AUTONOMOUS SOFTWARE QUALITY ENGINEERING

AATF Autonomous Agentic SDLC

Turn every meaningful change into a risk-aware, evidence-backed delivery workflow—from change impact and test planning to execution, failure analysis and governed release decisions.

One approach for any product, system, technology or delivery stack.

Discuss an AATF assessment Explore the architecture

Risk-led testing Deterministic gates Reviewable evidence

AATF / DELIVERY CONTROL PLANE ILLUSTRATIVE

Change detectedCommit · requirement · dependencyINPUT

Impact and risk mappedComponents · journeys · risk signalsANALYSE

Tests selected and runExisting suites · generated coverageVERIFY

Evidence evaluatedResults · artifacts · policy checksASSURE

Release eligibilityDetermined by configured policy—not an LLM assertion

DESIGNED TO FIT YOUR STACK

Web & mobileAPIs & servicesData & cloudEnterprise & legacyAI & agentic systems

THE DELIVERY GAP

Quality should move at the speed of change.

Modern systems change across code, configuration, APIs, dependencies, data, prompts and infrastructure. Traditional pipelines can run checks without knowing which risks matter most, while disconnected AI tools can produce activity without reliable release evidence.

AATF is designed to connect change intelligence, specialist agents, existing engineering tools and explicit quality policy into one traceable workflow.

Test the areas a change is most likely to affect.
Reuse current tools before adding new ones.
Make failures and release criteria inspectable.

THE PRODUCT

One lifecycle. Specialist intelligence.

Coordinate quality work across the lifecycle without forcing every team onto the same language, framework or test runner.

Change intelligence

Analyse requirements, commits, pull requests, dependencies and affected components to establish what changed and what may be at risk.

Risk-based test planning

Prioritise test coverage using change scope, business criticality, dependency relationships, historical failures and defined risk policies.

Test generation and review

Draft unit, integration, API, contract, BDD, end-to-end, visual and accessibility tests from approved requirements and system behaviour.

Orchestrated execution

Select the appropriate runners and environments, execute required suites, and collect results, logs, traces, screenshots and coverage evidence.

Failure triage

Correlate failures with changes and evidence, distinguish likely product defects from test or environment issues, and present explainable next actions.

Controlled healing and recovery

Propose test updates or code fixes, validate them against regression suites, and preserve review history instead of silently masking failures.

Quality governance

Evaluate required checks with deterministic rules, explicit thresholds, evidence requirements, approvals and auditable exception handling.

Quality intelligence

Track risk coverage, flaky tests, escaped defects, execution time, failure trends and release readiness across teams and services.

END-TO-END LIFECYCLE

From change signal to release evidence.

The lifecycle is event-driven and iterative. Failures return to diagnosis and re-validation; a successful test run is evidence for a policy decision, not an automatic guarantee of safety.

Detect

Collect requirements, code diffs, configuration changes and delivery events.

Understand

Map affected components, dependencies, critical journeys and risk.

Plan

Select required suites and identify gaps in coverage.

Generate

Draft tests and review them against requirements and existing conventions.

Execute

Run checks in approved environments and collect structured artifacts.

Diagnose

Group failures, identify likely causes and propose actionable next steps.

Validate

Re-run impacted checks and verify proposed repairs without hiding defects.

Decide

Evaluate deterministic gates, approvals and exceptions; record the outcome.

REFERENCE ARCHITECTURE

Separate intelligence from execution and control.

The product architecture is modular: orchestration coordinates work, adapters connect to systems, runners execute checks and policy controls release eligibility.

Integration and discovery

Repository, work-item, build, test, observability and deployment adapters.

Change and risk intelligence

A normalized view of changes, dependencies, impacted journeys and risk priorities.

Agent orchestration

A stateful workflow coordinates specialist agents, tools, checkpoints, retries and hand-offs.

Execution fabric

Existing and purpose-built test runners execute checks in the target system's own supported environments.

Policy and evidence

Deterministic quality gates combine required checks, results, artifacts, approvals and exception records.

Delivery and feedback

CI/CD integrations consume gate outcomes; production signals inform subsequent risk and regression planning.

Architecture diagrams will be added in separately reviewed stages.

The approved diagram set covers the end-to-end SDLC, agent orchestration, technology-independent integration, and CI/CD release gates. This first page release establishes the product narrative and architecture layers; the detailed diagrams will follow as individual reviewable changes.

TECHNOLOGY-INDEPENDENT BY DESIGN

Connect to the system you already have.

AATF should adapt to your technology instead of requiring a rewrite or a single prescribed toolchain.

Languages and frameworks

TypeScript, JavaScript, Python, Java, .NET, Go, mobile frameworks and other supported stacks.

