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Master Eric, Fast Product Development (VCM-C)

Intro​

Strap in. You are here for evidence, momentum, and outcomes that can survive scrutiny. I am your Master guide. I move fast, but I only move on proof. Sage is the case study threading this manual, and Dani is the user signal that keeps every step honest.

Hyperboost Formula​

What is the Hyperboost Formula?​

Hyperboost is the operating system I use to move from intent to validated action. It is the curated fusion of proven frameworks, sequenced in the exact order and applied in the right amount.

The DNA: Build-Measure-Learn—Relentlessly​

Every step is an experiment with a hypothesis, a signal, and a decision. If we cannot measure reality, we do not move forward.

Integration of Methods: Lean Startup, Empathy, and AI​

  • Lean Startup: Ruthless validation before investment.
  • Customer Empathy: Real pain beats internal opinions every time.
  • AI Acceleration: Machines handle grunt work so humans decide with clarity.

Why Does the Hyperboost Formula Matter?​

Because velocity without proof is just fast failure. Hyperboost forces evidence into every step so risk shrinks as speed increases.

Anatomy of the Hyperboost Journey​

This is a stepwise engine where each output becomes the next input. I do not skip gates; I compress ambiguity until the next decision is obvious.

Core Principles Guiding Every Step​

  • Evidence over ego: proof beats preference.
  • Traceability: every artifact links to a decision.
  • Velocity with control: fast, but never blind.
  • Autonomy ready: outputs must be executable without context loss.
  • Ruthless clarity: ambiguity is a defect, not a feature.

Process Overview​

  • 00: Idea Gathering
  • 01: Find Your Product/Business Idea
  • 02: Check if Idea is Worth It (POA)
  • 03: OKRs, Target Region & Profile Setup
  • 04: Target Niche & Dream Customer (HXC/ICP)
  • 05: Customer Journey (JTBD & Job Map)
  • 06: Customer Pain/Gain Analysis (DOS)
  • 07: How Users Adopt, Engage & Share (Consumption Chain/PLG)
  • 08: Product Roadmaps (MVP ODI Roadmap)
  • 09: Solution Opportunities (OST)
  • 10: Ideate Product Features
  • 11: Product Reqs Document (PRD)
  • 12: Track What Matters (Value Tree & Metrics)
  • 13: Organize Your Product Experience (Info Architecture)
  • 14: User Experience Flows (UX)
  • 15: User-Interface Design (Design System & Component Library)
  • 16: Technical Architecture Design
  • 17: Product Reqs Prompt (PRP)
  • 18: Gen Tasks for Professional AI Coders (EPIC & Task Breakdown)
  • 19: Setup Prompts for Professional AI Coders
  • 20: Build Prompts for Professional AI Coders
  • 21: AI Coder Build Manual
  • 22: WF Completion & Next Steps

Phase 1: Customer & Problem Discovery​

This phase compresses ambiguity so the next move is defensible and fast.

Step 00: Idea Gathering​

Intro​

This step turns idea gathering into a decision that can survive contact with reality. Sage uses this moment to translate ambition into a concrete move. Dani is the signal that keeps the outcome grounded in real user behavior.

Product Concept​

I apply Divergent Ideation & Hypothesis Capture. We collect raw ideas without judgment so we can frame the right hypothesis before validation. It belongs here because this step must create a defensible outcome, not activity.

This step is complete only when the outcome is achieved: User/ctx: idea/new/existing/continue; autodetect ctx; route→min effort; ready next step.

Actions​

  • I translate the intent of Idea Gathering into clear, testable criteria.
  • I apply Divergent Ideation & Hypothesis Capture to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a1_customer_discovery/my_idea: User prod/svc/biz idea, OR niche to help, OR ask Master support finding winning idea
  • mm_initiative: init&proj ctx: name&strategic attrs

Step 01: Find Your Product/Business Idea​

Intro​

Here I collapse ambiguity around find your product/business idea so every next move has proof behind it. Sage relies on this step to remove blind spots before momentum accelerates. Dani is the proof check that stops us from building for ourselves.

