Applying future-proofing principles to CTI's actual architecture — what to revisit on every model release, where the architecture should evolve, what's missing, and a concrete review cadence. The companion piece that turns the general principle into a working checklist for one production AI system.
How Orbital's three phases — Map, Architect, Build — were applied to CTI specifically. The case study from the inside: what got mapped, what got architected, what got built, and why the order matters.
How Orbital built an AI coaching platform whose recommendations are grounded in the athlete's own power data, fitness trajectory, and past conversations — not generic advice. The public proof of concept for the approach Orbital takes with every client.
How CTI's Performance Management Chart implementation — Critical Power, Normalized Power, TSS, CTL, ATL, TSB, plus subjective Feeling and RPE — gives the AI coach a quantitative model of fitness, fatigue, and form.
How CTI's prompt versioning, skill system, admin trace review, Evalite evals, and Langfuse telemetry form a reinforcing loop that makes the AI coaching layer improve with every user interaction.
A deep dive into the intent routing, layered prompts, three-tier memory system, and hybrid search that power CTI's AI coaching layer.
Transform indoor cycling training files into an interactive, cinematic experience. Not just charts — a way to discover insights about routes, locations, and performance through exploration.