Stage 2: Discovery
Overview
Discovery is where engagements take shape. This stage supports requirement gathering, technical research, business requirements documentation, security planning, and architectural exploration. With 14 assets available, Discovery provides the broadest research toolset in the lifecycle.
When You Enter This Stage
You enter Discovery after completing Stage 1: Setup with a configured environment.
NOTE
Prerequisites: HVE Core installation complete, project repository initialized.
Available Tools
| Tool | Type | How to Invoke | Purpose |
|---|---|---|---|
| task-researcher | Agent | Select task-researcher agent | Research best practices and technical topics |
| brd-builder | Agent | Select brd-builder agent | Create business requirements documents |
| security-planner | Agent | Select security-planner agent | Generate security plans and security models |
| sssc-planner | Agent | Select sssc-planner agent | Assess supply chain security posture against OpenSSF standards |
| rai-planner | Agent | Select rai-planner agent | Assess responsible AI risks and generate RAI plans |
| gen-data-spec | Agent | Select gen-data-spec agent | Generate data specifications and schemas |
| adr-creation | Agent | Select adr-creation agent | Document architecture decisions |
| arch-diagram-builder | Agent | Select arch-diagram-builder agent | Generate architecture diagrams |
| ux-ui-designer | Agent | Select ux-ui-designer agent | Design user experience and interface concepts |
| github-backlog-manager | Agent | Select github-backlog-manager agent | Discover and triage existing GitHub issues |
| memory | Agent | Select memory agent | Store research findings for later reference |
| risk-register | Prompt | /risk-register | Identify and track project risks |
| task-research | Prompt | /task-research | Quick research queries without full agent context |
| dt-coach | Agent | Select dt-coach agent | Guide teams through Design Thinking methods for user-centered requirements discovery |
| experiment-designer | Agent | Select experiment-designer agent | Design Minimum Viable Experiments to validate unknowns before committing to implementation |
Design Thinking as Pre-Research Methodology
NOTE
Teams can invoke dt-coach during Discovery to run scope conversations (Method 1) and design research (Method 2) before engaging the task-researcher agent. Design Thinking provides structured, empathy-driven research techniques that produce validated problem statements and stakeholder maps, strengthening the foundation for subsequent technical research.
Validating Unknowns with Minimum Viable Experiments
NOTE
When Discovery surfaces unknowns across data, technology, or use cases, invoke experiment-designer to design a Minimum Viable Experiment (MVE) before committing to full implementation. The agent guides you through problem discovery, hypothesis formation, vetting criteria, and experiment planning. MVEs resolve uncertainty early (whether hypotheses are validated or invalidated) the results inform your go/no-go decisions and reduce downstream risk.
Role-Specific Guidance
TPMs lead Discovery, producing BRDs and coordinating research across disciplines. Engineers contribute technical feasibility research. Tech Leads evaluate architecture options. Security Architects drive security model analysis. Data Scientists define data requirements.
- TPM Guide
- Engineer Guide
- Tech Lead Guide
- Security Architect Guide
- Data Scientist Guide
- UX Designer Guide
UX and UI designers use Discovery-stage tools alongside dt-coach for structured user research. The dt-coach agent provides nine Design Thinking methods, including interview planning, environmental observation, and input synthesis, that complement task-researcher workflows with empathy-driven requirements gathering. See the Design Thinking documentation for method details.
Starter Prompts
Select task-researcher agent:
Research best practices for container orchestration with Kubernetes,
focusing on namespace isolation for multi-tenant environments, resource
quota configuration, and secret management approaches like external
secrets operator vs sealed secrets.
Select brd-builder agent:
Create a business requirements document for the customer onboarding portal.
Target enterprise customers with 500+ seats, with the objective of reducing
onboarding time from 2 weeks to 3 days. Include integration requirements
for existing SSO and billing systems and SOC 2 Type II compliance constraints.
Select security-planner agent:
Generate a security plan for the /api/payments endpoint in our
customer-facing REST API. Scope the plan to authentication via
OAuth 2.0 with Azure AD B2C, PCI DSS compliance for payment
tokenization, and a security model covering injection and broken
access control. Exclude infrastructure and network-level controls.
Select sssc-planner agent:
Assess this repository's supply chain security posture against the OpenSSF Scorecard
Select rai-planner agent:
Assess the responsible AI risks for this project based on the security plan
Stage Outputs and Next Stage
Discovery produces BRDs, research summaries, security plans, data specifications, architecture decision records, supply chain security assessments, and RAI assessments. Transition to Stage 3: Product Definition when the BRD is complete (handoff at docs/brds/). TPMs who have a sufficient BRD can skip directly to Stage 4: Decomposition.
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