Product Concept​

I apply Market Scanning & Opportunity Scoring. We scan demand signals and score opportunities so the best hypothesis is selected, not guessed. It belongs here because this step must create a defensible outcome, not activity.

I layer Solution Ideation & Synthesis to reinforce the decision logic, so the result is repeatable and evidence-backed. Structured ideation turns validated outcomes into coherent solution options.

This step is complete only when the outcome is achieved: User: discovered or refined compelling product/feature idea w/ clear market potential OR explored alternative solution angles for existing hypothesis.

Actions​

  • I translate the intent of Find Your Product/Business Idea into clear, testable criteria.
  • I apply Market Scanning & Opportunity Scoring to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a1_customer_discovery/01_product_ideas: Top 20 biz/feature ideas w/ disruption potential OR alternative angles same problem
  • a1_customer_discovery/my_idea: User-selected prod/feature opp hypothesis w/ rationale

Step 02: Check if Idea is Worth It (POA)​

Intro​

This is where check if idea is worth it (poa) becomes a defensible call instead of a guess. Sage treats this step as the guardrail that keeps the journey honest. Dani is the reality anchor that keeps this step from drifting into theory.

Product Concept​

I apply Solution Ideation & Synthesis. Structured ideation turns validated outcomes into coherent solution options. It belongs here because this step must create a defensible outcome, not activity.

I layer Product Opportunity Assessment to reinforce the decision logic, so the result is repeatable and evidence-backed. POA stress-tests value, usability, feasibility, and viability before we invest.

This step is complete only when the outcome is achieved: Validated high-potential product/feature opportunity aligned w/ goals&product context OR identified alternative paths to pursue same vision.

Actions​

  • I translate the intent of Check if Idea is Worth It (POA) into clear, testable criteria.
  • I apply Solution Ideation & Synthesis to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a1_customer_discovery/02_opportunity_assessment_poa: prod opp Assessment w/ strategic analysis + loving mentor guidance
  • mm_initial_hypothesis_alts: Hypothesis context alternative sol angles exploration (Option 2)

Step 03: OKRs, Target Region & Profile Setup​

Intro​

This step turns okrs, target region & profile setup into a decision that can survive contact with reality. Sage uses this moment to translate ambition into a concrete move. Dani is the signal that keeps the outcome grounded in real user behavior.

Product Concept​

I apply OKR design. OKRs translate ambition into measurable outcomes that prevent drift. It belongs here because this step must create a defensible outcome, not activity.

I layer Agentic Build Operations to reinforce the decision logic, so the result is repeatable and evidence-backed. Operational prompts ensure coders execute with context and quality gates.

This step is complete only when the outcome is achieved: User has defined clear OKRs, target research region and profile, ready to begin systematic product dev process.

Actions​

  • I translate the intent of OKRs, Target Region & Profile Setup into clear, testable criteria.
  • I apply OKR design to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • No explicit deliverables are emitted at this step.

Step 04: Target Niche & Dream Customer (HXC/ICP)​

Intro​

Here I collapse ambiguity around target niche & dream customer (hxc/icp) so every next move has proof behind it. Sage relies on this step to remove blind spots before momentum accelerates. Dani is the proof check that stops us from building for ourselves.

Product Concept​

I apply OKR design. OKRs translate ambition into measurable outcomes that prevent drift. It belongs here because this step must create a defensible outcome, not activity.

I layer Persona & Empathy Modeling to reinforce the decision logic, so the result is repeatable and evidence-backed. Persona and empathy modeling define who we must delight first and why.

This step is complete only when the outcome is achieved: User: validated target niche(s) per audience (single/per platform side) w/ highest OKR/PMF potential, confirmed HXC Persona(s) as Job Executor(s) w/ full psychological/behavioral analysis (Empathy Map per audience), biz solutions include optimal ICP, ODIR tree initialized w/ audience branch(es).

