Signal / 01
Execution integrity
Was the journey actually completed, with the required trace and tool results?
ILLUSTRATIVE TREND · NOT MEASURED
AGENTIC SDLC CONTROL PLANE/Plan · build · test · secure · release · learn
The Agentic SDLC
from plan to production.
Move beyond isolated coding agents and test bots. Connect planning, implementation, testing, security, release and operational feedback in one governed engineering workflow—with evidence behind every critical decision.
FIG. 01 / AGENTIC SDLCINTERACTIVE SCHEMATIC · SYNTHETIC SAMPLE DATA
Change → system → evidence
SCENARIO / 014 · REFERENCE FLOW
Observer view
Factory execution graph
FIG. 02
Selected capability / 02EVALUATE
Vera
Execute · Test behaviour, not just endpoints.
Combine browser and API execution with deterministic assertions and semantic evaluation of intended outcomes.
Journey evaluation selected
Sample event streamSYNTHETIC
00:04
NEXUS
Change surface mapped
Components · dependencies · journeys
00:09
VERA
Evaluation selected
Rules + semantic criteria
00:12
CHAKRA
Policy boundary identified
Approval invariant required
—
GOVERN
Awaiting verified evidence
No release verdict issued
No verdict without verified evidence.
FIG. 03 / INTERACTIVE WORKFLOW MODELSample UI only · no live execution implied
Designed around principles that travel with your stack
Tool flexibility Traceable evidence Explicit guardrails Human-governed release
01 / Configuration
Your assurance workflow, defined in code.
Make the workflow legible. Specify the stages, evaluation criteria and release controls so the process can be reviewed and repeated.
Keep policy controls explicit
Compare runs against a stable baseline
Preserve evidence behind every verdict
assurance-config
CONCEPTUAL CONFIGURATIONfactory.yaml
factory:name: shyena-assurancemode: evidence-ledworkflow:- nexus # map the system- vera # test behaviour- chakra # probe security- govern # assemble evidencerelease:require_human_approval: true
02 / Agentic SDLC coverage
Autonomous engineering across the entire lifecycle.
Coding agents are only one part of the shift. Shyena brings the workflow around them into view—from intent and implementation to verification, security, release and operational learning.
Lifecycle explorer / 06 stagesSELECT A STAGE TO INSPECT
Stage 01 / 06 · Assurance brief
Plan & design
Translate product intent, requirements and architecture into goals, constraints and measurable acceptance criteria.
Evidence and policy requirements remain explicit at every stage.
assurance-run
Illustrative console · not executable$shyena assure --stage plan-design
scopeTranslate product intent, requirements and architecture into goals, constraints and measurable acceptance criteria.
evidencerequired · traceable · reviewable
nextCode & integrate
UI CONCEPT ONLY · NO LIVE RUN OR CUSTOMER DATA
03 / Quality loop
Measurement belongs inside the workflow.
Execution integrity, deterministic assertions and semantic evaluation answer different questions. Keep the signals separate, then bring them together with policy and risk.
Signal / 02
Deterministic rules
Did exact facts, required steps and hard constraints hold?
Required stepsExplicit assertion
Policy invariantHard control
Tool resultTrace verified
SCHEMATIC CHECKLIST
Signal / 03
Semantic quality
Did the result meet the user’s intent when exact string matching is too brittle?
SYNTHETIC VISUAL · NO SCORES SHOWN
Learn from failures. Never weaken a gate just to pass.Explore governance
04 / Open at every layer
Your stack. Your models. Your controls.
Assurance should be portable across the system being tested. Keep the workflow focused on contracts, outcomes and evidence rather than tying the decision to one model or interface.
Explore the approachLAYER 04SHYENA
Assurance workflow
Stages, policies, scoring criteria and release decisions
LAYER 03YOUR CHOICE
Agent / harness
The execution path and tools used for the task
LAYER 02CONFIGURABLE
Model / evaluator
Models and evaluation methods suited to the use case
LAYER 01YOUR SYSTEM
System under test
Applications, APIs, agents, retrieval and integrations
05 / Governance
Coordinate the work. Keep control of the outcome.
An assurance control plane should show what is running, which evidence is missing and where human review is required. This is an illustrative roster, not a live agent connection.
Factory control plane
Illustrative roster · no live agentsNexus
Map changed components
Vera
Evaluate critical journeys
Chakra
Probe policy boundaries
Govern
Assemble release evidence
Release guardrail
Evidence first. Approval explicit.
A missing trace, critical policy failure or required approval should remain visible. Do not average away a hard constraint.
Execution integrity verified
Critical assertions evaluated
Policy boundaries checked
Human approval recorded
06 / Use Shyena where you work
From a single critical journey to the release workflow.
Start with the highest-risk path, connect the checks you need, and expand coverage as the system and its risks evolve.
Change review
Map a pull request or change to the affected system and tests.
Developer workflow
Make checks and evidence visible alongside engineering work.
Release review
Bring test results, policy findings and approval into one decision.
FAQ / The basics
Questions, answered.
The factory should make the process clearer—not hide what is implemented and what remains an example.
No. The broader mission is the Agentic SDLC: connect planning, coding agents, test engineering, security checks, release evidence and operational feedback into one governed engineering workflow. Nexus, Vera, Chakra and Govern provide the assurance capabilities within that lifecycle.
Start with one critical journey
Make autonomous engineering accountable—from the first plan to production.
Map the risk. Test the behaviour. Challenge the boundaries. Decide with evidence.