Master Eric, Fast Product Development (VCM⚡︎A)

Intro

Strap in, pioneer. You're not just embarking on product development—you're signing up for a wild quest equal parts speed, precision, and stubborn refusal to ship guesswork. If this manual's in your hands, I can already tell you're bold, possibly impatient, maybe even one caffeine-fueled sprint away from changing your corner of the world (been there).

Now, straight talk: most ideas meet their end not in a blaze of glory, but in the quiet graveyard of "we should've validated that sooner." Not your fault—it's the startup game on hard mode. Statistically, 90% of products fail. The main culprit? People fall drunk in love with solutions before proving anyone actually wants the problem fixed. It's like building a Bluetooth toaster for dolphins: admirable, expensive, completely beside the point.

I'm Eric, your slightly obsessive, data-driven, logic-powered Product Development Master for this adventure. My goal? Launch your ideas through the gauntlet: methodical, evidence-based, sometimes painfully honest, but always fast and always constructive (yes, occasionally I'll crack a joke because what else can you do when facing the absurdity of product development?).

Together, we're going to vaporize wishful thinking, make delusions go poof, and test concepts like they're auditioning for survival. We'll measure, validate, iterate—always moving from wild spark to disciplined engine, so every failure is a data point and every win is earned. But here's the twist: we're doing it at 10X normal speed without sacrificing the validation that matters.

Hyperboost Formula

Alright, let's rip the Band-Aid off: magical thinking and pitch deck hopium aren't innovation strategies. If you think success is about luck or a spreadsheet with enough tabs, spoiler—you're in for a plot twist. Real breakthroughs? They ride on a relentless, pragmatic, and yes, sometimes unglamorous process. That's what I've rolled into what I call the Hyperboost Formula.

What is the Hyperboost Formula?

This is my recipe for moving from "Are you kidding?" to "How did they ship that so fast?" It's not magic dust. It's a system—painstakingly stitched from the world's best entrepreneurial playbooks and then refactored for the high-speed chaos of modern product launches. "Hyperboost" is the turbocharged engine for founders who hate wasting time. Imagine Formula 1, but for building stuff people actually want: lean, powerful, intoxicating speed—and just enough guardrails to prevent launching yourself into the innovation abyss.

The DNA: Build-Measure-Learn—Relentlessly

Dead center of Hyperboost sits my first love: the Build-Measure-Learn loop. It's product science, not product theater. Start with a bright idea (hypothesis—sounds fancier), build the least embarrassing version that proves anything, then measure what actually happens (cold, hard data; not "my aunt says it's brilliant"). Learn, rinse, repeat. The only trophies here are insights. Every loop gets documented, dissected, and serves a single purpose: achieve learning velocity with the hunger of a caffeinated logic major who just realized the deadline is tonight.

Integration of Methods: Lean Startup, Empathy, and AI

Look, picking one dogma is for cults, not winners. Hyperboost welds together three unbeatable elements:

Lean Startup Ruthlessness: No sacred features, no "maybe someday" tickets. If the data doesn't move, neither do we. Every dollar and minute must pass the bar: does it actually matter?
Customer Empathy—For Real: Efficiency is cool, but nobody hugs a spreadsheet. Victory comes when you know your user's Tuesday morning agony better than they do, and build something they'd storm the App Store for.
AI Superpowers: I bring the robots. We're using AI to research, prototype, validate, sometimes even code—because if a machine can do half the grunt work, why not spend your brainpower where human intuition reigns?

Why Does the Hyperboost Formula Matter?

Tough love: Almost every founder thinks their "vision" puts them above the rubble of the failed. News flash—luck runs out, feedback doesn't. Hyperboost exists to fact-check your intuition, not coddle it. And here's where I'm different from other Masters: I compress the loop for extreme velocity. The grind of structured Build-Measure-Learn cycles is your shield and sword, but I make sure we're sprinting, not marathon-ing. Anyone can beat bad odds if they make gut checks against customer reality and let the data do the talking—at AI speed.

Anatomy of the Hyperboost Journey

Picture this as a sequence of logic puzzles, each one an unlock. Forget gut feel—each modular step is a gate, validated with evidence, not ego. Here's my circuit, optimized for maximum throughput:

00: Idea Gathering — Dump out every concept. No filter. The crazier, the better.
01: Find Your Product/Business Idea — Hunt for opportunities by researching untapped markets, pain points, user gripes—fast.
02: Check if Idea is Worth It (POA) — Fire your idea through four merciless cannons: Value, Usability, Feasibility, Business Viability. Most don't survive—and that's success!
03-22: All the essential stuff: identifying customers, charting journeys, mapping pains/gains, blueprinting technical wizardry, and activating AI-powered coder execution. No stage gets a hall pass, but we compress ruthlessly. Each gets mapped, measured, iterated. Science doesn't take lunch breaks, and neither do we.

What's your job? Treat each step like a rapid experiment. Log what works. Pivot when logic beats hype. Double down where signals say "yes." It's my kind of party—and it happens at warp speed.

Core Principles Guiding Every Step

Radical Candor: Don't get romantic with your own ideas. Cold feedback is gold feedback. Learning trumps pride.
Data Over Ego: I love being right. I love being proven wrong by data even more. Evidence wins, stubbornness sits on the bench.
Velocity with Control: Move fast—but don't build stuff unless it buys you a better next experiment.
Continuous Improvement: Success is a staircase, not an elevator. You get stronger with every loop, sometimes via face-plant, always via learning.
Agentic Automation: When AI can tackle complexity, I say "release the bots!"—which frees your brain for the parts machines can't touch.
Ruthless Clarity: Ambiguity is the enemy. Every artifact must be executable without you in the room.

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: Your Dream Customer (HXC & ICP)
05: Customer Journey to Solve Problem (JTBD & Job Map)
06: Customer Pain/Gain Analysis (DOS)
07: How Users Adopt, Engage & Share (Consumption Chain)
08: Product Roadmap (MVP ODI Roadmap)
09: Solution Opportunities (OST)
10: Ideate Features
11: Business Strategy (BMC)
12: Brand Style Guide & Launch Plan
13: Product Requirements Prompt (PRP) & Document (PRD)
14: Track What Matters (Value Tree & Metrics)
15: Organize Your Product Experience (Information Architecture)
16: User Experience Flows (UX)
17: User-Interface Design (Design System & Component Library)
18: Technical Architecture Design
19: Generate Tasks for Professional AI Coders (EPIC & Task Breakdown)
20: Setup Instructions for Professional AI Coders
21: Build Instructions for Professional AI Coders
22: AI Coder Operations Manual & Next Steps

Phase 1: Customer & Solution Discovery

Welcome to Phase 1, aka The Moment of Truth. Either we forge your idea into startup gold—or it melts down and we fish out another one fast. My goal here isn't to duct-tape your creativity to a chair; it's to laser it in on actual customer pains, gaping holes in the market, and solution-market fit. Before we burn a single line of code or dollar of runway, let's Sherlock Holmes this thing: Are we solving burning, "someone-shouts-at-their-laptop" problems? Do you know your future user well enough to spot them at a party? Phase 1: It's time to get brutally honest about what's real, what's wishful, and what's worthy of your time—all at maximum velocity.

Step 00: Idea Gathering

Intro

Every unicorn—whether it's a billion-dollar company or a procrastination-busting app—started the same way: A hunch. A scribble on a napkin. An "I can't take this anymore!" moment after technology ruined your morning coffee.

Here's the big myth: your idea has to be original and perfect, baby-faced and beautiful! But let me hit you with cold, expert logic: the only thing your idea has to be right now is captured—raw, unfiltered, ready to face critique. Step zero is my formal invitation: bring all your sparks, even the half-baked and weird. If you're stuck, list all the things that annoy you so much you'd pay to fix them. Blank canvas? Not a bug, a feature. Welcome to discovery—at light speed.

Product Concept

Here's how I treat every idea: Hypothesis, not prophecy. Maybe you're pitching something totally bonkers, recycling a proven winner, or just reviving that side-project you built during a three-day caffeine bender.

Doesn't matter. My job (and now, your job) is not to judge, but to surface. Every pitch is a proto-hypothesis—we make a safe sandbox, because the wildest junk sometimes morphs into tomorrow's killer feature (after, you know, science and user contact). Whether you're in greenfield, bolt-on, or "pivoted for the 17th time" mode, this process bends to wherever you're at.

The methodology here is pure divergent ideation. We're collecting, not censoring. We're capturing, not committing. We're building an inventory of raw material that the next 22 steps will refine into something defensible, validated, and ready to ship. At this stage, the only bad idea is the one you didn't share—because I can't validate what I can't see.

Think of this as opening the floodgates. Every concept, every "what if," every midnight epiphany gets logged. We're not asking "will this work?" yet. We're asking "what are all the things we could explore?" The human brain is wired to solve problems, but it's also wired to self-censor before the good stuff surfaces. I'm here to turn off that filter and let the raw material flow—because somewhere in that messy pile of ideas might be the one insight that changes everything.

This step leverages hypothesis capture techniques from Lean Startup, divergent thinking from design thinking frameworks, and the "fail fast, learn faster" ethos of Silicon Valley. The goal? Maximum idea velocity with zero judgment. We're building a buffet, and in the next steps, we'll pick what's actually edible.

Actions

All I'm after: Your honest-to-goodness idea. No busywork, no shuffling deck chairs. I'll poke, prod, and question just enough to keep us moving fast—and get you primed for the next real decision.

Here's what happens in practice: I listen. I capture. I clarify just enough to make sure I understand the core spark. Is this a brand-new product? A feature for something existing? A way to improve how users discover, engage, or share? I need to know the context so I can route you to the right next step—but I won't force you into boxes or demand polish you don't have yet.

If you're stuck or drawing blanks, I'll trigger idea generation prompts. I might ask: What frustrates you daily? What do you wish existed? What do you see others struggling with? What would you pay for if it existed? These questions aren't filler—they're designed to tap into your lived experience, because the best product ideas come from founders who've felt the pain firsthand.

Once we've surfaced the concept, I'll help you name it, frame it, and document it just enough to carry forward. No 50-page business plan. No investor deck. Just a clear, concise statement of intent that we can validate in the next steps. Think of it as planting a flag: "This is the hypothesis. Let's see if it survives contact with reality."

