James Briggs on Building AI That Works

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James Briggs builds AI systems that work in production. As founder of Aurelio AI and formerly at Pinecone, he’s spent years shipping AI applications for clients ranging from stealth startups to Fortune 500 companies.

His core belief: AI systems need control and predictability. Not just demos that impress in a sandbox, but software that holds up when released into the wild.

Semantic Router: Fast Decision Making for AI

Briggs created Semantic Router, an open-source library with 3.2k+ GitHub stars. The idea is simple but powerful: instead of waiting for slow LLM generations to decide which tool to use or whether a request is safe, use semantic vector space to route requests instantly.

from semantic_router import Route
from semantic_router.layer import RouteLayer

# Define routes based on semantic meaning
chitchat = Route(
    name="chitchat",
    utterances=["how's the weather?", "what's up?", "hello"]
)
technical = Route(
    name="technical",
    utterances=["how do I fix this bug?", "what's the best architecture?"]
)

# Router uses embeddings to match intent
router = RouteLayer(routes=[chitchat, technical])

The router decides in milliseconds what would take an LLM seconds to figure out. For agent systems handling thousands of requests, this adds up fast.

Educational Philosophy: Show the Code

Briggs runs a YouTube channel focused on practical AI engineering. No hand-waving about capabilities—he walks through implementation details.

He’s also written several technical ebooks for Pinecone:

The pattern: pick a topic, go deep, make it accessible.

On Building Real AI Products

From client work across industries, Briggs has refined his approach:

Control matters more than capability. A system that does 80% of what you want reliably beats one that does 100% unpredictably.

Semantic routing reduces LLM calls. Not everything needs a full generation. Pattern matching via embeddings handles routine decisions faster and cheaper.

Test in production conditions. AI that works in notebooks often fails with real user input. Build evaluation into the workflow early.

Current Focus

Aurelio AI (with offices in San Francisco, Dubai, and London) focuses on:

The learning center at aurelio.ai/learn publishes tutorials on these topics regularly.

Key Takeaway

Briggs represents a practical school of AI engineering. Less hype about what’s theoretically possible, more focus on what you can ship today. Semantic Router embodies this: a targeted solution to a real bottleneck in agent systems.

His work shows that building effective AI tools doesn’t require breakthrough research—it requires understanding where current systems fall short and engineering around those gaps.

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