Use case

Modernize a legacy codebase with agents — safely

Legacy modernization is where AI agents are most tempting and most dangerous. Skaftor grounds agents in the system's real structure and gates every change by blast radius, so you can move fast without detonating a landmine.

The situation

You want agents to help modernize a large, poorly-understood codebase. But agents don't know which components are load-bearing, and a wide-reaching change to legacy code can cause an outage before anyone notices.

How Skaftor does it

Step 1

Map the system before you touch it

Skaftor reverse-engineers the codebase into a knowledge graph — dependencies, owners, and the latent risks (landmines) worth flagging before work starts.

  • Dependency and ownership graph
  • Flag architectural landmines up front
Step 2

Scope every change by blast radius

Before an agent's change merges, Skaftor computes its blast radius from the graph, so review and testing scale to real reach — not diff size.

  • Blast radius on every work order
  • Wide/systemic changes gated for extra review
Step 3

Ship behind gates

Approval gates, drift checks, and release-confidence scoring guard each step, so modernization proceeds incrementally with a rollback path, not in one risky leap.

What you get
  • Agents accelerate modernization without stepping on hidden dependencies.
  • Risky changes are caught by blast radius before they ship.
  • A safe, incremental path instead of a big-bang rewrite.

Capabilities behind this

Frequently asked questions

How do you use AI agents on legacy code without breaking things?

Ground the agents in the system's real dependency and ownership graph, compute each change's blast radius before merge, and gate wide-reaching changes for extra review and staged rollout. Skaftor does all three, so agents accelerate modernization without tripping hidden dependencies.

Related

Last updated July 28, 2026 · https://skaftor.com/use-cases/modernize-legacy-code-with-agents