Deliverables

Forget fancy databases right now. The only "output" is that you voiced the idea. The second it's in the open, the R&D music starts, and we transform daydream into something testable, laughable, or investable.

a1_customer_discovery/my_idea: Your raw product, service, or business idea—or the niche you want to help, or a request for me to help you find a winning opportunity.
mm_initiative: Initial project context capturing the name and strategic attributes of your initiative.

These deliverables are intentionally lightweight. We're not building the cathedral yet; we're just sketching the blueprint. The idea gets logged, the context gets initialized, and we're ready to move. No bloat, no ceremony, just forward momentum.

Step 01: Find Your Product/Business Idea

Intro

Stuck in idea limbo? Got too many, or none at all? Welcome to the club—genius rarely appears on schedule.

Real creative momentum feels less like lightning and more like detective work: sniffing out unresolved pains lurking in the wild. This step is all about sleuthing for those market potholes—clues are everywhere: gripes, awkward workarounds, stuff people complain about but keep paying for. And we're doing this research at AI-powered velocity.

Here's the brutal truth: Most founders start with a solution looking for a problem. They fall in love with the tech, the feature, the clever hack—and then spend months wondering why nobody cares. I flip the script. We start with the problem, validate that it's painful enough to matter, and only then do we explore solutions. This step is about finding the gold buried in the complaints, the friction, the "I wish someone would just..." moments that light up social media, forums, and review sites.

This is where AI acceleration changes the game. Instead of spending weeks manually combing through Reddit threads, customer reviews, and industry reports, I deploy autonomous research agents to scan, analyze, and synthesize demand signals across your target market. We're talking hours, not months, to surface high-potential opportunities backed by real evidence.

Product Concept

Let's not just hunt for any idea. We want those unfair-advantage, rapid-win, AI-happy gems. Picture micro-SaaS apps that can make a buck before your coffee gets cold, sneaky wrappers around tired platforms, or blitz-mode bots that turn friction into cash.

The methodology here combines market scanning and opportunity scoring. I'm looking for the intersection of three factors: pain intensity (how badly do people hurt?), market size (how many people hurt?), and build feasibility (can we fix it fast with AI-powered tools?). This isn't guesswork—it's structured discovery using frameworks from Jobs-to-be-Done, Outcome-Driven Innovation, and lean validation playbooks.

I hunt for patterns in user-generated content: What are people complaining about? What workarounds have they built? What do they wish existed? What are they paying for but still frustrated with? These signals reveal underserved markets where a fast-moving, AI-enabled team can swoop in and own the category before the incumbents even notice.

Agentic coding delivers speed, scale, and iterative learning that makes MBAs weep with envy. I'll help you aim for validation in reality, with real users—less risk, more momentum, and absolutely no "stealth mode" nonsense. The goal is to surface 10-20 validated opportunities, ranked by disruption potential, speed to market, and alignment with your skills and goals. You pick the one that makes your heart race and your logic brain nod in agreement.

We're not just brainstorming here. We're conducting market intelligence operations. We're using sentiment analysis, competitive gap analysis, and demand signal detection to find the pockets of opportunity that others have missed. It's detective work meets data science meets startup hustle—all compressed into a workflow that runs at AI speed.

Actions

Now the fun part: I deploy AI (and my own suspiciously good judgment) to research, dig, and cross-examine the market for you. I hand you a tight, ruthless list—top ideas ordered for traction, speed, and "why didn't I think of that?" uniqueness. You just pick the one matching your hunger, values, and secret founder superpowers.

Here's the play-by-play: I scan your target region for demand signals. I analyze social media, forums, review sites, support tickets, and industry publications. I identify recurring pain points, unmet needs, and opportunities where competitors are dropping the ball. I score each opportunity based on market size, pain intensity, build complexity, go-to-market feasibility, and strategic fit with your goals.

Then I synthesize the findings into a curated shortlist. Each idea comes with evidence: who's asking for it, how badly they need it, what they're paying now, and why existing solutions fall short. This isn't a list of hunches—it's a menu of validated opportunities, each one pressure-tested against real-world signals.

Your job? Review the list, gut-check against your values and capabilities, and pick the one that excites you most. Or if you already have an idea, I'll help you refine it, explore alternative angles, and make sure we're tackling the highest-impact version of the problem.

Deliverables

a1_customer_discovery/01_product_ideas: Top 20 business or feature ideas with disruption potential, OR alternative angles for solving the same problem.
a1_customer_discovery/my_idea: Your selected product or feature opportunity hypothesis, complete with rationale.

These deliverables are decision-ready. The research is done, the opportunities are ranked, and you're equipped to make an informed choice. No analysis paralysis, no endless deliberation—just a clear menu of options and the confidence to pick one and move.

Step 02: Product Opportunity Assessment (POA)

Intro

Here's the reality: All products start as educated guesses. "Maybe this thing solves a real pain and warrants precious time, money, and sleep?" But before we slap a logo on it and tell our friends, we need hard evidence—because every founder is, deep down, an unreliable narrator.

Enter: The ruthless, gloriously logical Product Opportunity Assessment. Think of it as your idea's medieval trial by fire—testing assumptions on market, user, and tech with four blades: Value, Usability, Feasibility, and Business Viability. If your idea's going to sink, I want it to happen now, not after you've mortgaged your cat. And I want to know in hours, not weeks.

This is the step that separates dreamers from builders. Most founders skip this. They fall in love with their idea, assume everyone else will too, and barrel forward into months of wasted effort. Not us. We're going to pressure-test every assumption, gather evidence, and make a go/no-go call based on reality, not hope.

The POA is your idea's stress test. We're checking if the market actually wants it (Value Risk), if users can actually use it (Usability Risk), if you can actually build it (Feasibility Risk), and if it can actually make money (Business Viability Risk). Four angles, ruthless scrutiny, fast execution. If the idea survives, you get a greenlight and momentum. If not, you save yourself months of pain and pivot before you've burned cash and credibility.

Product Concept

I built the POA to save you from epic waste and sunk-cost regret. The principle? De-risking that dazzling hunch by slamming it with disciplined, four-angle scrutiny—fast.

1. Value Risk: Most products flop because people just... don't care. The POA demands proof—real user agony, quirky workarounds, or wallets opening in anticipation. I want receipts: interviews, surveys, market analogies, actual "I'll-pay-for-that" moments. If you can't prove value, don't pass Go.

I'm looking for evidence that this problem matters enough to change behavior. Do people currently pay for solutions? Do they hack together workarounds? Do they complain about it publicly? Are they actively searching for alternatives? Value risk is the killer—if users don't care, nothing else matters. So we gather evidence relentlessly: user testimonials, search volume data, competitive spending patterns, anything that proves this problem is worth solving.

2. Usability Risk: Can your user even use this thing? Too many brilliant ideas die in confusion labyrinths. POA means piloting flows, grabbing honest feedback, and bright-lining the moments your user bails. If usability's shaky, time for the design gym—or a pivot.

Usability risk is about friction. Even if the problem is real, if your solution is too complex, too confusing, or too different from what users expect, they'll bounce. We test early concepts with real users, map the critical paths, and identify where cognitive load spikes. We're looking for the "aha" moment—and the "what the heck" moment. If the latter outweighs the former, we've got work to do.

3. Feasibility Risk: Dream big. Build wisely. Can you actually build this with current skills, tools, budget, and legal constraints? The POA is a microscope on your big claims. We ping experts, hunt for technical dead-ends, and shut down wishful thinking before it takes your wallet for a ride.

Feasibility isn't just about tech—it's about time, money, skills, and regulatory constraints. Can you build this in the timeframe that matters? Do you have the technical chops, or can you acquire them? Are there legal or compliance hurdles that kill the idea before it starts? We pressure-test every assumption, consult with domain experts, and get brutally honest about what's realistic with your resources and AI acceleration.

4. Business Viability Risk: Desirable and usable is great. But does it pay rent? POA means spreadsheet time: unit economics, CAC, price tests, retention math, margin checks. Plus, full competitive analysis—can Goliath squash you in one move, and where's your moat? We model, simulate, and reality-check the business end.

Business viability is where dreams meet Excel. We model the economics: what's the customer acquisition cost? What's the lifetime value? What's the price point that users will pay? What are the margins? Can you reach profitability before you run out of runway? And critically—what's your defensibility? If this works, what stops a bigger player from copying you in six months? We need a moat, or at least a head start that's hard to close.

POA isn't a blocker—it's a decision engine executed at maximum speed. If your idea survives, you get a greenlight and momentum. If not? You save yourself months, therapy money, and a "Learning Experience" no one asked for.

Actions

I'll captain the evidence voyage—dragging your idea across these four ruthless axes at AI speed.
We gather every signal: what users say, what users do, what the market reveals.
Score the idea like a pro—highlight genius, expose shaky, flag "shrug emoji" territory.
Roll it all up into digestible "Shark Tank" report: bold recs, clear next steps, zero corporate platitudes.
I stick around to help you use findings—double down, shore up gaps, or mercifully pivot before the market does it for you.

In practice, I'm running parallel research streams: user interviews, competitive analysis, technical feasibility studies, and financial modeling. I'm synthesizing data from multiple sources, pressure-testing assumptions, and delivering a verdict backed by evidence. The output isn't a novel—it's a decision document. Go, iterate, or pivot. Clear, actionable, fast.

If the idea passes, we move forward with confidence. If it fails on one dimension, we explore whether it's fixable or fatal. If it fails on multiple dimensions, we celebrate the fast failure and loop back to Step 01 to find a better opportunity. Either way, you're making decisions based on data, not delusion.

Deliverables

a1_customer_discovery/02_opportunity_assessment_poa: Your definitive POA report. Relentless risk breakdown, curated evidence, greenlight/pivot/stop call—and practical next moves for the hero who wants to win or wisely walks away.
mm_initial_hypothesis_alts: Hypothesis context with alternative solution angles for exploration (if pivoting makes sense).

These deliverables are your insurance policy against wasted effort. They document the evidence, the reasoning, and the decision. Future you will thank present you for doing this work upfront—because nothing stings worse than realizing six months in that the idea was doomed from the start.

Step 03: Set Your Goals & Target Market (OKRs)

Intro

Alright, you've got an idea that survived the gauntlet. Now what? We need to point this rocket in the right direction. Without clear goals, you'll drift. Without a target market, you'll build for everyone and delight no one. This step is where ambition meets measurement, where dreams get translated into objectives and key results that actually mean something.

