Daniel Ball is a software consultant working through Westsmith. His experience spans storage systems, cloud migration and software delivery, and his technical writing explains how to integrate AI image generation into repeatable application and agent workflows.[2]
Start with A practical guide to AI image generation, from diffusion to agents →
Education
Links
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GitHub · dgnball Founder and Software Consultant · Westsmith
Career
Ball graduated from Exeter in computer science, then worked at Risk Decisions, BAE Systems, IBM Storage Systems and Roke Manor Research. His account includes storage software, protocol tooling, team leadership and developer coaching. He founded Westsmith in June 2019 and later delivered projects for government, healthcare and enterprise clients. His 2023–2024 work for Cambridge’s IT department focused on cloud migration to Google Cloud.[1]
Contributions
Ball’s image-generation guide combines experiments with an integration pattern: keep provider-specific calls behind a thin interface, record prompts and returned metadata, and treat generation as a slow operation that can fail. Exact layout and typography can be completed in code around the generated material. This lets an application change models, reproduce a request and inspect the actual result instead of depending on an undocumented one-off chat. The guide distinguishes creative image work from deterministic post-processing.[3]
Tools, writing & talks
Writing, research & talks
Start here
An experiment-backed guide to image models, prompting, provider interfaces and agent integration.
Begin with the integration sections and compare them with one image task you want to repeat. Basic Python and API knowledge help with implementation; the examples explain when code should handle exact edits and layout.
Author[3]Original source