Actions​

  • I translate the intent of Target Niche & Dream Customer (HXC/ICP) into clear, testable criteria.
  • I apply OKR design to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • customer_discovery/04a_/niche_analysis: Top 3 niches per audience side for initiative success
  • a1_customer_discovery/04b_selected_niche: Selected niche(s) per audience
  • a1_customer_discovery/04c_ideal_user_hxc: HXC(s) per audience
  • a1_customer_discovery/04d_ideal_company_icp: If biz sol,rec the most opportune ICP (Ideal cust Profile),where the selected HXC persona works for,increasing the chances of biz success
  • mm_odir_yaml: ODIR tree initialization w/ audience(s),niche(s),HXC(s). JTBD/JMS/DOS added in subsequent steps

Phase 2: Strategy & Solution Design​

This phase compresses ambiguity so the next move is defensible and fast.

Step 05: Customer Journey (JTBD & Job Map)​

Intro​

This is where customer journey (jtbd & job map) becomes a defensible call instead of a guess. Sage treats this step as the guardrail that keeps the journey honest. Dani is the reality anchor that keeps this step from drifting into theory.

Product Concept​

I apply Jobs-to-be-Done & Job Map. JTBD clarifies the true user job, and the Job Map structures it into steps we can improve. It belongs here because this step must create a defensible outcome, not activity.

I layer Persona & Empathy Modeling to reinforce the decision logic, so the result is repeatable and evidence-backed. Persona and empathy modeling define who we must delight first and why.

This step is complete only when the outcome is achieved: User: defined JTBD statement(s) w/ 3 dimensions (Functional, Personal, Social) per audience + Job Map Steps (6-8 JMS) per audience, ODIR tree populated w/ JTBD + JMS branches.

Actions​

  • I translate the intent of Customer Journey (JTBD & Job Map) into clear, testable criteria.
  • I apply Jobs-to-be-Done & Job Map to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a1_customer_discovery/05_solution_journey_jtbd: JTBD statement(s) + Job Map per audience
  • mm_odir_yaml: ODIR tree update: add JTBD + JMS per audience

Step 06: Customer Pain/Gain Analysis (DOS)​

Intro​

This step turns customer pain/gain analysis (dos) into a decision that can survive contact with reality. Sage uses this moment to translate ambition into a concrete move. Dani is the signal that keeps the outcome grounded in real user behavior.

Product Concept​

I apply OKR design. OKRs translate ambition into measurable outcomes that prevent drift. It belongs here because this step must create a defensible outcome, not activity.

I layer Jobs-to-be-Done & Job Map to reinforce the decision logic, so the result is repeatable and evidence-backed. JTBD clarifies the true user job, and the Job Map structures it into steps we can improve.

I also use Desired Outcome Statements because it tightens the feedback loop and prevents drift. DOS expresses success in the user's language so we can prioritize based on outcome gaps.

This step is complete only when the outcome is achieved: User receives detailed Customer DOS evaluation across Job Map Steps, extracted from pain/gain research, ranked by OKR impact + Opp Score to guide ODI Roadmap for product dev priorities.

Actions​

  • I translate the intent of Customer Pain/Gain Analysis (DOS) into clear, testable criteria.
  • I apply OKR design to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • mm_odir_yaml: Complete ODIR tree w/ complete audience branch down to all DOS nodes
  • a2_solution_discovery/{{mm_session_persona}}/06_user_needs_dos: PM artifact: Complete JTBD journey mapping w/ complete custs' Desired Outcomes Statements (DOS) analysis per Job Map Step (JMS)

Step 07: How Users Adopt, Engage & Share (Consumption Chain/PLG)​

Intro​

Here I collapse ambiguity around how users adopt, engage & share (consumption chain/plg) so every next move has proof behind it. Sage relies on this step to remove blind spots before momentum accelerates. Dani is the proof check that stops us from building for ourselves.

Product Concept​

I apply Jobs-to-be-Done & Job Map. JTBD clarifies the true user job, and the Job Map structures it into steps we can improve. It belongs here because this step must create a defensible outcome, not activity.

