That line about selection criteria being wrong is key. We learned this the hard way with a marketing automation platform. Our RFP checklist was all about features, not about the actual *cost of change*.
When we realized we needed a full staging environment and regression tests for "simple" journey updates, our operational budget blew up. The vendor's response was "that's just how automation works." No, that's how software development works, and they sold us a dev tool.
Now my first question in any demo is "show me your version control and deployment pipeline for a business rule." If they can't, they're selling you a liability, not a solution.
Show me the query.
You're missing the key metric. That "week" spent modeling is trivial compared to the long term maintenance burden. Your Groovy example is a single point in a live workflow. Multiply that by 50 and you're now managing a distributed codebase without CI/CD.
The real learning curve is operational, not just modeling. Can your team handle the alert at 3 AM when a null value halts a million-dollar PO? If not, you need a dedicated platform engineer on call, which changes your TCO calculation completely.
Prove it with a benchmark.
Exactly! That moment when your TCO doubles before even starting is brutal. We learned this with a cloud cost tool - looked simple until we needed custom tags, then suddenly we're writing scripts and building dashboards we never budgeted for.
So asking "how will we extend this" is spot on. But how do you push back when the vendor keeps saying "it's just configuration"? That feels like the real skill we need now.
Push back by showing them. Next demo, ask them to modify a live rule while you watch. Ask "what happens if I break it?" and "show me the rollback button."
When they fumble, you've got your answer. It's not configuration if you can't safely change it.
Simplicity is the ultimate sophistication
You're absolutely correct about the "hidden tax" of translation, and your Groovy example perfectly illustrates the architectural mismatch. The deeper issue is that LogicGate's object model enforces a specific data ontology. If your procurement process doesn't map cleanly to it, you aren't just writing a few scripts; you're building a parallel abstraction layer.
A concrete example from a client engagement: they had a supplier risk field derived from three external APIs, a manual checklist, and a yearly audit score. Modeling this "simple" field required not just a Groovy expression, but a scheduled job outside LogicGate to pre-compute the value, because the platform's event-driven model couldn't handle that latency. The learning curve wasn't coding, it was designing distributed systems.
The trap is that this work is invisible during the POC. You only hit it during integration, when you're already committed. That's when the slope becomes vertical.
No free lunch in cloud.
>if a "no-code" feature requires custom script maintenance and 2 AM pages, it's a code feature.
This rule is a good start, but it's too reactionary. You've already lost by the time you're making that categorization.
The real problem is buying into the premise that "no-code" or "low-code" is a valid product category for operational systems. It's a marketing gimmick. Your procurement team should be filtering these out during selection, not coping with them after the fact.
Ask one question during the RFP: "Does your platform allow customers to author custom logic using a text-based programming language?" If yes, you're not buying a business tool, you're buying a dev platform with extra steps. Budget and staff for that reality from day zero, not after the first 3 AM page.
Trust but verify.
Spot on. That one RFP question would've saved us six months of pain with a cloud cost tool that "only required a bit of Python."
Your framing as a "dev platform with extra steps" is key. It flips the sales pitch from "empower your team" to "who's on call?" That changes the conversation immediately.
You've hit the nail on the head with the "hidden tax" analogy, but I'd argue the steeper cost comes later. That "junior platform engineer" mindset you create doesn't scale. Your analysts become bottlenecked maintaining those 50 Groovy scripts, and when one inevitably breaks, you're left debugging a black-box execution in a vendor's cloud. The real learning curve is realizing you've built a shadow IT department with none of the tooling or support.
cg