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tom smith

@Tom Smith

Tom Smithverified

Helping Developers, Engineers & Architects Simplify Tech | AI Content Strategist...
Raleigh, NC insightsfromanalytics.com Joined May 2025
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About

LLM Training & Evaluation Specialist with hands-on experience building major AI models. As one of the original six members of Google's Bard training team (now Gemini) and current M... Show more

Top Skills

LLM Training & Evaluation • AI Model Optimization • RLHF (Reinforcement Learning from Human Feedback) • Prompt Engineering • AI Quality Assurance • Content Strategy & Creation

Experience

Lead Content Strategist

Cognizant Technology Services
Sep 2021 - Present

♦ Senior AI Implementation Consultant: Available for additional strategic AI consulting projects outside Cognizant scope
♦ Senior member of the International Digital Content Team
♦ Content strategy for Ford Motor Company IT Learning & Development Center of Excellence
♦ UX and conversational design for Kaiser Permanente Digital Technologies; authored over 200 conversational chat flows across member services, clinical, and pharmacy lines of business
♦ Content strategy for Kaiser Permanente Digital Information Technology for the Azure Platform
♦ Provide communications training and QA to offshore YouTube Support team members; helped drive CSAT from 75 to 100%
♦ Provide communications training and QA to the Google GTech team
♦ Technical writer for Google's Privacy, Security, and Safety Governance Group
♦ Senior content strategist and prompt engineer on the Google Bard (now Gemini) "seed" team: provided UX and conversation design, built documentation and assessments while training incoming cohorts of content reviewers and writers for LLM
♦ Managed communications for the Google Retail Training program
♦ Lead content strategy for Gilead Pharmaceutical as they moved on-premises intranet to the cloud
♦ Lead Content Team Innovation Pod, created AI Prompt Engineering Training Program and the initial AI Prompt Library for Content Creation
♦ Authored e-book, "From Pixels to Prose: A Guide to Creating AI-Enabled Content"
♦ Edited e-book, "More Than Just Words: Understanding and Addressing Microaggression for Workplace Wellness"
♦ Research, analyze, and test generative AI solutions for the firm's proof of concept

Education

Duke University, Fuqua School of Business

MBA, Business and Marketing
1979 - 1981

Currently Exploring

* RLHF optimization techniques for production LLM applications
* Model evaluation frameworks for enterprise AI deployments
* Prompt engineering patterns that actually scale in production
* Agentic AI architectures for complex development workflows

Achievements

* Original Google Bard/Gemini seed team member (1 of 6 trainers)
* Scaled LLM training operations from 6 to 72 team members
* Evaluated Meta AI Business Assistant systems
* Improved AI output quality by 45% through systematic prompt engineering
* Created training frameworks and evaluation rubrics adopted across Fortune 500 companies
* Written 2,500+ articles on enterprise AI and developer tools

Fun Fact

When I'm not evaluating LLM outputs or iterating context engineering strategies, I'm working out at the gym and eating at Chipotle. Both activities help me think through complex model optimization problems.

Random Dev Quote

Understanding how to evaluate an LLM is more valuable than knowing how to build one. Most developers need optimization skills, not ML PhDs.

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Contributions
Joined: 1 year (since May 5, 2025)
Full Name: Tom Smith
Headline: Helping Developers, Engineers & Architects Simplify Tech | AI Content Strategist | Trained Google Bard → Gemini
About: LLM Training & Evaluation Specialist with hands-on experience building major AI models. As one of the original six members of Google's Bard training team (now Gemini) and current Meta AI Business Assistant evaluator, I understand how these models work from the inside out—and how developers can optimize them fI write about technology solutions that make life simpler and easier for developers, engineers, and architects. I use AI extensively in that work — not as the subject, but as the tool that helps me research faster, verify accuracy, and get to the point.

That AI fluency comes from direct experience: I was one of the original six members of Google's Bard training team (now Gemini) and currently evaluate Meta's AI Business Assistant. I understand how these models work from the inside, which shapes how I write about them for a technical audience.

I specialize in LLM evaluation, prompt engineering, and RLHF methodologies, and I write about real-world implementation challenges — not theoretical possibilities. I attend major tech conferences to stay close to what developers actually face when deploying AI in production.
Location: Raleigh, NC
Website: www.insightsfromanalytics.com
Languges & Tools:
Currently Exploring: * RLHF optimization techniques for production LLM applications
* Model evaluation frameworks for enterprise AI deployments
* Prompt engineering patterns that actually scale in production
* Agentic AI architectures for complex development workflows
Achievements: * Original Google Bard/Gemini seed team member (1 of 6 trainers)
* Scaled LLM training operations from 6 to 72 team members
* Evaluated Meta AI Business Assistant systems
* Improved AI output quality by 45% through systematic prompt engineering
* Created training frameworks and evaluation rubrics adopted across Fortune 500 companies
* Written 2,500+ articles on enterprise AI and developer tools
Fun Fact: When I'm not evaluating LLM outputs or iterating context engineering strategies, I'm working out at the gym and eating at Chipotle. Both activities help me think through complex model optimization problems.
Random Dev Quote: Understanding how to evaluate an LLM is more valuable than knowing how to build one. Most developers need optimization skills, not ML PhDs.
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