How to Evaluate an Engineering Orchestration Layer in 30 Days

Roughly 95% of enterprise generative-AI pilots deliver no measurable return, per the MIT study that became 2025's most-cited AI statistic. The failure isn't usually the model. It's the evaluation: a demo is an open-book exam — known inputs, the vendor in the room, retries allowed — and production is a closed-book exam set by reality. As Andreas Anding put it, "none of that survives contact with production." Teams pass the first exam and assume they're ready for the second. They aren't in the same room.

This guide is how to run a 30-day evaluation of an engineering orchestration layer so you actually learn something. It works for any vendor, including us. The point of the month is one question: does this stop bad hardware changes before they ship, in our environment, on our data?

Start with one real workflow

The most common evaluation mistake is the feature checklist: capabilities walked through on sample data. It tells you nothing, because orchestration quality is entirely about your tools, your data, and your mess. MIT's March 2026 agentic-AI study found adoption is constrained less by model capability than by fragmented, machine-unfriendly data and limited API-accessible toolchains. A checklist can't test that. Only your workflow can.

Pick one change type that has actually hurt you. It should recur at least monthly, cross at least two tools (schematics plus firmware, CAD plus BOM — cross-discipline inconsistency is what orchestration exists to catch), and have a named bad outcome: a respin, a wrong-BOM build, a firmware rev flashed against the wrong schematic. If you can't name what "bad" looks like, you can't measure whether the layer prevents it.

Write down how that workflow runs today — who touches what, where the checks are, where they fail — before the vendor sees any of it. That document is your baseline. Everything in week 4 gets measured against it.

One signal this problem is real: hardware teams are already hand-rolling the plumbing themselves — git-based source-of-truth repos for design context, human-approval gates bolted onto agent outputs, hand-built CAD bridges. Nobody builds infrastructure like that for fun. When your engineers are writing their own governance layer, the pain is verified; the only question is whether a product does it better than your weekend scripts.

A week-by-week plan: connect, gate, measure

Week 1 — Connect. The vendor plugs into your real tools: your GitHub, your Onshape or SolidWorks, your KiCad, your Arena or Windchill. Data flows, read-only to start. Success at the end of week 1 is simple: the layer sees your actual design data. This is also your first filter. An orchestration layer sits on top of your stack — no migration, no rip-and-replace. If a vendor asks you to move your data or adopt their toolchain before the pilot starts, they aren't selling orchestration. Walk away.

Weeks 2–3 — Gate one real change. Run your chosen workflow through the layer with a live change, not a canned demo. The system should watch the change move across tools and flag inconsistencies a human reviewer would plausibly miss: a schematic net rename that didn't propagate to the firmware pin map, a BOM line that no longer matches the CAD assembly, an ECO approved in one system and stale in another. Let your engineers act on the flags — accept, override, ignore — because the override rate is data. A layer that flags everything is as useless as one that flags nothing.

Week 4 — Measure and decide. Compare against the success criteria you wrote before day 1 (below). No new criteria, no moving goalposts. At the end of the week you make the call.

Success criteria that mean something

Write these before the pilot starts, in writing, signed by whoever owns the budget. Good criteria share three properties: pass/fail, observable by your team (not the vendor), and tied to a decision. Examples:

• The layer catches at least one real cross-tool inconsistency on a real change during weeks 2–3. "Real" means your engineers agree it would have shipped uncaught.
• Every flag and every agent action is traceable to its source data. Non-negotiable. The MIT study is explicit: reliability, verification, and auditability are central requirements for adoption in engineering and manufacturing, because engineering accountability doesn't transfer to a black box. If you can't audit it, you can't ship with it.
• Change-gate latency is measured against your current review cycle — stated as a number, not "faster."
• Override rate stays under an agreed threshold. If your engineers override 60% of flags, the layer is noise.

If a vendor resists fixed, written criteria — "let's keep it flexible, see what we learn" — that is information. Vendors who are confident in production behavior want the test to be sharp.

Traps

POC theater. The vendor runs the pilot on their hardware, their data, with a solutions engineer steering. Eight-out-of-ten success on stage becomes two thousand silent failures a day in production — Anding's arithmetic. Insist on your data, your tools, your engineers driving.

Evaluating on slides. Architecture diagrams, roadmaps, "our model is better." The model was never the thing standing between you and production — the system around it was. Grade the system: the gates, the audit trail, the behavior on your dirty inputs.

Boiling the ocean. Five workflows, twelve tools, "let's see the full platform." You'll learn nothing about any of them. One workflow, done properly, tells you more than a tour of everything. Depth is the only thing a pilot can give you; breadth is what sales decks are for.

The drifting pilot. Thirty days ends at thirty days. A pilot that slides into month three with no decision wasn't an evaluation — it was a free trial wearing a lab coat.

The decision

At day 30, you should be able to answer three questions: did it catch something real, can we audit everything it did, and do our engineers trust the flags? Yes to all three — buy. No to any one — kill it, and say which criterion failed so the next vendor knows what to fix. The worst outcome isn't a failed pilot. It's a pilot that ends in "promising, let's extend" with no criteria, no measurement, and another month of your engineers' time.

Our pilot is built for this shape: a fixed $8,000, 30 days, success criteria agreed up front, run against your real tools. If that's the evaluation you want to run, book a demo.