Delivery platforms

Git-based repositories, CI servers, build systems, deployment workflows and release management tools.

System types

Web applications, mobile apps, APIs, microservices, data pipelines, cloud platforms, legacy and embedded systems.

Integration patterns

APIs, command-line runners, test reports, event hooks, web interfaces and custom adapters.

Compatibility is established through an integration assessment. The availability of a particular connector or runner depends on access, system interfaces, security controls and test-environment support.

TESTING AND VERIFICATION

Use the right checks for the risk.

AATF is intended to orchestrate existing checks and extend coverage where needed. No single test type can establish overall product quality.

Unit and component

Validate isolated logic and UI components.

Integration and contract

Verify service boundaries, schemas, events and dependencies.

API and data

Check endpoints, business rules, permissions and data transformations.

BDD and acceptance

Connect readable business scenarios to executable acceptance criteria.

End-to-end and UI

Exercise user journeys across real application boundaries.

Visual and accessibility

Detect rendering regressions and accessibility barriers.

Performance and resilience

Evaluate latency, load behaviour, timeouts and recovery where the environment supports it.

Security and AI quality

Add security checks, adversarial testing and model/agent evaluation when relevant to the system.

SPECIALIST AGENTS

Focused agents. One governed workflow.

Agent responsibilities can be combined or separated based on system scale, risk and operational cost. The target design starts with a small set of clear roles.

Change Intelligence

Summarises diffs, dependencies, affected components and change risk.

Test Engineering

Plans coverage, drafts tests and checks generated tests against requirements.

Test Execution

Dispatches suites to approved runners and gathers structured results.

Triage and Healing

Correlates failures and proposes repairs for controlled re-validation.

Quality Governance

Assembles evidence and evaluates policy-defined release criteria.

GOVERNED AUTONOMY

Autonomy with clear boundaries.

AI can accelerate engineering work. Deterministic controls, evidence and permissions must remain the authority for high-impact decisions.

Agents cannot declare a required check passed without its configured evidence.

Release rules are deterministic, versioned and independently inspectable.

Production changes, merges and deployments follow repository permissions and configured approval policies.

Self-healing must not silently weaken assertions, remove coverage or convert a real defect into a pass.

Every run records its inputs, selected tests, outcomes, artifacts, policy evaluation and human decisions.

MEASURE WHAT IMPROVES

Evidence over vanity scores.

Metrics should help teams find bottlenecks and risk, not imply that one composite score can guarantee quality.

Change-risk coverage

Share of identified high-risk areas covered by required checks.

Feedback lead time

Time from change submission to actionable quality evidence.

Defect escape rate

Defects discovered after release, interpreted with severity and context.

Test reliability

Flakiness, retry rates and the proportion of actionable failures.

Repair validation

Share of proposed fixes that pass independent regression checks.

Gate traceability

Releases with recorded results, policy evaluations and approvals.

FREQUENTLY ASKED QUESTIONS

Designed for your delivery reality.

Start with the system, toolchain and release constraints you need to support.

Discuss your use case

What does AATF stand for?

AATF is the product name for Autonomous Agentic SDLC: a governed platform concept for coordinating software lifecycle quality activities with specialist agents, deterministic checks and reviewable evidence.

Is AATF only for AI applications?

No. Its intended scope includes conventional software, APIs, mobile applications, data platforms, cloud services, enterprise systems, legacy applications and AI-enabled products. AI-specific evaluation is one optional capability, not a prerequisite.

Does every technology need a native AATF agent?

No. The architecture separates orchestration from technology-specific adapters and test runners. Integrations can use existing CLI tools, APIs, CI jobs, test reports or custom adapters where the target system permits them.

Can it work with our existing test suites?

The intended approach is to orchestrate and reuse existing suites where their interfaces and reports are accessible, then add coverage where gaps are identified. Exact compatibility must be validated during implementation.

Can an agent deploy to production by itself?

Only if an organisation explicitly configures and authorises that workflow. The recommended default is policy-controlled release eligibility, with human approval for sensitive or high-impact actions.

Does self-healing mean tests can change themselves?

An agent may propose a repair and run validation. Changes to assertions, expected behaviour or coverage should be reviewed according to policy; healing must not conceal product defects.

Is the complete platform already available?

This page describes the proposed AATF product and target architecture. Individual connectors, orchestration workflows, test runners and governance capabilities must be implemented and validated before they can be represented as available features.

START WITH YOUR SYSTEM

Make your next change easier to verify.

Discuss your architecture, current test stack, delivery process and the quality risks you need to control. We can define a realistic first implementation scope together.

Discuss AATF