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Keep Systems Consistent as They Grow

· 2 min read
Codey
Codey
Your repo is just a giant inference puzzle

Speed is easy.

Consistency is not.

The failure shows up late.

As the system gets larger, the agent sees only slices of it at a time.

It sees files. Prompts. Tests. Comments. A ticket. Maybe some memory from an earlier session.

From that, it has to infer:

  • what behavior is actually accepted
  • which decisions are still active
  • what is in scope for this task
  • which tests prove real intent
  • which nearby code is authoritative versus incidental

Sometimes that inference is good enough.

As the system grows, good enough stops being good enough.

The same AI speed that makes feature work exciting starts making inconsistency compound faster.

What You Actually Want​

You do not want agents to be timid.

You want them to move fast.

But you do not want them to reinterpret the product every time they touch it.

You want to say:

Here is the accepted behavior.
Here are the decisions already made.
Here is the scope.
Move fast inside that.
If you need to change it, propose the change.

That is a very different development model from "point the agent at the repo and review whatever comes back."

What Fernsehturm Changes​

Fernsehturm keeps requirements, decisions, scope, checks, and code linked.

That means consistency is no longer something you hope reviewers preserve by reading everything carefully.

It becomes an active property of the system.

When an agent proposes work, Fernsehturm can ask:

  • Does this code trace to accepted requirements?
  • Do these tests prove accepted behavior?
  • Is this decision still active?
  • Is this file change inside scope?
  • Is this extra behavior a valid implementation, or a new proposal?

This is the wedge:

Let the agent move fast inside the box. Stop it when it tries to move the box.

The box is accepted intent.

Why This Matters​

Without this structure, consistency becomes a human burden.

Review turns into reconstruction. The team has to rediscover what was accepted, what was rejected, what changed, and what the agent assumed.

With Fernsehturm, the agent can still propose better behavior, alternative implementations, or decision changes.

But it cannot quietly turn nearby intent into accepted truth.

That is the difference between letting agents generate code and letting agents evolve a system that stays coherent over time.