Skip to content
Aplora
EdTech
Document & Reporting Automation

Client under NDA

Course materials stopped going stale faster than they could be updated

An online IT school with a large product base: dozens of modules, each with assignments and quizzes. The technologies in the syllabus change faster than the methodologists can rewrite the materials.

Published: 2026-08-24 · updated: 2026-08-24

A desk with reference material pinned to the wall, someone making notes
Illustrative photo of the working context, not a screenshot of the client's system

  • Speed of releasing and updating material

    ×10

  • Share of manual work in content production

    −50%

  • Cost of producing content

    −40%

In short

  • Problem: releasing and updating materials took weeks, and the product aged between releases.
  • Solution: a single knowledge base and course standards as the generation frame, drafts of materials and assignments, syllabus conformance checks, and post-publication staleness monitoring.
  • Result: preparing material against an existing standard is roughly ten times faster; the share of manual work halved.
  • Systems: knowledge base, LMS, assignment templates.

Context

  • An online IT school; name under NDA, regions CIS and EU.
  • Process volume: a large product base — dozens of modules with assignments and quizzes.
  • Team: methodologists and the course product team.
  • Systems: knowledge base, LMS, assignment templates; some under NDA.
  • The constraint became visible as the catalogue widened: every new course added not only development but permanent upkeep of what was already released.

Baseline

Baseline metrics with their sources. Without them, any later result has nothing to be compared against.
  • A new module or an update takes weeks
  • The load on methodologists grows faster than the team
  • The product ages between releases
  • A student sees an example on a library version that no longer exists
  • Before the work started we fixed: the time to prepare one module, the share of methodologist time spent on manual work, and the average age of a material at its last update.
  • Data source: time records and the change history in the knowledge base.
  • What the speed figure measured: preparing material against a course standard that already exists. Designing a new syllabus from scratch does not speed up this way — the work there is methodological, not production. Without that caveat, “×10” would read wider than it is.

Diagnosis

Which hypotheses were considered, why this one was chosen, what was assumed, and the condition under which we would have stopped.
  • Three hypotheses were on the table: hire more methodologists, change the authoring tool, or stop spending time reproducing what is already written down.
  • The third was chosen: review showed the material is largely reassembled from what the knowledge base already holds — and reassembled by hand every time.
  • The assumption: the course standards are described well enough to serve as a frame. Tested on released modules — and it needed work: some standards existed only in the methodologists' heads.
  • Stop criterion: if a draft needs more than half of it rewritten, there is no saving — reviewing and fixing costs as much as writing from scratch.

What we implemented

  • Data sources: the course knowledge base, the standards and syllabus, assignment and quiz templates, student feedback.
  • AI components: material drafts, generated assignment and quiz variants, syllabus conformance checks, detection of stale fragments after publication.
  • Business rules: the course standard sets the frame. Generation does not step outside it — otherwise the product sprawls faster than anyone can review it.
  • Integrations: knowledge base, LMS.
  • Human checkpoints: a methodologist publishes. Review is mandatory and never skipped “because it looks right anyway”: a factual error in teaching material costs more than one in a newsletter.
  • Monitoring: the share of drafts needing substantial rewriting. Its rise means the standard has drifted from the syllabus.

How the process changed

Before

5 steps
  1. The methodologist assembles the material by hand from their own sources
  2. Assignments and quizzes are written from scratch for every module
  3. Syllabus conformance is checked by eye
  4. Publication to the LMS is manual
  5. Staleness is discovered through student feedback

After

6 steps
  1. The knowledge base and course standards as the source
  2. A draft of the material and of assignment variants
  3. A syllabus conformance check
  4. Review and publication by a methodologist
  5. Feedback collection
  6. A staleness signal on an outdated fragment

What was stuck

A new module or an update took weeks. The load on methodologists grew faster than the team, and the product aged between releases: a student would see an example on a library version that no longer exists.

  1. 1The knowledge base and course standards as the source
  2. 2A draft of the material and of assignment variants
  3. 3A syllabus conformance check
  4. 4Review and publication by a methodologist
  5. 5Feedback collection
  6. 6A staleness signal on an outdated fragment
  7. Measured result

Results

Speed of releasing and updating material

×10

Reported by: Client figures: measured on preparing material against an existing course standard, not on designing a syllabus from scratch

Share of manual work in content production

−50%

Reported by: Client figures: their own time records for the methodology team

Cost of producing content

−40%

Reported by: The client's own cost model; the composition of the costs was not disclosed to us

Economic impact

  • The effect is freed methodologist time, which goes into methodology rather than production.
  • The cost reduction is the client's calculation from their own model; the cost composition was not disclosed to us.
  • Cost of ownership is higher than it looks: the course standards and knowledge base need maintenance, and without it draft quality is the first thing to slip — quietly.

Adoption

  • The team works to shared standards rather than personal boilerplate.
  • Updates became regular: previously they happened in a scramble before each new intake.
  • The solution owner is the product lead, who is also accountable for the course standards.
«Updates and new modules used to take weeks and consume the methodologists. Now content ships faster, to a standard, and with a clear quality gate.»

Client under NDA — Product lead, EdTech (NDA)

What's next

  • Scaling: extending the loop to programmes whose standard is not yet written down.
  • Next initiative: linking student feedback to the specific fragments it refers to.
  • What we decided against: publishing without review. The saving is obvious and deceptive: one factual error in teaching material costs more than the entire time gain.

Have a similar workflow? Let's check whether the hypothesis transfers

Another company's result is not a promise. It does show where to look.

All cases