microsoft

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(3) Measure metrics and failure modes together

AIE on production data to unlocktargeted insights

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AIE

MEASURE Review AI outouts AralyTe perfornarce to prioritise work Specify failure mode' to fix and perforrance threshold Make changes

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Failure mode datasets enable targeted product iteration

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Empower your domain experts to make

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Takeaways

To build domain-native LLM applications you need to solve the last mile problem.

Using the best models isn't enough - you should build an adaptive domain intelligence engine.

Domain experts power this system by reviewing AI outputs to generate performance metrics, failure modes and suggested improvements.

This takes production data and uses it to give your LLM product a nuanced understanding of customer workflows.

The result is a self-improving, data-driven process that can be managed by a domain expert PM.

Hidden Non-Slide Evidence

Classification audit: raw/sources/slide-ai-classification/reconstructed/MRM7oA3JsFs/audit.json