Synopsis
Bones of Yew follows a pagan peasant archer during the Hundred Years’ War. As war rises and the old ways fade, he reflects on the land, the yew tree, and the changing tide of faith.
The story takes an introspective view from the perspective of this peasant rooted in nature, toil, and quiet reverence, who watches as Christianity spreads across the land. When churches were first raised in England, it was the pagans who pointed to the ancient yew trees as sacred ground. Many churches to this day still stand beside these trees, which long predate Christianity.
In the eyes of the peasant, the yew does not resist the new faith it simply endures it, as it has endured all seasons. Through AI-generated visuals, layered voiceover, and historically inspired sound design, the film evokes the resilience of common men ,those who, with longbows carved from sacred yew, brought down the armoured nobility at the Battle of Crécy.
The film is underscored by a beautiful but haunting original score by Jordan Hudson,
featuring La Vergues Astrea by Bill Vine and vocals by Paulin Bündgen. Sung in “Occitan” an old French dialect, the track weaves a mournful tone through the narrative—complementing the film’s reflection on faith, loss, and the tragic poetry of war in medieval France.
Bones of Yew is a reminder that AI filmmaking still relies on the skill, creativity, and collaboration of talented people.
Bones of Yew explores AI’s potential to deliver cinematic, historically grounded storytelling with emotional, character-centric depth. AI was used to analyse historical sources rooted in 14th-century life ,informing everything from costume to architecture. These references became the foundation for prompt generation, which was then refined through a cinematic lens to evoke realism, tone, and thematic weight.
A core focus of the project was character consistency. I developed a custom LoRA trained on actor Matt Lewis to maintain his likeness across time, enabling the character to age and evolve naturally throughout the film. The training involved a bespoke dataset built through photographic references, contextual motion studies (such as archery and farming), and volumetric capture to produce high-quality, realistic input data.
Additionally, I experimented with LoRAs to replicate and stylise ancient yew trees, enabling consistent visual language and symbolic continuity throughout the film. These yews, revered as sacred in both pagan and Christian traditions, were trained and tuned with real-world yew to generate the recurring imagery of the trees at the heart of the story.
This approach demonstrates how AI can now sustain continuity, realism, and performance across narrative arcs ,bringing new depth to independent filmmaking.
But most importantly, Bones of Yew is a reminder that AI filmmaking still relies on the skill, creativity, and collaboration of talented people. It’s not about sitting at a laptop and generating a film in isolation—it’s about combining fieldwork, photography, and performance to enhance believability, all while keeping production accessible for creators outside the traditional system.