I layer Desired Outcome Statements to reinforce the decision logic, so the result is repeatable and evidence-backed. DOS expresses success in the user's language so we can prioritize based on outcome gaps.

I also use Product-Led Growth & Consumption Chain because it tightens the feedback loop and prevents drift. The consumption chain maps adoption moments so growth and retention are designed, not hoped for.

This step is complete only when the outcome is achieved: User: full catalog of DOS across all seven consumption jobs (Acquire|Activate|Onboard|Support|Engage|Expand|Advocate) w/ Job Map Steps, opp scores, benchmarks serving as strategic foundation for developing PLG strategies, habit-forming mechanisms, automation frameworks, viral loops, self-service experiences, AHA moments, retention systems.

Actions​

  • I translate the intent of How Users Adopt, Engage & Share (Consumption Chain/PLG) into clear, testable criteria.
  • I apply Jobs-to-be-Done & Job Map to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a2_solution_discovery/{{mm_session_persona}}/07a_growth_journey_plg: PM artifact: Consumption chain jobs sol persona/ICP w/ Job Map Steps PLG strat
  • mm_odir_yaml: Complete ODIR tree w/ added consumption outcomes branch PLG strat
  • a2_solution_discovery/{{mm_session_persona}}/07b_product_led_growth_dos: PM artifact: Consumption DOS statements PLG strat w/ success metrics
  • mm_odir_yaml: Complete ODIR tree w/ consumption outcomes branch PLG strat

Step 08: Product Roadmaps (MVP ODI Roadmap)​

Intro​

This is where product roadmaps (mvp odi roadmap) becomes a defensible call instead of a guess. Sage treats this step as the guardrail that keeps the journey honest. Dani is the reality anchor that keeps this step from drifting into theory.

Product Concept​

I apply Desired Outcome Statements. DOS expresses success in the user's language so we can prioritize based on outcome gaps. It belongs here because this step must create a defensible outcome, not activity.

I layer Product-Led Growth & Consumption Chain to reinforce the decision logic, so the result is repeatable and evidence-backed. The consumption chain maps adoption moments so growth and retention are designed, not hoped for.

I also use Outcome-Driven Roadmapping because it tightens the feedback loop and prevents drift. ODI roadmaps prioritize outcomes first so sequencing optimizes value and learning.

This step is complete only when the outcome is achieved: User selected highest-potential roadmap for solution (w/ appropriate DOS), w/ highest probability to rapidly reach PMF + start accelerated PLG loop w/ strong end-user engagement + satisfaction.

Actions​

  • I translate the intent of Product Roadmaps (MVP ODI Roadmap) into clear, testable criteria.
  • I apply Desired Outcome Statements to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a2_solution_discovery/{{mm_session_persona}}/08a_competitive_analysis: Competitive intelligence analysis quantifying market gaps&competitor positioning weaknesses
  • a2_solution_discovery/{{mm_session_persona}}/08b_outcomes_roadmap_odir: MVP roadmap w/ detailed cluster breakdown + DOS mapping

Step 09: Solution Opportunities (OST)​

Intro​

This step turns solution opportunities (ost) into a decision that can survive contact with reality. Sage uses this moment to translate ambition into a concrete move. Dani is the signal that keeps the outcome grounded in real user behavior.

Product Concept​

I apply Solution Ideation & Synthesis. Structured ideation turns validated outcomes into coherent solution options. It belongs here because this step must create a defensible outcome, not activity.

I layer Desired Outcome Statements to reinforce the decision logic, so the result is repeatable and evidence-backed. DOS expresses success in the user's language so we can prioritize based on outcome gaps.

I also use Outcome-Driven Roadmapping because it tightens the feedback loop and prevents drift. ODI roadmaps prioritize outcomes first so sequencing optimizes value and learning.

This step is complete only when the outcome is achieved: User validated OST trees for all roadmap DOS w/ sequential opp leaf order optimized for ideation comprehension + UX flow.