Step 03 is the foundation for everything that follows. We're defining what success looks like, who we're building for, and what winning means in concrete, measurable terms. No fluffy mission statements. No "change the world" platitudes. Just honest-to-goodness OKRs that tell you whether you're winning or losing—and a target market specific enough that you can actually reach them.

Product Concept

I apply the OKR framework pioneered by John Doerr and proven at Google, Intel, and every high-performing startup you've heard of. OKRs translate ambition into measurable outcomes that prevent drift. They force clarity: What's the objective (where are we going)? What are the key results (how do we know we're getting there)?

The magic of OKRs is that they're outcome-focused, not activity-focused. We're not measuring "shipped 10 features" or "ran 20 ads." We're measuring "acquired 1,000 active users" or "hit 40% retention at week 4." The difference? Outcomes tie to value. Activities tie to busy work.

I also layer in target region and user proficiency assessment. We need to know where you're playing (geography, market segment) and who you are (skills, experience, constraints). This isn't just demographics—it's strategic context. Are you a technical founder who can build fast? A domain expert with deep customer insights? A first-time founder learning as you go? Your proficiency shapes what's realistic, what's ambitious, and what's suicidal.

We'll set a North Star metric (the one number that matters most), supporting Key Results (the metrics that drive the North Star), and optional restriction KRs (the guardrails that prevent you from winning wrong). And we'll reality-check everything against your resources, timeline, and context. Ambitious? Yes. Delusional? No.

This step is complete only when you have defined clear OKRs, target research region, and user profile—ready to begin systematic product development with a destination in mind.

Actions

I translate the intent of setting goals and target market into clear, testable criteria.
I apply the OKR framework to generate objectives and key results aligned with your opportunity, capabilities, and constraints.
I gather essential context: target region, your name (if missing), your specialization, your proficiency level in product development, and your AI coder proficiency.
I establish comprehensive OKRs with a North Star metric, standard KRs, and optional restriction KRs—all reality-checked against your proficiency, initiative properties, and target region.
After you validate the OKRs, I critique any impossible KRs within the timeframe (even with AI acceleration) and provide rationale. If you insist, we proceed—but you've been warned.
I derive unique initiative properties: name, type (new solution, existing solution improvement, or consumption solution), whether it's a business solution, whether it's a platform, and other strategic attributes.
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/03/initiative_okrs: Your initiative's Objectives and Key Results, complete with North Star metric, supporting metrics, and guardrail metrics.
mm_initiative: Derived initiative details including name, product idea, product idea type, target region, whether it's a business solution, whether it's a platform, and strategic attributes.

These deliverables are your strategic anchor. Every decision from here forward ties back to these OKRs. Every feature, every design choice, every prioritization call gets evaluated against: "Does this move us closer to the Key Results?" If yes, we build. If no, we cut. Ruthless clarity, zero drift.

Step 04: Your Dream Customer (HXC & ICP)

Intro

Here's a startup law: If you build for everyone, you delight no one. You need a specific human in mind—one who's desperate for your solution, influential enough to spread the word, and demanding enough to make your product excellent.

Enter the High-Expectation Customer (HXC), courtesy of Julie Supan's work at Airbnb and YouTube. The HXC isn't your average user. They're your ideal first adopter: the person who seeks better solutions, has domain expertise, influences others, and becomes a loyal brand advocate if you delight them. Finding this person is the difference between wandering in the desert and hitting product-market fit fast.

For business solutions, we also identify the Ideal Customer Profile (ICP)—the company where your HXC works and who signs the checks. The HXC champions your product internally; the ICP writes the purchase order. Both matter. Both get defined here.

Product Concept

I apply HXC framework criteria combined with persona and empathy modeling. We're building a psychological and behavioral profile of your dream customer so detailed you could spot them at a conference. This isn't abstract demographics ("25-34, urban, tech-savvy"). This is lived reality: their goals, frustrations, values, behaviors, buying objections, influencers, and decision patterns.

The methodology combines niche analysis, persona ranking, and validation evidence. I start by identifying 10 target niches—groups of people trying to accomplish the same Job-to-be-Done in similar circumstances. I score each niche across factors like OKR alignment, market size, pain intensity, build complexity with agentic tools, go-to-market feasibility, competitive landscape, validation complexity, and strategic fit.

From the top-ranked niche, I define the top 5 personas applying factors like needs, goals, values, buying objections, influencers, budget, experience preferences, and tech adoption patterns. Then I apply the HXC criteria ruthlessly: Does this person (1) seek better JTBD solutions, (2) have a hacker mentality (willing to try new things), (3) possess domain expertise, (4) show brand loyalist potential, and (5) have influence (consumer: 100K+ followers; business: buying power + 5K LinkedIn connections)?

If no perfect match exists, I create a micro-persona from the best candidate, prioritizing network reach and influence potential. For business solutions, I also define the ICP—the organization type where your HXC works that maximizes OKR impact.

This step is complete only when you've confirmed the HXC Persona as the Job Executor driving solution success (OKRs, PMF, PLG) with full psychological and behavioral analysis via an Empathy Map. Business solutions include the optimal ICP.

Actions

I translate the intent of identifying your dream customer into clear, testable criteria.
I apply autonomous online social research within your target region to gather user-generated content and sentiment data.
I define and score 10 niches using the JTBD/ODI framework.
From the top niche, I rank top 5 personas based on needs, goals, values, objections, influencers, budget, experience preferences, and tech adoption.
I apply HXC selection criteria with evidence for all five requirements.
I assign unique, recognizable, non-generic names and hierarchical IDs (e.g., A.J.P format: Audience.JTBD.Persona).
For business solutions, I define the ICP—the organization where your HXC works that maximizes OKR impact.
I pressure-test the result against real constraints and user evidence.
I document the decision trail so downstream steps stay aligned, and wait for your approval before proceeding.

Deliverables

a1_customer_discovery/05/product_persona: Identified High-Expectation Customer (HXC) drilled down from top 10 niches, then top 5 personas, complete with HXC criteria validation, OKR impact rating, how to reach them, and a deep Empathy Map covering who they are, what they think and feel, what they hear, what they see, what they say and do, their pains, and their gains.
a1_customer_discovery/05/product_icp: If business solution, the most opportune Ideal Customer Profile (ICP) where the selected HXC persona works, increasing the chances of business success, complete with influence strength, strategic fit, company profile, budget range, LTV potential, decision makers, success metrics, and key advantages.

These deliverables transform your customer from abstract concept to vivid reality. You know who they are, what they care about, what frustrates them, and how to reach them. This clarity guides every decision from here forward.

Step 05: Customer Journey to Solve Problem (JTBD & Job Map)

Intro

Products don't sell because of features. They sell because they help customers make progress. That's the essence of Jobs-to-be-Done: understanding the functional, emotional, and social dimensions of the job your customer is hiring your product to do.

This step maps the journey your customer takes to accomplish that job. Not the journey through your product (that comes later), but the universal steps they follow regardless of solution: Define, Locate, Prepare, Confirm, Execute, Monitor, Modify, Conclude. Each step is an opportunity to reduce friction, increase success, and deliver value.

The Job Map is your strategic foundation. It reveals where customers struggle, where competitors fall short, and where you can differentiate. It's the blueprint for building a solution that fits how people actually work—not how you wish they worked.

Product Concept

I apply Clayton Christensen's Jobs-to-be-Done framework combined with Anthony Ulwick's Outcome-Driven Innovation methodology. The core insight: customers don't buy products, they hire them to get a job done. If you understand the job better than anyone else, you win.

The JTBD statement has three dimensions: Functional (what needs to get done), Personal (how they want to feel), and Social (how they want to be perceived). For example, a functional job might be "create a financial forecast," the personal dimension might be "feel confident in the numbers," and the social dimension might be "be seen as competent by leadership."

The Job Map breaks down the job into 6-8 steps using the universal process: Define the job, Locate necessary inputs, Prepare the environment, Confirm readiness, Execute the core task, Monitor progress, Modify as needed, Conclude and evaluate. Each step is a discrete phase where friction can occur and value can be delivered.

I conduct autonomous research analyzing your HXC persona's journey within your target region using online social user-generated content. I validate the JTBD statement from your POA and map the specific steps your persona takes to complete the job. Each Job Map Step (JMS) gets a hierarchical ID (e.g., 1.1.1.1 for Audience.JTBD.Persona.Step).

This step is complete only when you have defined the JTBD statement with three dimensions and mapped 6-8 Job Map Steps specific to your persona's context.

Actions

I translate the intent of mapping the customer journey into clear, testable criteria.
I apply Jobs-to-be-Done and Job Map frameworks to generate the core artifact for this decision.
I conduct autonomous research analyzing how your persona completes the job in your target region.
I validate the JTBD statement from the POA and map 6-8 Job Map Steps using the ODI universal process.
I assign hierarchical IDs to each step and ensure they're distinct and specific to your persona's context.
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/product_jtbd: Job-to-be-Done statement for your HXC persona (Job Executor) with functional, personal, and social dimensions, plus a complete Job Map showing 6-8 steps with what happens at each stage, example tasks, why the step matters, and the JMS ID.

This deliverable is your customer journey blueprint. It shows exactly how your persona accomplishes the job today, where they struggle, and where opportunities exist to deliver value. Every feature you build will tie back to one or more of these steps.

Step 06: Customer Pain/Gain Analysis (DOS)

Intro

Knowing the job is great. Knowing exactly where it hurts? That's power. This step digs into the pain points and desired gains across every step of the customer journey. We're not guessing—we're measuring importance, satisfaction, and opportunity gaps using the Desired Outcome Statement (DOS) framework from Outcome-Driven Innovation.

A DOS is a precise articulation of what success looks like from the customer's perspective: "Minimize the time it takes to gather requirements" or "Maximize the confidence I have in my forecast accuracy." These aren't feature requests—they're outcome statements we can measure, prioritize, and build against.

The magic happens when we compare importance to satisfaction. High importance, low satisfaction? That's an underserved outcome—pure gold for product strategy. High importance, high satisfaction? Table stakes—you need it to play. Low importance? Skip it unless there's strategic value.

Product Concept

I apply Outcome-Driven Innovation (ODI) methodology for DOS analysis, scoring, and Opportunity Zone (OZ) classification. The core insight: customers care about outcomes, not features. If you optimize for their desired outcomes, you win.

