---
title: "Adam King (@adamatflex) | Hashnode"
description: "BizOps at FlexAI. Read the latest articles by Adam King on Hashnode."
url: "https://hashnode.com/@adamatflex"
---

@adamatflex

# Adam King

@adamatflex · Austin, TX · Joined March 2026

BizOps at FlexAI

### [Running AI Workloads Across NVIDIA, AMD, and Multiple Clouds Without Refactoring](https://flexai.hashnode.dev/ai-workloads-nvidia-amd-multi-cloud-without-refactoring?utm_source=hashnode&utm_medium=feed)

A technical look at hardware-agnostic AI infrastructure — running training on NVIDIA H100s and inference on AMD MI300X across multiple clouds.

6 min read · [flexai.hashnode.dev](https://flexai.hashnode.dev/ai-workloads-nvidia-amd-multi-cloud-without-refactoring?utm_source=hashnode&utm_medium=feed)

[Apr 30](https://hashnode.com/posts/ai-workloads-nvidia-amd-multi-cloud-without-refactoring/69f36e7e980b88463f683a56)

### [Fine-Tuning a 32B Legal LLM That Outperformed a Frontier Model at 4× Lower Serving Cost](https://flexai.hashnode.dev/fine-tuning-32b-legal-llm-outperformed-frontier-model-lower-cost?utm_source=hashnode&utm_medium=feed)

LegML fine-tuned a 32B legal LLM using GRPO and supervised fine-tuning that beat a frontier model on legal benchmarks.

6 min read · [flexai.hashnode.dev](https://flexai.hashnode.dev/fine-tuning-32b-legal-llm-outperformed-frontier-model-lower-cost?utm_source=hashnode&utm_medium=feed)

[Apr 21](https://hashnode.com/posts/fine-tuning-32b-legal-llm-outperformed-frontier-model-lower-cost/69e782f1feb2629cd50851d2)

### [LLM Inference GPU Sizing: How to Choose the Right GPU for Your Model and Traffic](https://flexai.hashnode.dev/llm-inference-gpu-sizing-right-gpu-model-traffic?utm_source=hashnode&utm_medium=feed)

How to size GPUs for LLM inference in production. Walk through real latency and cost tradeoffs for LLaMA 3.1 8B across L40, H100, and H200 — with toke

5 min read · [flexai.hashnode.dev](https://flexai.hashnode.dev/llm-inference-gpu-sizing-right-gpu-model-traffic?utm_source=hashnode&utm_medium=feed)

[Apr 14](https://hashnode.com/posts/llm-inference-gpu-sizing-right-gpu-model-traffic/69de486ad3d873268bfe11f8)

### [Why AI Infrastructure Software Is Harder Than Hardware — Lessons from Building Aurora and FlexAI](https://flexai.hashnode.dev/ai-infrastructure-software-harder-than-hardware-aurora-flexai?utm_source=hashnode&utm_medium=feed)

FlexAI CEO Brijesh Tripathi shares lessons from 25 years at NVIDIA, Apple, Tesla, and Intel — including delivering the Aurora supercomputer

7 min read · [flexai.hashnode.dev](https://flexai.hashnode.dev/ai-infrastructure-software-harder-than-hardware-aurora-flexai?utm_source=hashnode&utm_medium=feed)

[Apr 7](https://hashnode.com/posts/ai-infrastructure-software-harder-than-hardware-aurora-flexai/69d4ffd815135c96413880fc)

### [Heterogeneous AI Compute: Why Mixed NVIDIA, AMD, and TPU Clusters Are Harder Than They Look](https://flexai.hashnode.dev/heterogeneous-ai-compute-nvidia-amd-tpu-mixed-clusters?utm_source=hashnode&utm_medium=feed)

A practitioner's look at the runtime, scheduling, and deployment challenges of running AI training and inference across different architectures.

8 min read · [flexai.hashnode.dev](https://flexai.hashnode.dev/heterogeneous-ai-compute-nvidia-amd-tpu-mixed-clusters?utm_source=hashnode&utm_medium=feed)

[Apr 3](https://hashnode.com/posts/heterogeneous-ai-compute-nvidia-amd-tpu-mixed-clusters/69cfb9f2c67e01c86b0e7743)