Actions​

  • I translate the intent of Solution Opportunities (OST) into clear, testable criteria.
  • I apply Solution Ideation & Synthesis to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • mm_solutions_yaml: Complete OST trees each DOS w/ multi-level opp nodes (DOS→OpportunityNode→OpportunityLeaf) in selected sol roadmap
  • a2_solution_discovery/{{mm_session_persona}}/{{mm_session_roadmap}}/09a_solution_options_ost: PM artifact: Sequential ideation order opp leaves organized by JMS progression + UX flow
  • a2_solution_discovery/{{mm_session_persona}}/{{mm_session_roadmap}}/09b_tree_visual_ost: Interactive 3D force-graph: OST hierarchy w/OKR→Journey→JMS→Opps; node sizing+colors+particle flow showing OST structure

Step 10: Ideate Product Features​

Intro​

Here I collapse ambiguity around ideate product features so every next move has proof behind it. Sage relies on this step to remove blind spots before momentum accelerates. Dani is the proof check that stops us from building for ourselves.

Product Concept​

I apply Solution Ideation & Synthesis. Structured ideation turns validated outcomes into coherent solution options. It belongs here because this step must create a defensible outcome, not activity.

I layer User Experience Flow Design to reinforce the decision logic, so the result is repeatable and evidence-backed. UX flows map the critical path and eliminate dead ends.

This step is complete only when the outcome is achieved: User: cohesive product structure w/ integrated features that work together as a unified UX system.

Actions​

  • I translate the intent of Ideate Product Features into clear, testable criteria.
  • I apply Solution Ideation & Synthesis to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a2_solution_discovery/{{mm_session_persona}}/{{mm_session_roadmap}}/10a_[%feat_id%, hint='0X (seq num) + (a/b/c) (version)']_feat_[%gen.words(max:3, 'unique solution name')%]: Approved OST leaf sol w/ complete impl specs + job story analysis agentic coder
  • a2_solution_discovery/{{mm_session_persona}}/{{mm_session_roadmap}}/10b_product_scorecard: Iterative consolidated list of approved features w/pointers to their vars
  • a2_solution_discovery/{{mm_session_persona}}/{{mm_session_roadmap}}/10c_product_brief: Complete ideation rounds report w/ all opp leaf sols + Solution synthesis

Phase 3: Build Readiness​

This phase compresses ambiguity so the next move is defensible and fast.

Step 11: Product Reqs Document (PRD)​

Intro​

This is where product reqs document (prd) becomes a defensible call instead of a guess. Sage treats this step as the guardrail that keeps the journey honest. Dani is the reality anchor that keeps this step from drifting into theory.

Product Concept​

I apply Product Requirements Document. A PRD makes the why/what explicit so execution stays aligned. It belongs here because this step must create a defensible outcome, not activity.

I layer Agentic Build Operations to reinforce the decision logic, so the result is repeatable and evidence-backed. Operational prompts ensure coders execute with context and quality gates.

This step is complete only when the outcome is achieved: User: full SV-grade Product Reqs Document designed for autonomous implementation by agentic coder platform, creating professional product w/o additional docs or human supervision , also has functional reqs, business context, strategic foundation enabling designers/engineers to translate WHY/WHAT→HOW.

Actions​

  • I translate the intent of Product Reqs Document (PRD) into clear, testable criteria.
  • I apply Product Requirements Document to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/11_product_reqs_doc_prd: Strategic PM-level PRD w/ biz case, market context, high-level reqs for stakeholders

Step 12: Track What Matters (Value Tree & Metrics)​

Intro​

This step turns track what matters (value tree & metrics) into a decision that can survive contact with reality. Sage uses this moment to translate ambition into a concrete move. Dani is the signal that keeps the outcome grounded in real user behavior.

Product Concept​

I apply OKR design. OKRs translate ambition into measurable outcomes that prevent drift. It belongs here because this step must create a defensible outcome, not activity.

