ViBe

AI tools don't break all at once — they drift. This episode unpacks the scope creep trap that quietly degrades custom AI agents, and the one discipline that stops it before it starts.

Show Notes

A custom AI agent can be working brilliantly on launch day and nearly unrecognizable a month later — not because anyone made a mistake, but because everyone made a reasonable request. This episode of ViBe digs into why scope creep is uniquely dangerous in AI tooling, and lays out the pre-build discipline that keeps agents focused and reliable over time.

Here's what the episode covers:

  • How scope creep actually happens — a step-by-step walkthrough of a single customer-enquiry drafting agent that gradually absorbs five additional jobs, each addition individually sensible, collectively destructive.
  • Why AI tools fail differently from traditional software — conventional tools break loudly; AI tools fail softly, continuing to produce output that is subtly worse or quietly wrong in ways that only surface after the damage is done.
  • The job description framework — writing a one-sentence primary outcome and an explicit out-of-scope list before a single instruction is drafted, because both halves carry equal weight.
  • Using the out-of-scope list as a decision filter — how a pre-written boundary turns every future feature request into a quick check rather than a full design renegotiation, keeping custom internal tools coherent as business needs evolve.
  • The backlog-as-roadmap principle — rejected scope isn't wasted thinking; recurring requests signal which capabilities deserve their own focused agent, a pattern that sits at the heart of building a scalable business operating system.
  • A practical audit you can run today — a retrospective exercise for any AI tool already in production: one sentence on what it does, five bullets on what it doesn't, then a line-by-line check of the current instructions against that description to find where reliability is leaking.

The episode is a useful companion to ViBe's earlier look at getting a new agent up to speed — if you missed it, The Cold Start Problem: How to Give a New AI Agent Enough to Work With covers the other side of the same challenge. For more on how focused agents are built and deployed — including how they can work alongside or replace existing software — explore AI employees and the build process at VB.co.

VB.co

What is ViBe?

Building the connective tissue of a modern business software stack — shared identity, module boundaries, tenancy models, and the integration decisions that are cheap now and expensive later.

Each episode takes one architectural decision — where a tenant boundary belongs, how modules should hand off a signed-in user, what to share and what to duplicate — and reasons through the consequences a year out. Written for platform engineers and architects designing systems other teams will build on. Five or six minutes, one decision, no framework advocacy.

Topics include tenancy models and boundaries, shared identity and single sign-on between modules, what to share versus duplicate, module contracts and versioning, migration paths, and integration decisions that are cheap now and expensive later.

Produced by ViBe. Full details, services and further reading at https://vb.co