Engineering: Where Everything Begins and Ends
Once you understand the system-level vision, you need to make it real — and that begins with engineering. This isn’t about CAD drawings or circuit boards; it’s about deeply listening to customers, negotiating what’s possible, and building the foundation for a product that can scale. At Dexterity, engineering is where the promise of physical AI starts to take shape, grounded in trade-offs, systems thinking, and hard-won principles of product design.
If manufacturing is the body, and operations is the nervous system, then engineering is the brain of Mech. At Dexterity, every product journey starts with a simple but essential question:
What does the customer truly need — and what are they willing to pay for?
We start not with internal targets or spec sheets, but with real-world workflows:
- What environment will it run in?
- Who operates it — and how often?
- What uptime and cycle time make the business case work?
- How does the customer measure success?
These aren’t abstract questions — they’re the backbone of good engineering. Once we understand the customer, we translate that into system-level requirements — defining performance, interfaces, reliability, latency, and safety boundaries. Only then do we break it down into hardware and software specs — for grippers, arms, drivetrain, compute, sensors, diagnostics, and everything else needed to make Mech not just functional, but field-ready.
Negotiation Is Part of Engineering
Product design isn’t a wishlist. It’s a negotiation. We don’t just negotiate within Dexterity between software, hardware, and field teams. We negotiate with our customers too — openly and honestly. We ask:
- What’s possible with the current state of technology?
- What will bend our architecture — and what might break it?
- What’s the real cost of that “just one more” feature — in time, in dollars, in downstream complexity?
These conversations aren’t easy, but they’re critical. Our customers don’t need magic. They need a roadmap they can trust. This is how we keep Mech real, not hypothetical.
Product Design Principles: Discipline Before Scale
We follow a few hard-won truths that have saved us more than once:
1. Architecture Matters
The first decisions are the most permanent. A flawed concept will haunt you — no matter how fast you move. Even being first to market won’t help if your architecture limits performance or reliability.
2. Concept Quality is Everything
Good architecture starts with a sound concept. We stress-test ours early — for feasibility, simplicity, extensibility, and long-term risk. A weak concept gets more expensive with every build.
3. Product Quality > Early Cost Wins
You don’t get a second chance if your product fails in the field. Reliability and build quality are table stakes — not stretch goals.
4. Sequence Matters
Get customer traction first. Then optimize cost. Premature cost-cutting leads to fragile designs — and painful field failures.
Platform Thinking: Build Once, Scale Many
We don’t treat Mech as a one-off product. It’s the foundation of a platform — and we’ve designed it accordingly. Our architecture supports:
- Commonality: Robotic arms, chassis, compute, vision, powertrain, harnessing — all shared across Dex product lines.
- Modularity: Subsystems are designed as swappable, reusable blocks — easily adapted across truck loading, palletization, and parcel handling.
- Configurability: We use an Integrate-to-Order approach — pushing customization as late as possible, so we can scale efficiently without sacrificing flexibility.
This strategy enables:
- Faster time to market
- Lower engineering overhead
- Simplified supply chain
- Easier field service
- Better margins at scale
It also enables something even more valuable: focus. We’re not reinventing the wheel for every customer. We’re building a system that learns, scales, and compounds value.
Design for X: Balance Is What Makes It Real
Building Physical AI isn’t just about vision. It’s about balance — and that’s where our engineering team puts its weight. We follow a disciplined Design for X (DfX) framework that ensures we don’t just build great robots — we build real products that thrive in the field. We organize DfX with a clear priority order:
#1 SAFETY This is non-negotiable. Operator safety, service safety, system fail-safes — everything starts here.
#2 FUNCTIONALITY The system must perform. Accurately. Repeatably. Robustly. Performance metrics aren’t “nice to have” — they mean survival.
#3 BALANCE The most overlooked. A product isn’t real until it balances all competing constraints: manufacturing, certification, ergonomics, service, cost, testability.
