Common AI project failure modes
AI projects rarely die at the demo. They die months later, in production, for reasons that were visible on day one.
The demo was never the risk. Projects fail because ownership, evaluation, latency, cost, permissions, deployment and recovery were left for later — and later arrived with users watching.
A model call gets mistaken for a system
The model is one box in the diagram. The work that decides success is around it: data flow, queues, retries, logs, review surfaces, deployment, cost control. Teams that budget only for the box ship only the box.
Evaluation arrives after the arguments start
Without evals or acceptance examples, every prompt change is an opinion and every regression is invisible until a user reports it. The eval suite is cheapest on the day the prototype first works — that's when to write it.
Nobody owns the failure
A production AI workflow needs a named owner for bad answers, provider outages, duplicate work and escalation to humans. If the answer to "who gets paged?" is a shrug, the system isn't in production — production is in the system.
Case studies behind this
- Orchestrating long-running inference on serverless GPUs
Transient disconnects no longer killed useful work, and finished or abandoned jobs released GPU resources instead of leaving expensive workers pinned.
- A multi-provider AI gateway with built-in cost accounting
Model choice became configuration, new providers inherited common controls, and spend became visible while requests were still running.
Related services
AI automation consulting
Start here when a manual process is eating senior hours, a no-code chain has hit its ceiling, or an AI idea needs a build plan before it gets budget.
Open serviceLLM productionization
Start here when the prototype is convincing but nobody can say what it costs at scale, why it fails, or whether yesterday's prompt change made it worse.
Open serviceAI agent workflow design
Start here when the team wants agents, but nobody has decided what happens when one fails at 2am.
Open service