Build Release Confidence as Fast as Teams Create Change
AI can generate requirements, code, tests, and documentation faster than ever. Hyper-Agile Quality Engineering connects intent, risk, validation, automation, release readiness, and production learning so teams can move faster without pushing uncertainty downstream.
Hyper-Agile Testing
by Evgeny Tkachenko
Forthcoming from Apress — available for preorder on Amazon
A practical framework for quality engineering in AI-accelerated delivery.
Software creation accelerated. Confidence-building didn’t.
AI accelerates creation across product and engineering — requirements, code, tests, documentation. Release confidence can still be constrained by unclear requirements, validation that happens late, quality signals that never connect, and production feedback that arrives too slowly to act on.
Late surprises
Risk and ambiguity that surface only after most of the work is already done.
Escaped defects
Issues that reach production because validation depth didn't match real risk.
Repeated quality effort
The same test thinking and coverage re-created by different people because it was never captured as a reusable artifact.
Fragmented release confidence
Signals from requirements, testing, CI/CD, and production that never connect into one clear picture at release time.
Hyper-Agile Quality Engineering™
Hyper-Agile Quality Engineering is a risk-based operating model for modern delivery environments where teams move quickly, use AI-assisted workflows, release in smaller increments, and continuously learn from users and production.
- 01
Risk-Based Validation Depth
Validation depth changes with risk, reach, release stage, and potential impact.
- 02
Continuous Quality Signals
Confidence is built incrementally across requirements, testing, CI/CD, release readiness, and production.
- 03
Enabled Ownership
Product, Engineering, and Quality Engineering contribute to quality earlier instead of relying on a late QA handoff.
- 04
Informed Confidence
Release decisions make validated behavior, remaining uncertainty, and accepted risk visible.
Quality Knowledge Should Move With the Work
Within the Hyper-Agile Quality Engineering™ framework, the Hyper-Agile Quality Loop connects ten activities from product intent through production learning.
- Clarify intent, then
- Identify risk, then
- Generate test expectations, then
- Create reusable quality artifacts, then
- Automate what is repeatable, then
- Analyze change impact, then
- Select regression intelligently, then
- Release with informed confidence, then
- Monitor production, then
- Feed learning back into the knowledge base, loops back to Clarify intent
The activities stay connected. The depth changes with risk.
Hyper-Agile Testing
Delivering Software in an AI-Accelerated World
Evgeny Tkachenko · Apress
Forthcoming from Apress — available for preorder on Amazon
Hyper-Agile Testing follows quality from product intent through production learning. It presents a connected approach to risk-based validation, trustworthy automation and CI/CD, AI-augmented Quality Engineering, release readiness, prototypes and early-access releases, collaborative ownership, meaningful metrics, and organizational transformation.
What you’ll learn
- Apply the Hyper-Agile Quality Loop from product intent through production learning.
- Match validation depth to risk, release stage, and customer impact.
- Build trustworthy automation and CI/CD signals that support release decisions.
- Use AI responsibly for requirements review, test design and automation, change-impact analysis, release readiness, and defect triage.
Hyper-Agile Quality Engineering™ Consulting
Organizations can engage Evgeny Tkachenko through Carunel LLC to assess their software delivery and quality challenges, adapt the Hyper-Agile Quality Engineering™ framework to their operating environment, and support its implementation across engineering, product, and quality.
From Organizational Pain Points to Production Confidence
Each engagement begins with an assessment of the organization’s delivery constraints, quality risks, ownership gaps, quality signals, AI-assisted workflows, and release decision-making. Based on the findings, Evgeny works with leaders and teams to develop a practical adoption roadmap, implement the Hyper-Agile Quality Loop, and establish sustainable improvements tailored to the organization.
Engagements may include assessments, advisory and implementation support, leadership working sessions, workshops, and training.
Speaking & Conferences
Evgeny is available for conference talks, panels, workshops, podcasts, and leadership discussions on Hyper-Agile Quality Engineering and AI-accelerated software delivery.
About Evgeny Tkachenko
Evgeny Tkachenko is CEO of Carunel LLC, author of the forthcoming Apress book Hyper-Agile Testing, and originator of the Hyper-Agile Quality Engineering™ framework and the Hyper-Agile Quality Loop.