Balance is where the magic happens — and where most prototypes go to die.
Here’s how we apply DfX every day:
- DFA – Design for Assembly
- DFC – Design for Cost
- DFE – Design for Ergonomics
- DFM – Design for Manufacturability
- DFCE – Design for Certification
- DFR – Design for Reliability
- DFS – Design for Serviceability
- DFD – Design for Diagnostics
- DFT – Design for Test
- DFTP – Design for Transportability
- DFAE – Design for Aesthetics
Whether we’re designing a gripper or onboarding a CM, DfX is baked into the process. Because when you design for safety, functionality, and balance, the result isn’t just a flashy demo — it’s a product that lasts.
You Can’t Fake Reliability
In a previous startup, we shipped what we thought was a “working prototype” to a customer site. Within days, it failed. The cause? A system that hadn’t been fully characterized for all field environments. We’d tested function — not endurance. The cost: weeks of credibility, frantic triage, and damaged trust. Since then, I’ve carried a rule with me:
You don’t ship until you’ve tested the extremes.
At Dexterity, We Do Things Differently
When we started building Mech, we made a conscious choice:
- Don’t treat the field as your lab.
- Don’t treat manufacturing as a handoff.
- Build with the end in mind.
We mapped out everything required to go from prototype to product — and treated each item as core to product success, not “nice to have”:
- Validation and verification
- Component qualification
- Reliability growth modeling
- Functional safety
- Logistics planning
- Packaging and shipment
- NPI and manufacturing training
- Spare parts strategy
- Field diagnostics and support
- Documentation and certification
We didn’t outsource this work. We didn’t bury it in a checklist. We prioritized it. We reviewed it. We owned it. Because that’s what it takes to go from something that works once… to something that works every time, everywhere, at scale. Here’s a look at the hidden work — the failure modes we anticipated, and the intentional choices we made to avoid them. Each one could’ve sunk Mech before it ever scaled.
| What Could Have Gone Wrong | What We Actually Did |
|---|---|
| Used cheap, unvetted components for quick wins | Ran full qualification and lifecycle planning |
| Ignored reliability modeling | Built reliability growth curves into the dev cycle |
| Deferred packaging and logistics planning | Designed packaging, transport, and unboxing from day one |
| Treated pilot build as a demo | Used it as a system validation checkpoint |
| Overlooked serviceability in mechanical design | Designed hot-swappable parts and fast access points |
| Let tribal knowledge live only in senior engineers | Codified everything into build instructions and checklists |
| Assumed test coverage based on 'it works' | Wrote validation protocols with pass/fail criteria, including extreme conditions |
| Delayed manufacturing readiness | Used a concurrent NPI and build-readiness workflow |
| Treated the CM as a vendor | Engaged Sanmina as an extension of our internal team |
| Waited to write field documentation | Created install, service, and escalation playbooks early |
| Designed for function, not serviceability | Built in modular service-friendly subsystems |
| Used dev boards and breadboards | Qualified production-ready parts from day one |
| Assumed we could assemble it ourselves | Partnered with Sanmina for scalable assembly |
| Skipped safety standards | Baked in functional safety and compliance tests |
| Focused only on throughput | Modeled MTBF, uptime, and long-term reliability |
| Used tribal knowledge for scaling | Built internal documentation & training early |
| Waited too long to industrialize | Engaged Sanmina early for NPI & scale-up |
| Built the prototype, then scrambled for scaling | Designed with manufacturing and serviceability in mind from Day 1 |
| Assumed the factory would catch design defects | Built validation tests upstream of the line |
What Comes Next: Engineering Meets the Real World
Great engineering sets the direction, but it takes great manufacturing to realize it. All the smart design decisions in the world won’t matter if they can’t be built at scale, on time, and with consistency. In the final blog of this series, I’ll walk through how we approached manufacturing at Dexterity — why we partnered with Sanmina, what it takes to make physical AI real in production, and how we turned the “invisible work” into a competitive advantage.