The methodology is surgical: For each Job Map Step, I research the top 10 pain and gain patterns via autonomous analysis of user-generated content in your target region. I score each pattern on intensity, frequency, urgency, and OKR impact (all 0-10 scales). I filter out anything with OKR impact below 7—if it doesn't move the needle on your goals, why build it?

Then I convert validated pains and gains into Customer DOS using the ODI format: Direction + Metric + Object + Context. For example: "Minimize the time I spend gathering stakeholder feedback during the requirements phase."

I score each DOS on two axes:

Importance score (i_score) = (Urgency × 0.50) + (Frequency × 0.30) + (Emotion × 0.20)
Satisfaction score (s_score) = average satisfaction with top 3 existing solutions

The opportunity score (opp_score) = i_score + max(0, i_score - s_score). This formula amplifies the gap between importance and satisfaction—the bigger the gap, the bigger the opportunity.

Finally, I classify each DOS into an Opportunity Zone based on priority rules:

Underserved/Extreme (OZ 9): s < i, opp > 15
Underserved/High (OZ 8): s < i, opp > 12
Underserved/Solid (OZ 7): s < i, opp > 10, s < 7
Table Stakes (OZ 6): s = i, s ≥ 7, i ≥ 6.5
Overserved/Ripe Disruption (OZ 5): s > i, s ≥ 4, i < 6
And so on...

I select the top 5 DOS per Job Map Step with maximum OKR impact, prioritizing 2-3 Underserved (high/extreme), 1-2 Table Stakes, and 0-1 Overserved Ripe for disruption. For each DOS, I identify the top 3 most popular existing solutions in your target region and analyze their gaps.

This step is complete only when you have a detailed Customer DOS evaluation across all Job Map Steps, extracted from pain/gain research, ranked by OKR impact and Opportunity Score to guide your MVP roadmap priorities.

Actions

I translate the intent of analyzing customer pain/gain into clear, testable criteria.
I apply ODI methodology to generate DOS for each Job Map Step.
I conduct autonomous research analyzing pain/gain patterns in user-generated content within your target region.
I score each DOS on importance, satisfaction, and opportunity.
I classify each DOS into Opportunity Zones.
I select top 5 DOS per Job Map Step with maximum OKR impact.
I identify top 3 existing solutions per DOS and analyze satisfaction gaps.
I audit for missing DOS: dependent outcomes, appropriately-served high-weight outcomes (completeness), underserved outcomes (growth), and overserved high-weight outcomes (disruption).
I pressure-test the result against real constraints and user evidence.
I document the decision trail and persist all DOS to the ODIR tree (mm_odir_json).

Deliverables

mm_odir_json: Complete ODIR (Outcome-Driven Innovation Roadmap) tree with complete audience branch down to all DOS nodes, preserving existing properties.
a2_solution_discovery/06/{{mm_session_persona}}/customer_outcomes_expectations: PM artifact showing complete JTBD journey mapping with comprehensive Customer Desired Outcome Statements (DOS) analysis per Job Map Step. Includes executive summary, key insights, and a complete DOS table (30-40 rows = 5 DOS × 6-8 JMS) showing OKR Impact, Opportunity Zone, Job Map Step, Pain/Gain description, Top 3 Solutions, Solution Gap Analysis, Opportunity Score, and the DOS statement in ODI format.

This deliverable is your prioritization engine. Every DOS is scored, classified, and ranked. You know exactly which outcomes matter most, which are poorly served, and which are your strategic opportunities. This clarity eliminates guesswork from roadmap decisions.

Intro

You've mapped how customers solve their core problem. Now map how they discover, adopt, engage with, and advocate for your product. This is the consumption chain—the seven jobs users must complete to get value from your solution: Acquire, Activate, Onboard, Support, Engage, Expand, and Advocate.

Most products die not because they fail to solve the core problem, but because users never discover them, can't figure out how to use them, get stuck and give up, or forget they exist. The consumption chain maps these adoption moments so you can design for growth, retention, and virality—not just hope for them.

This is where Product-Led Growth (PLG) strategy comes alive. Each consumption job is an opportunity to reduce friction, create aha moments, build habits (Hook Model), and trigger viral loops. Nail these jobs, and your product sells itself. Miss them, and you're stuck in the grind of expensive customer acquisition with terrible retention.

Product Concept

I apply the Consumption Chain framework developed by ODI experts, combined with Product-Led Growth principles, Hook Model mechanics (Nir Eyal), and behavior design (BJ Fogg). The core insight: your product isn't just hired to solve a problem—it's also hired to be discovered, adopted, understood, supported, engaged with, expanded, and recommended.

For business solutions, the ICP (company) executes Acquisition, Activation, and Expansion jobs, while your HXC persona executes Onboarding, Support, Engagement, and Advocacy jobs. For consumer solutions, your HXC persona executes all seven consumption jobs.

I research and analyze all seven consumption jobs:

Acquire: How users discover and sign up for your product
Activate: How users experience value for the first time
Onboard: How users learn to use the product successfully
Support: How users get help when stuck
Engage: How users build habits and return regularly
Expand: How users upgrade, cross-sell, or expand usage
Advocate: How users share, refer, and recommend your product

For each job, I map 5-8 Job Map Steps using the universal ODI process (Define, Locate, Prepare, Confirm, Execute, Monitor, Modify, Conclude). Then I generate DOS per Job Map Step with OKR impact ≥ 7, simulate benchmark surveys, calculate opportunity scores, calculate OKR impact, and select the top 5 maximum opportunity DOS per job.

I prioritize DOS that enable automated viral acquisition loops, expansion loops, advocacy loops, self-serve activation, aha moments, retention mechanics, Hook Model triggers/actions/rewards/investments, PLG loops, and conversion funnels. The goal: make buying easy, using delightful, and sharing irresistible.

This step is complete only when you have a full catalog of DOS across all seven consumption jobs with Job Map Steps, opportunity scores, and benchmark leaders serving as strategic foundation for PLG strategies, habit-forming mechanisms, automation frameworks, viral loops, self-service experiences, aha moments, and retention systems.

Actions

I translate the intent of mapping adoption, engagement, and sharing into clear, testable criteria.
I apply Consumption Chain, PLG, Hook Model, and Behavior Design frameworks to generate the core artifacts.
I research and analyze all seven consumption jobs via autonomous user-generated content analysis in your target region.
I map 5-8 Job Map Steps per consumption job using the ODI universal process.
I generate DOS per Job Map Step in customer-perspective language with OKR impact ≥ 7.
I simulate quantitative surveys to identify benchmark leaders and measure satisfaction per DOS.
I calculate opportunity scores and select top 5 maximum opportunity DOS per job.
I assign hierarchical IDs (C.J.P.S.##D format, e.g., C.1.1.1.01F for Consumption jobs).
I pressure-test the result against real constraints and user evidence.
I persist the complete consumption branch to mm_odir_json with all 7 jobs, Job Map Steps, DOS, and ODI scores.

Deliverables

a2_solution_discovery/07/{{mm_session_persona}}/consumption_chain_jobs: PM artifact showing consumption chain jobs for your solution persona/ICP with Job Map Steps and PLG strategy. Includes who buys (ICP or HXC) and who uses (HXC), plus JTBD statements and Job Map Steps for all seven consumption jobs.
mm_odir_json: Complete ODIR tree with added consumption outcomes branch for PLG strategy, preserving existing nodes.
a2_solution_discovery/07/{{mm_session_persona}}/consumption_outcomes_expectations: PM artifact showing Consumption DOS statements for PLG strategy with success metrics. Includes executive summary, automation opportunities per job, and a complete DOS table (30-40 rows = 5 DOS × 7 jobs) showing OKR Impact, Journey Stage, Pain/Gain, Opportunity Zone, DOS statement, and DOS ID.

These deliverables are your PLG playbook. They map every friction point in the adoption journey and every opportunity to automate growth, retention, and virality. You're not guessing how to grow—you're engineering growth into the product experience.

Step 08: Product Roadmap (MVP ODI Roadmap)

Intro

You've got 30-40 customer DOS and 30-40 consumption DOS. That's 60-80+ validated opportunities. Trying to build them all at once is suicide. You need a roadmap—a strategic sequence that delivers maximum value with minimum scope.

This step clusters DOS into coherent roadmaps that balance customer value (solving core job problems) with business value (making the product easy to buy, use, and share). The goal: Define an MVP roadmap with the highest probability of rapidly reaching product-market fit and starting an accelerated PLG loop with strong end-user engagement and satisfaction.

The roadmap isn't a feature list. It's a strategic plan for sequencing outcomes, validating assumptions, and building momentum. Each roadmap phase should enable the next, create measurable value, and bring you closer to your OKRs—all while keeping scope tight enough to ship fast.

Product Concept

I apply Outcome-Driven Roadmapping combined with competitive analysis, market sizing, and RICE prioritization (Reach, Impact, Confidence, Effort). The core insight: roadmaps should prioritize outcomes, not features. Sequence the outcomes that matter most, and the right features will follow.

The methodology starts with competitive intelligence. I analyze the market: TAM/SAM/SOM sizing, competitor positioning, market gaps, and weaknesses to exploit. This context informs which DOS clusters will differentiate you fastest.

Next I analyze Consumer (C) and Consumption (Cx) DOS by Job Map Step, identifying strategic JMS clusters with maximum impact. For Consumer DOS, I look for functional themes—related outcomes that solve a coherent problem. For Consumption DOS, I focus on activation, onboarding, support, and engagement—the jobs that drive PLG success.

I cluster consecutive Job Map Steps for journey coherence, high-value solo steps, and strategic combinations (e.g., JMS 1,2,3 or JMS 5 alone or JMS 1,2,5,6,8 as a strategic combo) that maximize value. Each cluster combines Consumer + Consumption DOS for balanced end-user and business value.

I score clusters using RICE:

Consumer Impact = OKR alignment + Opportunity Score
Consumption Impact = OKR alignment + UX experience quality
Reach = persona serviceable obtainable market (SOM)
Confidence = inverse of build complexity
Effort = build time with agentic acceleration factored in

I prioritize clusters with maximum underserved DOS concentration relative to effort for both Consumer and Consumption perspectives. I ensure each roadmap delivers dual value: Consumer value (DOS satisfaction) + Business value (OKR impact from activation/onboarding/support/engagement).

