FDE readiness for freshers: demonstrate foundations before autonomy

Readiness is visible in work: code another person can run, tests that catch failures and a recovery path. It is not a personality label or promise of independent client delivery.

Check the artifact ladder

The delivery lab evaluates a fictional learner record.

from delivery_cases import readiness_case

result = readiness_case()
assert result["foundation_count"] == 5
assert result["ready_for_independent_delivery"] is False
assert result["supervised_next"] == ["rollback_runbook", "client_discovery"]

The learner has CLI, tests, API contract, container spec and health check, but still needs supervised rollback and discovery practice.

Use evidence gates: installable package; tested business/API boundaries; Git review; deployed or reproducibly local service; structured logs; backup/restore; rollback; discovery, scope, demo and handover simulation. Ask the learner to explain one failure and repair.

Autonomy grows gradually. Start with synthetic data and read-only systems, then sandbox writes behind approval. A mentor reviews risk and communication before wider responsibility. This fixture is not an admission, placement or hiring decision.

The FDE for Freshers course is designed from zero coding experience across approximately 30 weeks.

Exercise

Build your artifact matrix with links and reviewer status. Select the next two missing prerequisites and define how another person will verify them.

Continue learning

This article is part of the FDE career entry and client-delivery practice sequence. Use the neighbouring tasks when you need the prerequisite or the next application.

• Continue with Choose a first FDE portfolio project with a bounded client problem.
• Then apply it in Run a discovery interview for a fictional client.

Reference: GOV.UK service assessment guidance.