Kindled Flame StudiosIndependent ideas. Tangible work.
I’m Justin Almquist. I turn complex ideas and workflows into working software through system design, AI-directed implementation, hands-on testing and iteration. I design, use and manage these systems daily.
One person directing the work, using AI teams for implementation. Scope, delivery stages, validation and ongoing management needs are discussed before work begins.
Map the user journey, constraints and essential behaviors, then direct delivery of an agreed system or feature. Make the result concrete, testable and connected to the problem it needs to solve.
Design a browser extension, desktop utility or AI-connected workflow, then direct a scoped implementation. Use prototypes where they answer a question; validate delivered behavior in the workflows it is meant to support.
Assess the product behavior, workflow gaps and system design in an existing AI-assisted build. Define and direct its next phase, validate it in actual use and manage its evolution.
These are studio projects I designed and directed through AI-assisted development. They demonstrate outcomes, not claims of personally writing their code.
CinderACE brings export formats and optional destinations into a single browser workflow. It shows product design around a recurring user need: making conversations portable.
ember-memory connects a desktop controller, imported knowledge and retrieval hooks. Its public source and recorded demo let you inspect how the design carries context across AI coding tools.
The KFS account and payment system connects checkout, email verification and license entitlement. This is a studio systems example, not a client engagement or a security certification.
I own product vision, system design and delivery direction. My AI coding teams implement the software; I test it in actual use, guide iteration and manage how it develops. I have coding experience from earlier work, while my current practice centers on design, orchestration and validation.
Technologies used across KFS projects
TypeScript · React · Python · Rust · Go
Desktop apps · Browser extensions · AI systems
Delivery scope includes clear validation evidence and any remaining review needs. Production security, compliance and independent code assurance are scoped with appropriately qualified specialists when required.
Clarify the audience, the friction, the constraints and what successful delivery needs to demonstrate.
Direct AI-assisted implementation, test the system in actual use and refine the result against the agreed behavior.
Review what was delivered, explain what was checked and agree on handoff or ongoing system management. Document limitations and the specialist review needed for further use.
Send the idea, who it is for and the part that feels stuck. We can discuss a useful scope and whether this process fits.