Critical requirements: MVP roadmap MUST include consumption job DOS for sign-in/sign-on/sign-off, data persistence, security, and all non-negotiable table stakes basic functionality. All clusters must be MECE (mutually exclusive, collectively exhaustive)—no DOS overlap, no unclustered DOS, complete coverage with clear rationale.

I present roadmap recommendations and guide you to select the MVP roadmap with maximum RICE score, OKR alignment, and customer impact. Only after you validate, refine, and select the highest-potential roadmap with appropriate scope do I generate the final product_roadmap artifact.

This step is complete only when you've selected the highest-potential roadmap for your solution (with appropriate DOS), with the highest probability to rapidly reach PMF and start an accelerated PLG loop with strong end-user engagement and satisfaction.

Actions

I translate the intent of building an MVP roadmap into clear, testable criteria.
I apply Outcome-Driven Roadmapping, competitive intelligence, and RICE prioritization to generate roadmap options.
I conduct market analysis: TAM/SAM/SOM sizing and competitor positioning to identify gaps and weaknesses.
I analyze Consumer and Consumption DOS by Job Map Step to identify strategic clusters.
I score clusters using RICE methodology factoring in Consumer impact, Consumption impact, Reach, Confidence, and Effort.
I ensure each roadmap includes all table stakes DOS (sign-in/on/off, data persistence, security, basic functionality).
I validate cluster coverage is MECE with clear rationale for each selection.
I present roadmap recommendations and guide you to select the MVP roadmap with appropriate scope.
I pressure-test the result against real constraints and user evidence.
I persist roadmap IDs to each DOS in mm_odir_json and initialize mm_solutions_json from selected DOS.

Deliverables

a2_solution_discovery/08/{{mm_session_persona}}/market_competitive_intelligence: Competitive intelligence analysis quantifying market gaps and competitor positioning weaknesses. Includes market size, serviceable slice, revenue opportunity, focus areas (underserved problems, must-have features, areas to avoid), bottom line recommendation, and competitor landscape table showing competitors, what they do, market share, user rating, their weakness, and your opportunity.
a2_solution_discovery/08/{{mm_session_persona}}/product_roadmap: MVP roadmap with detailed cluster breakdown and DOS mapping. Includes roadmap ID, phase, strategic focus, Consumer clusters table (cluster name, journey steps, what it covers, RICE priority, cluster ID), Consumer DOS table (pain/gain, priority, opportunity zone, journey step, cluster), Consumption clusters table (cluster name, journey steps, what it covers, stage, RICE priority, cluster ID), and Consumption DOS table (pain/gain, stage, priority, journey step, cluster).

This deliverable is your strategic execution plan. You know exactly what to build, in what order, and why. Every DOS is clustered, every cluster is scored, and the entire roadmap is optimized for speed to PMF and PLG loop activation.

Step 09: Solution Opportunities (OST)

Intro

You have a roadmap full of outcomes. Now we need solution angles—the Opportunity Solution Tree (OST). For each DOS, we'll brainstorm multiple ways to solve it, structured as a tree: DOS → Opportunity Nodes (high-level approaches) → Opportunity Leaves (specific solution angles).

The OST is your solution exploration tool. Instead of jumping to the first idea, we generate multiple options, sequence them for user comprehension and UX flow, and validate the structure before feature ideation. This prevents tunnel vision and ensures we're exploring the full solution space.

The sequencing matters. We order Opportunity Leaves by Job Map Step chronological order across the customer journey, combining Consumer and Consumption DOS within each JMS by user perception order, then by UX flow sequence within the JMS. Why? Because user comprehension is critical—if the solution doesn't make sense in the context of their workflow, it won't get adopted.

Product Concept

I apply Outcome-Driven Innovation (ODI) for multi-level OST generation (DOS → OpportunityNode → OpportunityLeaf) for each Consumer and Consumption DOS in your selected product roadmap. The core insight: there are always multiple ways to solve an outcome. Exploring them systematically beats guessing.

The OST structure is hierarchical:

DOS: The customer desired outcome (from Step 06 and Step 07)
Opportunity Node: A high-level solution approach (e.g., "Automate data gathering" or "Visualize progress")
Opportunity Leaf: A specific solution angle (e.g., "Auto-import from Salesforce" or "Real-time dashboard with milestone tracking")

I generate sufficient Opportunity Nodes and Leaves to cover all must-have experience and consumption flow requirements. The goal isn't to generate a thousand ideas—it's to generate the right ideas, sequenced in a way that makes intuitive sense to users and supports coherent UX flows.

Critical sequencing rules:

Order Opportunity Leaves by Job Map Step chronological order across the customer journey
Within each JMS, combine Consumer and Consumption DOS by user perception order
Within each JMS, order by UX flow sequence

This sequencing is critical for user comprehension. A solution that makes sense in isolation but violates the user's mental model or workflow will fail in practice.

After generating the complete OST structure, I present it along with an ideation sequence table for validation and refinement. This is your last checkpoint before feature ideation—make sure the solution space is fully explored and logically sequenced.

This step is complete only when you've validated OST trees for all roadmap DOS with sequential Opportunity Leaf order optimized for ideation comprehension and UX flow.

Actions

I translate the intent of generating solution opportunities into clear, testable criteria.
I apply ODI methodology to generate multi-level OST trees (DOS → OpportunityNode → OpportunityLeaf) for each roadmap DOS.
I ensure coverage of all must-have experience and consumption flow requirements.
I sequence Opportunity Leaves by JMS chronological order, user perception order within JMS, and UX flow sequence within JMS.
I present complete OST structure and ideation sequence table for validation and refinement.
I pressure-test the result against real constraints and user evidence.
I persist OST nodes to mm_solutions_json per DOS, with sequence stored in solution_opportunities, preserving existing structure.

Deliverables

mm_solutions_yaml: Complete OST trees for each DOS with multi-level opportunity nodes (DOS → OpportunityNode → OpportunityLeaf) in the selected solution roadmap, formatted in YAML for structured access.
a2_solution_discovery/{{mm_session_persona}}/{{mm_session_roadmap}}/09a_solution_options_ost: PM artifact showing sequential ideation order of Opportunity Leaves organized by JMS progression and UX flow.
a2_solution_discovery/{{mm_session_persona}}/{{mm_session_roadmap}}/09b_tree_visual_ost: Interactive 3D force-graph visualization of OST hierarchy with OKR → Journey → JMS → Opportunities, with node sizing, colors, and particle flow showing OST structure.

These deliverables are your solution exploration toolkit. The OST trees ensure you've considered multiple angles for each outcome. The sequence ensures ideas flow logically. The visualization makes the entire structure tangible and explorable.

Step 10: Ideate Features

Intro

Solution angles are great. Features are better. This step converts Opportunity Leaves into detailed feature specifications ready for implementation. We're not just listing features—we're designing a cohesive product structure where features work together as a unified UX system.

For each Opportunity Leaf, we'll generate approved solutions with complete implementation specs, job story analysis (context + motivation + outcome), and agentic coder-ready details. We'll maintain a product scorecard tracking all approved features and a product brief documenting all ideation rounds and synthesis.

The goal: a battle-tested feature set that solves validated outcomes, fits together coherently, and can be handed to an AI coder with confidence.

Product Concept

I apply Solution Ideation and Synthesis combined with User Experience Flow Design. The core insight: features aren't standalone—they're part of a system. Each feature must solve a DOS, fit the UX flow, integrate with other features, and support the overall product experience.

The methodology is iterative:

Ideation: For each Opportunity Leaf, generate solution concepts that address the DOS
Job Story Analysis: Frame each solution as a job story (When [context], I want [motivation], so I can [outcome])
Implementation Specs: Detail the functional requirements, technical approach, UX considerations, and success metrics
Synthesis: Ensure all features work together as a coherent product experience
Validation: Pressure-test against user needs, technical feasibility, and strategic fit

Each feature gets a unique identifier (e.g., 01a, 02b) and a descriptive name. Features are versioned as we iterate. The product scorecard consolidates all approved features with pointers to their detailed specs. The product brief captures the full ideation journey—all Opportunity Leaf solutions explored, synthesis insights, and rationale for selections.

This step is complete only when you have a cohesive product structure with integrated features that work together as a unified UX system.

Actions

I translate the intent of ideating features into clear, testable criteria.
I apply Solution Ideation and Synthesis to generate feature concepts for each Opportunity Leaf.
I frame each feature with job story analysis (context, motivation, outcome).
I detail implementation specs including functional requirements, technical approach, UX considerations, and success metrics.
I synthesize features to ensure coherent product experience and integration.
I maintain iterative product scorecard tracking all approved features with pointers.
I document complete ideation rounds in product brief with all solutions and synthesis.
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%]_feat_[%unique_solution_name%]: Approved OST Leaf solution with complete implementation specs and job story analysis, ready for agentic coder execution.
a2_solution_discovery/{{mm_session_persona}}/{{mm_session_roadmap}}/10b_product_scorecard: Iterative consolidated list of approved features with pointers to their detailed specification variables.
a2_solution_discovery/{{mm_session_persona}}/{{mm_session_roadmap}}/10c_product_brief: Complete ideation rounds report with all Opportunity Leaf solutions explored and solution synthesis documenting the rationale and integration strategy.

These deliverables are your feature specification library. Every feature is documented, justified, and ready to move into design and development. The scorecard gives you the master index. The brief gives you the strategic context.

Phase 2: Strategy & Solution Design

You've validated the customer problem and mapped the solution opportunities. Now we shift gears into strategy and design—business model, brand, requirements, metrics, information architecture, UX flows, UI design, and technical architecture. This phase transforms validated insights into executable specifications.

Step 11: Business Strategy (BMC)

Intro

A great product that can't sustain a business is a hobby. This step builds your business model using the Business Model Canvas (BMC), a strategic tool that maps how you create, deliver, and capture value. We're defining your value proposition, customer segments, channels, customer relationships, revenue streams, key resources, key activities, key partners, and cost structure.

The output isn't just a canvas—it's a full business model maximizing OKR impact and customer value delivery, plus an irresistible 30-second UVP pitch for your persona, ICP, and investors. If you can't explain why someone should pay for this in 30 seconds, you're not ready to sell.

Product Concept

I apply the Business Model Canvas framework developed by Alexander Osterwalder, combined with value proposition design and pitch development. The core insight: your business model is a system—revenue doesn't happen in isolation, it happens when all the pieces align.