I layer Outcome-Driven Roadmapping to reinforce the decision logic, so the result is repeatable and evidence-backed. ODI roadmaps prioritize outcomes first so sequencing optimizes value and learning.

I also use Value Tree & Metrics because it tightens the feedback loop and prevents drift. Value trees connect outcomes to measurable signals and guide prioritization.

This step is complete only when the outcome is achieved: User: full metrics hierarchy w/ weighted priorities, NSM w/ secondary OKR metrics, impl signals for strategic roadmap decision-making + agentic coder dev.

Actions​

  • I translate the intent of Track What Matters (Value Tree & Metrics) into clear, testable criteria.
  • I apply OKR design to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • mm_solutions_yaml: Updated OST w/ complete metrics hierarchy,global weights,NSM secondary metrics integration
  • a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/12b_metrics_vtree: PM artifact: Complete metrics hierarchy + technical impl fmwk agentic coder dev

Step 13: Organize Your Product Experience (Info Architecture)​

Intro​

Here I collapse ambiguity around organize your product experience (info architecture) so every next move has proof behind it. Sage relies on this step to remove blind spots before momentum accelerates. Dani is the proof check that stops us from building for ourselves.

Product Concept​

I apply Information Architecture. IA structures content and navigation to reduce cognitive friction. It belongs here because this step must create a defensible outcome, not activity.

I layer Technical Architecture Design to reinforce the decision logic, so the result is repeatable and evidence-backed. Architecture decisions keep feasibility, performance, and scalability honest.

I also use Agentic Build Operations because it tightens the feedback loop and prevents drift. Operational prompts ensure coders execute with context and quality gates.

This step is complete only when the outcome is achieved: User: intelligent IA optimized for solution end-users + implementable by agentic coders matching creator proficiency, w/ tier-appropriate nav, content org, technical specs.

Actions​

  • I translate the intent of Organize Your Product Experience (Info Architecture) into clear, testable criteria.
  • I apply Information Architecture to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/13_navigation_ia: PD artifact: Complete IA foundation w/ nav,technical arch,impl specs entire roadmap

Step 14: User Experience Flows (UX)​

Intro​

This is where user experience flows (ux) becomes a defensible call instead of a guess. Sage treats this step as the guardrail that keeps the journey honest. Dani is the reality anchor that keeps this step from drifting into theory.

Product Concept​

I apply Solution Ideation & Synthesis. Structured ideation turns validated outcomes into coherent solution options. It belongs here because this step must create a defensible outcome, not activity.

I layer User Experience Flow Design to reinforce the decision logic, so the result is repeatable and evidence-backed. UX flows map the critical path and eliminate dead ends.

I also use Agentic Build Operations because it tightens the feedback loop and prevents drift. Operational prompts ensure coders execute with context and quality gates.

This step is complete only when the outcome is achieved: User: UX flows per feature w/ emotional journey orchestration + Hook loops + AHA moments, implementable by vibe coders.

Actions​

  • I translate the intent of User Experience Flows (UX) into clear, testable criteria.
  • I apply Solution Ideation & Synthesis to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/14_[%feat_id%]_flow_[%unique_feat_name%]: UX Flow for feature: emotional journey + Hook loops + AHA moments + implementable specs

Step 15: User-Interface Design (Design System & Component Library)​

Intro​

This step turns user-interface design (design system & component library) into a decision that can survive contact with reality. Sage uses this moment to translate ambition into a concrete move. Dani is the signal that keeps the outcome grounded in real user behavior.

Product Concept​

I apply UI System & Visual Design. A UI system enforces consistency, accessibility, and velocity. It belongs here because this step must create a defensible outcome, not activity.

This step is complete only when the outcome is achieved: User: full design system w/ component specs ready for implementation.

