Lifecycle stage — Run
The point of every Hyperion engagement is that your team ends up stronger, not reliant on outside help. Physical AI engineering upskilling is the Train pillar delivered as a capability: a structured programme that transfers the agent-augmented delivery methodology — the L0→L3 maturity climb behind shipping 1.7M lines of production code in two months — and working fluency in the Physical AI Stack (Sense · Connect · Compute · Reason · Act · Orchestrate) to your engineers, on your actual codebase and your actual machines. It is not a generic AI-literacy course; it is hands-on enablement for teams building real physical-AI systems with real deadlines.
Tools are not a method. Engineers have Copilot and a chat assistant and are barely faster, because nobody taught them the workflow that turns AI from autocomplete into an agent-augmented delivery system.
Physical AI spans disciplines most teams have never combined. Perception, edge, control, and safety each have their own experts; very few engineers can reason across the whole Sense-to-Orchestrate stack — which is exactly what physical-AI delivery requires.
Capability that lives in a consultant leaves with the consultant. Without deliberate transfer, the engagement ends and the team is back where it started the next time.
Delivered against your real work — not slideware — with the maturity climb structured so progress is measurable.
Assess the team's current delivery maturity (L0→L3) and physical-AI stack fluency, and agree the target and the real project the upskilling will run against.
Hands-on sessions on the agent-augmented workflow — orchestrating AI agent-roles across PM, dev, and QA — applied to the team's actual codebase, not a toy example.
Working sessions across the six layers so engineers can reason about perception, edge, decision, actuation, and orchestration as one system, with the standards context for safety-relevant work.
Coach the team through a real delivery increment, document the playbook in their words, and exit — leaving the method owned internally.
Industrial, robotics, automotive, and aerospace engineering teams that are building (or about to build) physical-AI systems and want their own engineers to own the delivery method — not to re-hire help for every project. Best paired with a Build engagement so the upskilling runs against live work.
No. It is hands-on engineering enablement run against your actual codebase and machines, focused on the agent-augmented delivery method and physical-AI stack fluency — not a vendor-neutral overview of what AI is.
Either, though the hands-on sessions work best with at least some on-site time. The programme is built around your real delivery increment regardless of format.
Agent-Augmented Delivery is the methodology I use to deliver every engagement; this service transfers that methodology to your team so they can use it themselves. The methodology is the how of delivery; this is the how of making it yours.
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