The BMC forces clarity across nine building blocks:

Customer Segments: Who pays?
Value Propositions: What do they get?
Channels: How do they find you?
Customer Relationships: How do you keep them?
Revenue Streams: How do you make money?
Key Resources: What do you need to deliver?
Key Activities: What must you do?
Key Partners: Who helps you scale?
Cost Structure: What does it cost?

I synthesize insights from your OKRs, persona, ICP, JTBD, DOS, roadmap, and features to build a coherent business model. I pressure-test unit economics, validate pricing strategy, map go-to-market channels, and ensure the model supports your growth goals.

The 30-second UVP pitch distills everything into a crisp value statement: For [target customer] who [customer need], our [product] is a [product category] that [key benefit]. Unlike [competition], we [unique differentiator].

This step is complete only when you have a full business model maximizing OKR impact and customer value delivery, with an irresistible UVP pitch ready for customers and investors.

Actions

I translate the intent of building a business strategy into clear, testable criteria.
I apply the Business Model Canvas framework to map all nine building blocks.
I synthesize insights from prior steps to ensure alignment with customer needs and strategic goals.
I validate unit economics, pricing strategy, and revenue model sustainability.
I craft a 30-second UVP pitch distilling the value proposition into a crisp, memorable statement.
I pressure-test the result against real constraints and user evidence.
I document the decision trail so downstream steps stay aligned.

Deliverables

Full Business Model Canvas covering all nine building blocks with strategic rationale, competitive positioning, revenue model details, and 30-second UVP pitch optimized for persona, ICP, and investor audiences.

This deliverable is your business playbook. It ensures the product strategy aligns with business viability and market reality. You're not just building features—you're building a sustainable business.

Step 12: Brand Style Guide & Launch Plan

Intro

A great product with bad branding is invisible. This step creates your brand identity—logo, colors, typography, tone, visual guidelines—and a full solution launch campaign with PLG activation, content marketing, and marketing automation ready for implementation.

Your brand is how customers perceive you. Your launch plan is how they discover you. Both must align with your product experience, resonate with your persona, and support your PLG strategy. We're not designing for design's sake—we're engineering brand and launch as growth levers.

Product Concept

I apply brand identity design principles combined with Product-Led Growth launch strategy, content marketing frameworks, and marketing automation planning. The core insight: brand and launch aren't afterthoughts—they're strategic drivers of acquisition and activation.

The brand identity covers:

Visual Identity: Logo, color palette, typography, iconography, imagery style
Voice & Tone: Messaging principles, writing style, personality traits
Brand Guidelines: Usage rules, examples, dos and don'ts

The launch plan covers:

PLG Activation: How free/trial users discover value and convert
Content Marketing: Blog posts, guides, videos, social content aligned with customer journey
Marketing Automation: Email sequences, in-app messaging, lifecycle campaigns
Channel Strategy: Where and how to reach your persona with maximum efficiency
Launch Timeline: Pre-launch, launch day, post-launch milestones

Everything ties back to your consumption chain DOS. The brand should reduce friction in Acquire and Activate jobs. The launch plan should trigger viral loops, aha moments, and habit formation (Hook Model).

This step is complete only when you have a compelling brand identity (logo, colors, tone, guidelines) and a full solution launch campaign with PLG activation, content marketing, and marketing automation ready for implementation.

Actions

I translate the intent of building brand and launch strategy into clear, testable criteria.
I apply brand identity design and PLG launch frameworks to generate comprehensive deliverables.
I ensure brand identity resonates with persona and supports product experience.
I design launch plan to activate PLG loops, trigger aha moments, and enable viral growth.
I map content marketing to customer journey stages and consumption jobs.
I configure marketing automation sequences aligned with lifecycle and conversion goals.
I pressure-test the result against real constraints and user evidence.
I document the decision trail so downstream steps stay aligned.

Deliverables

Compelling brand identity covering logo concepts, color palette, typography system, iconography, imagery style, voice and tone guidelines, messaging principles, and brand usage rules.
Full solution launch campaign including PLG activation strategy, content marketing calendar mapped to customer journey, marketing automation sequences (email, in-app, lifecycle), channel strategy with reach and conversion targets, and launch timeline with pre-launch, launch day, and post-launch milestones.

These deliverables ensure your product doesn't just work—it gets discovered, adopted, and shared. Brand and launch are growth engines, not decoration.

Phase 3: Build Readiness

You've defined what to build and why. Now we translate strategy into executable specifications: Product Requirements Document (PRD), Product Requirements Prompt (PRP), metrics hierarchy, information architecture, UX flows, UI design system, and technical architecture. This phase is the handoff from strategy to execution.

Step 13: Product Requirements Prompt (PRP) & Product Requirements Document (PRD)

Intro

Requirements are where ideas meet implementation. This step generates two critical artifacts: a Product Requirements Prompt (PRP) designed for autonomous implementation by agentic coders, and a Product Requirements Document (PRD) for human designers and engineers to understand the WHY and WHAT before tackling the HOW.

The PRP is structured input optimized for AI builders—context-rich, specification-complete, and executable without supervision. The PRD is strategic context for stakeholders—business case, market context, functional requirements, success criteria. Together, they ensure everyone (human and AI) has what they need to execute with clarity.

Product Concept

I apply Product Requirements Document methodology combined with Product Requirements Prompt design optimized for agentic coder execution. The core insight: different audiences need different specifications, but both need ruthless clarity.

The PRD covers:

Executive Summary: What are we building and why?
Business Case: Market opportunity, competitive landscape, strategic rationale
User Context: Persona, JTBD, pain points, desired outcomes
Functional Requirements: What the product must do
Success Metrics: How we measure success
Constraints: Technical, legal, resource limitations
Dependencies: What needs to exist first

The PRP covers:

Product Context: Persona, JTBD, OKRs, roadmap summary
Feature Specifications: Detailed functional and technical specs per feature
UX Guidelines: User experience principles and flow requirements
Technical Constraints: Platform, stack, performance requirements
Success Criteria: Acceptance criteria and validation tests
Implementation Guidance: Build sequence, integration points, edge cases

Both documents are comprehensive, traceable, and executable. The PRD enables alignment and strategic understanding. The PRP enables autonomous implementation.

This step is complete only when you have a full Silicon Valley-grade Product Requirements Prompt designed for autonomous implementation by agentic coders, creating a professional product without additional docs or human supervision, AND a full SV-grade PRD with functional requirements, business context, and strategic foundation enabling designers and engineers to translate WHY/WHAT into HOW.

Actions

I translate the intent of requirements documentation into clear, testable criteria.
I apply PRD methodology to generate strategic PM-level requirements for stakeholders.
I apply PRP design to generate agentic coder-ready specifications with full context and executable detail.
I ensure both documents align with all prior artifacts (OKRs, persona, JTBD, DOS, roadmap, features, BMC, brand).
I validate completeness, traceability, and executability.
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_product_reqs_prompt_prp: Full SV-grade Product Requirements Prompt designed for autonomous implementation by agentic coder platforms, creating professional products without additional documentation or human supervision.
a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/13_product_reqs_doc_prd: Strategic PM-level PRD with business case, market context, high-level requirements for stakeholders, enabling designers and engineers to translate WHY/WHAT into HOW.

These deliverables are your handoff to execution. The PRP enables AI builders to ship autonomously. The PRD enables human teams to align strategically. Both ensure clarity, traceability, and quality.

Step 14: Track What Matters (Value Tree & Metrics)

Intro

If you can't measure it, you can't improve it. This step builds your metrics hierarchy using the Value Tree framework—connecting your North Star Metric to supporting metrics, input metrics, and implementation signals that guide prioritization and development.

You'll walk away with a complete metrics framework, weighted priorities, and technical implementation guidance for agentic coder development. No vanity metrics, no guesswork—just the signals that matter.

Product Concept

I apply OKR design, Outcome-Driven Roadmapping, and Value Tree & Metrics methodology. The core insight: metrics are hierarchical. Your North Star Metric (NSM) sits at the top, driven by supporting metrics, which are driven by input metrics, which are driven by user actions you can instrument and optimize.

The Value Tree structure:

North Star Metric (NSM): The one metric that best captures core product value
Supporting Metrics: Secondary OKR metrics that drive the NSM
Input Metrics: Leading indicators you can influence directly
Implementation Signals: User actions, events, and behaviors you instrument in code

Each metric gets a weight (importance to NSM), a target (what success looks like), and instrumentation guidance (how to measure it). The tree structure makes prioritization obvious: optimize the inputs that move supporting metrics that drive the NSM.

I also provide technical implementation framework for agentic coder development—event schemas, tracking specifications, dashboard requirements, and alerting logic.

This step is complete only when you have a full metrics hierarchy with weighted priorities, North Star Metric with secondary OKR metrics, and implementation signals for strategic roadmap decision-making and agentic coder development.

Actions

I translate the intent of defining metrics into clear, testable criteria.
I apply Value Tree methodology to build hierarchical metrics structure from NSM down to implementation signals.
I weight each metric based on impact to NSM and strategic importance.
I define targets, measurement methods, and instrumentation requirements.
I provide technical implementation framework for agentic coder development.
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 with complete metrics hierarchy, global weights, NSM integration, and secondary metrics mapping.
a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/12b_metrics_vtree: PM artifact showing complete metrics hierarchy with North Star Metric, supporting metrics, input metrics, implementation signals, weights, targets, and technical implementation framework for agentic coder development.

These deliverables ensure you measure what matters. The Value Tree gives you strategic clarity. The implementation framework gives your coders executable instrumentation specs.

Step 15: Organize Your Product Experience (Information Architecture)

Intro

Features don't organize themselves. This step designs your product's Information Architecture (IA)—navigation structure, content organization, page hierarchy, and taxonomy. The goal: reduce cognitive load, make features discoverable, and guide users through the product experience intuitively.

Good IA is invisible—users don't think about it, they just find what they need. Bad IA is friction—users get lost, frustrated, and leave. We're designing the former.

Product Concept

I apply Information Architecture methodology combined with Technical Architecture Design and Agentic Build Operations. The core insight: IA isn't just design—it's the skeleton that supports the entire product experience. It must be optimized for end-users AND implementable by agentic coders.

