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Requs AI Training Series

How to identify software program risks early

A 1-day, virtual, self-guided training class on spotting the risks that derail software programs — before they've already derailed them.

identify software program risks early training
1 Day
Virtual, self-guided — work through it at your own pace
Recommended For
Teams using Requs AI Risk ID or Requs AI Predict
No Software Required
The class can be purchased and taken on its own, without any Requs AI product
01 — Authority

Our founder is the global leader in software reliability and program risk

Standards Body

IEEE 1633 Leadership

Chair of the 2026 IEEE 1633 working group — the governing standard for software reliability engineering.

Continual lessons learned applied to the world's largest defect density benchmarking study

Decades of Trending Data

While others fail to keep their model factors current with technology - we're on our 8th major revision since 1993.

World's largest database of software failures analyzed by root cause

CDE Taxonomy inventor

From it, we created the Common Defect Enumeration, the primary taxonomy currently adopted and cited across DOW technical frameworks.

02 — The Class

Most program risk gets identified after it's already too expensive to fix

By the time a software program's risks show up as a missed milestone or a late delivery, they were usually visible months earlier — if anyone had known what to look for. This class teaches the same reasoning behind why software projects fail, so risks get caught while there's still time to act on them.

This class pairs naturally with Requs AI Risk ID and Requs AI Predict — but doesn't require either. It's built to be useful on its own.

Capability
Without this training
With this training
Spotting risks before they derail the program
Reactive — discovered only after a schedule slip or failed milestone
Structured early identification, before the program is committed to the risk
Understanding why software projects actually fail
Folklore and anecdote, repeated from project to project
Grounded in the documented reasons software projects actually fail
Weighing which risks matter most
Gut feel, or whichever risk was mentioned most recently
Tied to the factors that actually correlate with project success and failure
Connects to your existing tools
Generic risk-management training, disconnected from your data
Built to pair directly with Requs AI Risk ID and Requs AI Predict
03 — Curriculum

What the class covers

Three modules, covered in a single self-guided day.

§1Why Projects Fail

Reasons why software projects fail

What You'll Learn

The documented, recurring reasons software projects fail — not the postmortem excuses, but the patterns that show up again and again across programs.

Why It Matters

You can't watch for a failure pattern you've never been taught to recognize. Naming it is the first step to catching it early.

§2Program Risks

Software project risks

What You'll Learn

How to identify the specific risks present in your own program — scope, schedule, staffing, and technical risk — and score them before they turn into missed deadlines.

Why It Matters

A risk that's identified and scored can be managed. A risk that's invisible until it happens can only be reacted to.

software project risks percentile rank identification dashboard

Risk identification in practice: a predicted percentile rank, probability of late delivery, and predicted customer satisfaction, scored against a distressed-to-world-class benchmark scale — the same kind of scoring this module teaches by hand.

§3Success & Failure Factors

Factors that contribute to software project success and failure

What You'll Learn

The specific, measurable factors that separate programs that deliver from programs that don't — so risk conversations are grounded in evidence instead of opinion.

Why It Matters

This is the same factor set behind Requs AI Risk ID and Requs AI Predict — by the end of this module you'll understand what's actually driving the score, not just the score itself.

software project risks predicted risk level chart

Predicted risk level is one piece of a larger picture: reliable software predictions roll up into RAM metrics, SLA/RAM metrics, and SQA and test metrics — the same factor set this module covers.

04 — Class Details

Format, duration, and prerequisites

Duration

1 Day

Delivered as a single day of self-guided instruction.

Format

Virtual, Self-Guided

Work through the material on your own schedule, at your own pace.

Prerequisites

None Required

Recommended for teams already using Requs AI Risk ID or Predict, but the class can be purchased and taken entirely on its own.

Catch the risks that derail software programs — before they do.

Register for the class, or schedule a demonstration of the Requs AI tools it pairs with.