Actions​

  • I translate the intent of User-Interface Design (Design System & Component Library) into clear, testable criteria.
  • I apply UI System & Visual Design to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/15a_design_system: PD artifact: Complete design system foundation w/ atomic components,design tokens,accessibility specs entire roadmap
  • a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/15b_[%feat_id%].v[YY]_ui_[%gen.words(max:3, 'ui_unique_name')%]: HTML|HMTL+SVG wireframe version {{version_number}} for UI interface (screen/dialog/etc) extracted from feat+IA+ds+flow

Step 16: Technical Architecture Design​

Intro​

Here I collapse ambiguity around technical architecture design so every next move has proof behind it. Sage relies on this step to remove blind spots before momentum accelerates. Dani is the proof check that stops us from building for ourselves.

Product Concept​

I apply Technical Architecture Design. Architecture decisions keep feasibility, performance, and scalability honest. It belongs here because this step must create a defensible outcome, not activity.

This step is complete only when the outcome is achieved: User: robust technical architecture w/ detailed system design ready for implementation.

Actions​

  • I translate the intent of Technical Architecture Design into clear, testable criteria.
  • I apply Technical Architecture Design to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/16_technical_design: Technical arch deliverables

Phase 4: Execution & Handoff​

This phase compresses ambiguity so the next move is defensible and fast.

Step 17: Product Reqs Prompt (PRP)​

Intro​

This is where product reqs prompt (prp) becomes a defensible call instead of a guess. Sage treats this step as the guardrail that keeps the journey honest. Dani is the reality anchor that keeps this step from drifting into theory.

Product Concept​

I apply Solution Ideation & Synthesis. Structured ideation turns validated outcomes into coherent solution options. It belongs here because this step must create a defensible outcome, not activity.

I layer Product Requirements Prompt to reinforce the decision logic, so the result is repeatable and evidence-backed. A PRP is structured input that drives consistent build outputs from agentic coders.

I also use User Experience Flow Design because it tightens the feedback loop and prevents drift. UX flows map the critical path and eliminate dead ends.

This step is complete only when the outcome is achieved: User: Self-contained PRPs per feature for UI/UX design refinement + concept demo - Figma (NO CODE) OR AI Builders (WITH MOCKS).

Actions​

  • I translate the intent of Product Reqs Prompt (PRP) into clear, testable criteria.
  • I apply Solution Ideation & Synthesis to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/17_[%feat_id%]_prp_ch:figma|{{prp_platf_slug}}_[%unique_feat_name%]: Self-contained PRP: navigable prototype specs embedded

Step 18: Gen Tasks for Professional AI Coders (EPIC & Task Breakdown)​

Intro​

This step turns gen tasks for professional ai coders (epic & task breakdown) into a decision that can survive contact with reality. Sage uses this moment to translate ambition into a concrete move. Dani is the signal that keeps the outcome grounded in real user behavior.

Product Concept​

I apply Epic & Task Breakdown. Decomposition enables parallel execution and reduces ambiguity. It belongs here because this step must create a defensible outcome, not activity.

I layer Agentic Build Operations to reinforce the decision logic, so the result is repeatable and evidence-backed. Operational prompts ensure coders execute with context and quality gates.

This step is complete only when the outcome is achieved: User: full EPIC analysis w/ intelligent task breakdown optimized for modern agentic coder execution + sequential implementation.

Actions​

  • I translate the intent of Gen Tasks for Professional AI Coders (EPIC & Task Breakdown) into clear, testable criteria.
  • I apply Epic & Task Breakdown to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a4_product_delivery/{{mm_session_persona}}/{{mm_session_roadmap}}/18_delivery_plan_prompt: EPIC+task plan: seq, all src(product_scorecard,product_brief,product_reqs_doc_prd,feat,prp,design_system,mm_solutions_yaml,). For agentic AI coders.

Step 19: Setup Prompts for Professional AI Coders​

Intro​

Here I collapse ambiguity around setup prompts for professional ai coders so every next move has proof behind it. Sage relies on this step to remove blind spots before momentum accelerates. Dani is the proof check that stops us from building for ourselves.

Product Concept​

I apply Agentic Build Operations. Operational prompts ensure coders execute with context and quality gates. It belongs here because this step must create a defensible outcome, not activity.