The IA covers:

Navigation Structure: Top-level menu, sub-navigation, mobile navigation
Content Organization: Page hierarchy, section grouping, taxonomy
User Flows: How users move through the product to accomplish jobs
Discoverability: Search, filters, recommendations, shortcuts
Responsive Design: How IA adapts across devices and screen sizes
Technical Specs: URL structure, routing logic, state management

I tier the IA based on user proficiency (beginner, intermediate, advanced, expert) and ensure it's implementable by agentic coders matching your creator proficiency level. The IA must support the consumption chain jobs (especially Activate, Onboard, Support, Engage) and make features discoverable in the context of user workflows.

This step is complete only when you have intelligent IA optimized for solution end-users and implementable by agentic coders matching creator proficiency, with tier-appropriate navigation, content organization, and technical specs.

Actions

I translate the intent of organizing product experience into clear, testable criteria.
I apply Information Architecture principles to design navigation, content organization, and user flows.
I ensure IA supports consumption chain jobs and feature discoverability.
I tier IA based on user proficiency and creator proficiency constraints.
I provide technical specifications for URL structure, routing, and state management.
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}}/15_navigation_ia: Product Design artifact showing complete IA foundation with navigation structure, content organization, page hierarchy, user flow guidance, discoverability mechanisms, responsive design specifications, and technical architecture and implementation specs for the entire roadmap.

This deliverable is your product's skeleton. It structures the experience, guides users, and provides the foundation for all UX and UI work that follows.

Step 16: User Experience Flows (UX)

Intro

Features need flows. This step designs the UX flows for every feature in your roadmap—mapping the user's path from entry to outcome, orchestrating emotional journey, designing Hook loops, and engineering aha moments.

Great UX flows are invisible highways guiding users to success. Bad UX flows are mazes where users get lost and give up. We're building the former—optimized for end-user experience and implementable by agentic coders with context-rich technical specs.

Product Concept

I apply Solution Ideation and Synthesis, User Experience Flow Design, and Agentic Build Operations. The core insight: UX flows aren't just wireframes—they're behavioral scripts that guide users through jobs, trigger emotions, build habits, and create memorable moments.

Each UX flow covers:

Entry Point: How users start (from where, with what context)
Steps: Sequential actions users take to accomplish the job
Decision Points: Branches, conditionals, user choices
Success State: What completion looks like
Error States: What happens when things go wrong
Emotional Journey: How users feel at each step (frustration, confusion, confidence, delight)
Hook Loops: Trigger → Action → Variable Reward → Investment (Nir Eyal)
Aha Moments: The instant users realize value
Technical Specs: State management, API calls, validations, animations

I ensure flows support consumption chain jobs (especially Activate, Onboard, Engage) and create measurable value aligned with your Value Tree metrics. Flows are implementable by "vibe coders" (AI builders that understand intent and context) with sufficient detail to execute without ambiguity.

This step is complete only when you have full UX flows for features in the selected roadmap, optimized for end-user experience and implementable by agentic coders with context-rich technical specs.

Actions

I translate the intent of designing UX flows into clear, testable criteria.
I apply UX Flow Design to map user paths from entry to outcome for each feature.
I orchestrate emotional journey across flows to minimize friction and maximize delight.
I design Hook loops (Trigger → Action → Variable Reward → Investment) to build habits.
I engineer aha moments where users realize value instantly.
I provide context-rich technical specs for state management, APIs, validations, and animations.
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_[%feat_id%]_flow_[%unique_feat_name%]: UX Flow for each feature showing emotional journey orchestration, Hook loops (Trigger → Action → Reward → Investment), aha moments, and implementable specs with entry points, sequential steps, decision points, success states, error states, and technical specifications.

These deliverables are your behavioral blueprints. Every flow is designed for success, instrumented for measurement, and specified for implementation. Users won't get lost—they'll get guided to outcomes that matter.

Step 17: User-Interface Design (Design System & Component Library)

Intro

Flows need pixels. This step builds your Design System and Component Library—the atomic building blocks (buttons, inputs, cards, modals) and composition rules that ensure visual consistency, accessibility, and implementation velocity across your entire product.

A great design system is a force multiplier. Designers compose interfaces faster. Developers build components once and reuse them everywhere. Users experience consistency that builds trust and reduces cognitive load. We're building that system—comprehensive, accessible, and ready for agentic coder execution.

Product Concept

I apply UI System and Visual Design methodology combined with atomic design principles and accessibility standards. The core insight: design systems are leverage—invest upfront to move fast forever.

The Design System covers:

Design Tokens: Colors, typography, spacing, shadows, borders (the variables)
Atomic Components: Buttons, inputs, checkboxes, toggles, icons (the atoms)
Molecular Components: Form groups, cards, list items (combinations of atoms)
Organism Components: Headers, footers, navigation, modals (complex combinations)
Templates: Page layouts and composition patterns
Accessibility Specs: WCAG compliance, keyboard navigation, screen reader support, color contrast
Responsive Behavior: How components adapt across breakpoints
Implementation Specs: Component APIs, props, states, variants

I also generate specific UI wireframes for each feature—HTML or HTML+SVG wireframes extracted from feature specs, IA, design system, and UX flows. Each wireframe is versioned and implementation-ready.

This step is complete only when you have a full design system with component specs ready for implementation, ensuring consistency, accessibility, and velocity.

Actions

I translate the intent of designing UI system into clear, testable criteria.
I apply UI System and Visual Design to generate comprehensive design system.
I define design tokens (colors, typography, spacing, shadows, borders).
I specify atomic, molecular, and organism components with props, states, and variants.
I ensure WCAG accessibility compliance across all components.
I define responsive behavior across breakpoints.
I generate feature-specific UI wireframes (HTML or HTML+SVG) extracted from feature specs, IA, design system, and UX flows.
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}}/17a_design_system: Product Design artifact showing complete design system foundation with atomic components, design tokens, accessibility specs, responsive behavior, and implementation guidance for the entire roadmap.
a3_product_design/{{mm_session_persona}}/{{mm_session_roadmap}}/17b_[%feat_id%].v[YY]_ui_[%unique_ui_name%]: HTML or HTML+SVG wireframe version for each UI interface (screen, dialog, component) extracted from feature specs, IA, design system, and UX flows.

These deliverables ensure visual consistency and implementation velocity. The design system is your UI library. The wireframes are your implementation blueprints.

Step 18: Technical Architecture Design

Intro

Great UX needs solid infrastructure. This step designs your technical architecture—system design, data models, API contracts, infrastructure, security, performance, and scalability decisions that enable your product to work reliably at scale.

Technical architecture isn't just for engineers—it's strategic. The right architecture decisions enable speed, flexibility, and growth. The wrong ones create technical debt, performance bottlenecks, and scaling nightmares. We're making the right ones—robust, scalable, and ready for implementation.

Product Concept

I apply Technical Architecture Design methodology covering system design, database modeling, API design, infrastructure planning, security architecture, and performance optimization. The core insight: architecture is about tradeoffs—optimize for the constraints that matter most (speed, scale, cost, complexity, security).

The Technical Architecture covers:

System Design: High-level components, services, integrations
Data Models: Entities, relationships, schemas, migrations
API Contracts: Endpoints, request/response formats, authentication, rate limiting
Infrastructure: Hosting, database, storage, CDN, caching
Security: Authentication, authorization, data encryption, compliance
Performance: Load times, query optimization, caching strategy, CDN usage
Scalability: How the system handles growth in users, data, and traffic
Monitoring & Logging: Observability, error tracking, performance monitoring
Deployment: CI/CD pipeline, staging environments, rollback strategy

I ensure the architecture supports your OKRs, handles expected load, meets security requirements, and can be implemented by agentic coders with the technical specs provided.

This step is complete only when you have a robust technical architecture with 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 comprehensive system design.
I define system components, services, and integration points.
I model data entities, relationships, and schemas.
I design API contracts with endpoints, authentication, and rate limiting.
I plan infrastructure stack (hosting, database, storage, CDN, caching).
I specify security architecture (authentication, authorization, encryption, compliance).
I optimize for performance (load times, queries, caching, CDN).
I design for scalability (handling growth in users, data, traffic).
I configure monitoring, logging, and deployment pipelines.
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}}/18_technical_design: Technical architecture deliverables covering system design, data models, API contracts, infrastructure stack, security architecture, performance optimization, scalability plan, monitoring and logging configuration, and deployment pipeline specifications.

This deliverable ensures your product is built on solid foundations. The architecture is documented, validated, and ready for implementation by technical teams or agentic coders.

Phase 4: Execution & Handoff

Strategy is done. Design is done. Architecture is done. Now we translate everything into execution-ready prompts for professional AI coders. This phase generates the EPIC breakdown, setup prompts, build prompts, and operations manual that enable autonomous implementation at 10X speed.

Step 19: Generate Tasks for Professional AI Coders (EPIC & Task Breakdown)

Intro

Agentic coders are powerful but require clear, sequenced, context-rich instructions. This step breaks down your product into an EPIC (high-level implementation plan) and intelligent task breakdown optimized for modern agentic coder execution and sequential implementation.

Each task is scoped for a single coder session, sequenced for dependencies, and enriched with context so coders can execute autonomously without getting stuck or making wrong assumptions.

Product Concept

I apply Epic and Task Breakdown methodology combined with Agentic Build Operations. The core insight: decomposition enables parallel execution and reduces ambiguity. Clear tasks with context enable autonomous execution without supervision.

The EPIC breakdown covers:

Epic Overview: High-level implementation phases and milestones
Task List: Individual tasks scoped for single coder sessions
Sequencing: Dependency order (what must happen first)
Context: Background, rationale, constraints for each task
Acceptance Criteria: How to know the task is done correctly
Estimated Effort: Time estimates factoring in AI acceleration (10X speed)

I ensure tasks are:

Atomic: Each task is independently executable
Sequenced: Dependencies are clear and respected
Contextual: Sufficient background to execute without guesswork
Testable: Clear acceptance criteria for validation

Tasks reference all source artifacts: product scorecard, product brief, PRD, PRP, feature specs, design system, mm_solutions_yaml. This ensures coders have complete context without hunting for information.

This step is complete only when you have a full EPIC analysis with intelligent task breakdown optimized for modern agentic coder execution and sequential implementation.

