Fitted Automation
Engineering // Platforms

No-Code Automation: When They Work, When They Don't

► The Promise vs Reality

"Democratize automation." "Reduce IT dependencies." "Solve problems at the speed of thought."

The promise is compelling. The reality is nuanced. Platforms are training wheels for maturity, not the destination for scale.

> When Platforms Excel

Linear Workflows

If This -> Then That. Simple trigger/action sequences.

Prototyping

Validate logic before investing dev hours. Fail fast, cheap.

Empowerment

Let marketing fix lead routing without submitting a ticket.

Experimentation

Learn requirements through usage, not speculation.

> System Failures

[Scaling Limits]
Platforms work until they don't. Rate limits hit exactly during peak load.
[Integration Walls]
Great for SaaS. Terrible for legacy DBs or custom internal tools.
[Logic Gaps]
Complex business rules don't fit templates. Workarounds > Solutions.
[Vendor Lock-In]
Data trapped in proprietary black boxes. Migration costs compound.
[TCO Spike]
Per-user/per-task pricing exceeds dev costs at scale.

> Evolution Pattern

PHASE 1Experimentation (0-6mo)
↓
PHASE 2Limitations Hit (6-18mo)
↓
PHASE 3Hybrid Strategy (18mo+)

> Strategic Framework

USE PLATFORMS IF:

  • Simple, standardized workflows
  • Predictable, moderate volume
  • Standard SaaS integrations
  • Manageable failure impact
  • No competitive differentiation

BUILD CUSTOM IF:

  • Process creates advantage
  • Volume exceeds limits
  • Complex logic/legacy integration
  • Failure is critical
  • Long-term cost efficiency

> Modern Landscape

Make.com

Visual complexity. Data heavy.

N8N

Open source. Dev friendly.

Plumb

AI-native. Natural language.

Platforms are the start. Architecture is the destination.

SYSTEM_ID: NO_CODE_ANALYSIS // SECURE