This step is complete only when the outcome is achieved: User: platform-specific setup prompts ready for agentic coder execution.

Actions​

  • I translate the intent of Setup Prompts for Professional AI Coders into clear, testable criteria.
  • I apply Agentic Build Operations to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a4_product_delivery/{{mm_session_persona}}/{{mm_session_roadmap}}/19_setup_[%get.context('current_outer.prompt_file_name')%]: Platform-specific setup prompt individual setup task

Step 20: Build Prompts for Professional AI Coders​

Intro​

This is where build prompts for professional ai coders becomes a defensible call instead of a guess. Sage treats this step as the guardrail that keeps the journey honest. Dani is the reality anchor that keeps this step from drifting into theory.

Product Concept​

I apply UI System & Visual Design. A UI system enforces consistency, accessibility, and velocity. It belongs here because this step must create a defensible outcome, not activity.

I layer Agentic Build Operations to reinforce the decision logic, so the result is repeatable and evidence-backed. Operational prompts ensure coders execute with context and quality gates.

This step is complete only when the outcome is achieved: User: platform-specific build prompts ready for agentic coder execution.

Actions​

  • I translate the intent of Build Prompts for Professional AI Coders into clear, testable criteria.
  • I apply UI System & Visual Design to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a4_product_delivery/{{mm_session_persona}}/{{mm_session_roadmap}}/20_build_{{current_outer.task_id}}_{{current_outer.epic_id}}_[%get.context('current_outer.prompt_file_name')%]: Platform-specific build prompt individual dev task

Step 21: AI Coder Build Manual​

Intro​

This step turns ai coder build manual into a decision that can survive contact with reality. Sage uses this moment to translate ambition into a concrete move. Dani is the signal that keeps the outcome grounded in real user behavior.

Product Concept​

I apply UI System & Visual Design. A UI system enforces consistency, accessibility, and velocity. It belongs here because this step must create a defensible outcome, not activity.

I layer Agentic Build Operations to reinforce the decision logic, so the result is repeatable and evidence-backed. Operational prompts ensure coders execute with context and quality gates.

This step is complete only when the outcome is achieved: User: has a manual to guide them how to operate the AI Coders with the setup/build prompts.

Actions​

  • I translate the intent of AI Coder Build Manual into clear, testable criteria.
  • I apply UI System & Visual Design to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a4_product_delivery/{{mm_session_persona}}/{{mm_session_roadmap}}/21_my_build_manual: Agentic coder operations manual

Step 22: WF Completion & Next Steps​

Intro​

Here I collapse ambiguity around wf completion & next steps so every next move has proof behind it. Sage relies on this step to remove blind spots before momentum accelerates. Dani is the proof check that stops us from building for ourselves.

Product Concept​

I apply UI System & Visual Design. A UI system enforces consistency, accessibility, and velocity. It belongs here because this step must create a defensible outcome, not activity.

I layer Agentic Build Operations to reinforce the decision logic, so the result is repeatable and evidence-backed. Operational prompts ensure coders execute with context and quality gates.

I also use Business Model Canvas because it tightens the feedback loop and prevents drift. BMC aligns revenue logic and market fit before scaling.

This step is complete only when the outcome is achieved: User: celebrated all achievements with clear understanding of next phase; immediate next engineering step: BUILD in AI Coder IDE; PM/PD & business team: proceed to Business Strategy Master.

Actions​

  • I translate the intent of WF Completion & Next Steps into clear, testable criteria.
  • I apply UI System & Visual Design to generate the core artifact for this decision.
  • I pressure-test the result against real constraints and user evidence.
  • I document the decision trail so downstream steps stay aligned.

Deliverables​

  • a5_conclusion/22a_completion_summary: WF completion celebration&next steps
  • a5_conclusion/22b_ai_coder_time_estimate: Estimated timeline based on AI Coder prompt execution timings (10x speed)

Conclusion​

We end with a handoff-ready body of evidence and artifacts you can execute without guesswork. If Sage can act with confidence and Dani would still trust the outcome, the system did its job.