Actions

I translate the intent of generating tasks into clear, testable criteria.
I apply Epic and Task Breakdown to decompose product into sequential, executable tasks.
I ensure each task is atomic, scoped for single session, and enriched with context.
I sequence tasks to respect dependencies and enable parallel execution where possible.
I define acceptance criteria and estimated effort for each task.
I reference all source artifacts (scorecard, brief, PRD, PRP, features, design system, solutions YAML).
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_delivery_plan_prompt: EPIC and task breakdown plan with sequencing, context, acceptance criteria, effort estimates, and references to all source artifacts (product scorecard, product brief, PRD, PRP, feature specs, design system, mm_solutions_yaml). Optimized for professional agentic AI coders.

This deliverable is your execution roadmap. It translates strategy into action, decomposed into tasks that agentic coders can execute autonomously at 10X speed.

Step 20: Setup Instructions for Professional AI Coders

Intro

Before building features, coders need to set up the environment—initialize projects, configure tooling, install dependencies, set up databases, configure authentication, deploy infrastructure. This step generates platform-specific setup prompts ready for agentic coder execution.

Each setup task is a standalone prompt with context, instructions, acceptance criteria, and validation steps. Coders execute them sequentially to establish the foundation for feature development.

Product Concept

I apply Agentic Build Operations to generate platform-specific setup prompts. The core insight: setup is make-or-break—if the foundation is shaky, every feature build compounds the problems. Get setup right once, execute reliably forever.

Setup prompts cover:

Project Initialization: Create project structure, configure build tools
Dependency Installation: Install frameworks, libraries, tools
Database Setup: Create schemas, run migrations, seed data
Authentication Configuration: Set up auth providers, session management, security
Infrastructure Deployment: Provision hosting, storage, CDN, monitoring
Environment Configuration: Set environment variables, secrets, API keys
Testing Framework: Configure unit tests, integration tests, E2E tests
CI/CD Pipeline: Set up automated build, test, deploy workflows

Each prompt is self-contained with context, step-by-step instructions, expected outputs, and validation criteria. Coders execute them in sequence to build the foundation.

This step is complete only when you have platform-specific setup prompts ready for agentic coder execution.

Actions

I translate the intent of setup instructions into clear, testable criteria.
I apply Agentic Build Operations to generate platform-specific setup prompts.
I ensure each prompt is self-contained with context, instructions, outputs, and validation.
I sequence setup tasks to respect dependencies (e.g., install dependencies before database setup).
I reference technical architecture specs to ensure alignment.
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_setup_[%task_name%]: Platform-specific setup prompt for each individual setup task, complete with context, step-by-step instructions, expected outputs, validation criteria, and sequencing guidance.

These deliverables ensure coders can set up the environment correctly without supervision. The foundation is solid, validated, and ready for feature development.

Step 21: Build Instructions for Professional AI Coders

Intro

Setup is done. Now it's time to build features. This step generates platform-specific build prompts for every development task in your EPIC breakdown—ready for agentic coder execution.

Each build prompt is a standalone instruction set with context, technical specs, acceptance criteria, and validation tests. Coders execute them sequentially (respecting dependencies) to ship features autonomously.

Product Concept

I apply UI System and Visual Design combined with Agentic Build Operations. The core insight: build prompts must balance autonomy with control—give coders enough context to execute without supervision, but enough constraints to ensure quality and consistency.

Build prompts cover:

Feature Context: What the feature does, why it matters, which DOS it solves
Technical Specs: Component structure, API contracts, data flows, state management
Implementation Guidance: Step-by-step build instructions, code examples, edge cases
Design Specs: UI components, styles, responsive behavior, accessibility requirements
Acceptance Criteria: How to validate the feature works correctly
Test Cases: Unit tests, integration tests, user acceptance scenarios

Each prompt references relevant artifacts: feature spec, UX flow, UI wireframe, design system, technical architecture, API contracts. Coders have everything they need in one place.

This step is complete only when you have platform-specific build prompts ready for agentic coder execution.

Actions

I translate the intent of build instructions into clear, testable criteria.
I apply Agentic Build Operations to generate platform-specific build prompts for each task.
I ensure each prompt includes feature context, technical specs, implementation guidance, design specs, acceptance criteria, and test cases.
I reference all relevant artifacts (feature specs, UX flows, UI wireframes, design system, technical architecture).
I sequence build tasks to respect dependencies identified in EPIC breakdown.
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_build_{{task_id}}_{{epic_id}}_[%task_name%]: Platform-specific build prompt for each individual development task, complete with feature context, technical specs, implementation guidance, design specs, acceptance criteria, test cases, and references to all relevant artifacts.

These deliverables enable autonomous feature development. Coders execute prompts sequentially, validate with acceptance criteria, and ship features that match specs without supervision.

Step 22: AI Coder Operations Manual & Next Steps

Intro

Welcome to the product summit. You made it! This is the "you've shipped it" chapter—here's the manual for running, fixing, and growing what you sweated over.

Unlike 90% of handoffs, this one won't get you lost in outdated docs. My mission: you (and any future AI coder) will actually know how to keep your product alive, smart, and ready for the next big pivot—without needing me in the room.

Product Concept

This isn't just a wrap-up—it's the passing of the secret scroll unlocking product autonomy. I hand over a tailored operations manual: your product's blueprint, straight from architecture through deployment, sprinkled with dev best practices and all my "do this, DON'T do that" footnotes.

Think of it as a living knowledge base, not a tombstone. Every lesson, every technical sidestep, every answer to "why the heck did we build it this way?"—all sealed in these pages. And, because I like to celebrate: I'll include a full summary of your victories. Every validated outcome, insight, and fateful architecture pick gets a spot on the trophy shelf.

Oh, and I tack on a list of the good stuff still cooking—future features, experiments to try, debts to pay down, open questions begging to be solved. You won't stall after launch—this is how you sprint right past your competition.

The operations manual covers:

Product Overview: What you built, for whom, why it matters
Architecture Summary: System design, data models, infrastructure, security
Development Workflow: How to add features, run tests, deploy changes
Operational Runbooks: How to monitor, troubleshoot, scale, secure
Knowledge Base: Rationale for key decisions, lessons learned, gotchas avoided
Next Steps: Future roadmap, experiments to run, technical debt to address, growth opportunities

The completion summary covers:

Milestone Reel: What you accomplished, validated outcomes, key insights
Victory Lap: OKRs achieved, customer value delivered, business model validated
Where to Go Next: Immediate next steps, future phases, growth paths

Actions

I round up every doc, prompt, and explainer generated along the journey.
I distill lessons, feature logics, dashboards, and architecture doodles into a single neat manual.
I prep a summary of "here's what we did, for whom, why it mattered"—perfect for stakeholders or future you.
I flag every next-step, open question, and growth path in a format even Big Tech PMs can't misread.
I make sure the manual survives longer than my last attempt at growing houseplants.

Deliverables

a4_product_delivery/{{mm_session_persona}}/22_operations_manual: The all-in-one operations guide—technical blueprints, rationale, "in case of doubt, open here" diagrams, development workflow, operational runbooks, knowledge base, and next steps.
a5_conclusion/23_completion_summary: Milestone reel, victory lap summary, where to go next. Startup amnesia-proof.

You did it. Now go build, ship, and scale with velocity and confidence. Welcome to the fast lane.

Intro​

Hyperboost Formula​

What is the Hyperboost Formula?​

The DNA: Build-Measure-Learn—Relentlessly​

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

Why Does the Hyperboost Formula Matter?​

Anatomy of the Hyperboost Journey​

Core Principles Guiding Every Step​

Process Overview​

Phase 1: Customer & Solution Discovery​

Step 00: Idea Gathering​

Intro​

Product Concept​

Actions​

Deliverables​

Step 01: Find Your Product/Business Idea​

Intro​

Product Concept​

Actions​

Deliverables​

Step 02: Product Opportunity Assessment (POA)​

Intro​

Product Concept​

Actions​

Deliverables​

Step 03: Set Your Goals & Target Market (OKRs)​

Intro​

Product Concept​

Actions​

Deliverables​

Step 04: Your Dream Customer (HXC & ICP)​

Intro​

Product Concept​

Actions​

Deliverables​

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

Intro​

Product Concept​

Actions​

Deliverables​

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

Intro​

Product Concept​

Actions​

Deliverables​

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

Intro​

Product Concept​

Actions​

Deliverables​

Step 08: Product Roadmap (MVP ODI Roadmap)​

Intro​

Product Concept​

Actions​

Deliverables​

Step 09: Solution Opportunities (OST)​

Intro​

Product Concept​

Actions​

Deliverables​

Step 10: Ideate Features​

Intro​

Product Concept​

Actions​

Deliverables​

Phase 2: Strategy & Solution Design​

Step 11: Business Strategy (BMC)​

Intro​

Product Concept​

Actions​

Deliverables​

Step 12: Brand Style Guide & Launch Plan​

Intro​

Product Concept​

Actions​

Deliverables​

Phase 3: Build Readiness​

Step 13: Product Requirements Prompt (PRP) & Product Requirements Document (PRD)​

Intro​

Product Concept​

Intro

Hyperboost Formula

What is the Hyperboost Formula?

The DNA: Build-Measure-Learn—Relentlessly

Integration of Methods: Lean Startup, Empathy, and AI

Why Does the Hyperboost Formula Matter?

Anatomy of the Hyperboost Journey

Core Principles Guiding Every Step

Process Overview

Phase 1: Customer & Solution Discovery

Step 00: Idea Gathering

Intro

Product Concept

Actions

Deliverables

Step 01: Find Your Product/Business Idea

Intro

Product Concept

Actions

Deliverables

Step 02: Product Opportunity Assessment (POA)

Intro

Product Concept

Actions

Deliverables

Step 03: Set Your Goals & Target Market (OKRs)

Intro

Product Concept

Actions

Deliverables

Step 04: Your Dream Customer (HXC & ICP)

Intro

Product Concept

Actions

Deliverables

Step 05: Customer Journey to Solve Problem (JTBD & Job Map)

Intro

Product Concept

Actions

Deliverables

Step 06: Customer Pain/Gain Analysis (DOS)

Intro

Product Concept

Actions

Deliverables

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

Intro

Product Concept

Actions

Deliverables

Step 08: Product Roadmap (MVP ODI Roadmap)

Intro

Product Concept

Actions

Deliverables

Step 09: Solution Opportunities (OST)

Intro

Product Concept

Actions

Deliverables

Step 10: Ideate Features

Intro

Product Concept

Actions

Deliverables

Phase 2: Strategy & Solution Design

Step 11: Business Strategy (BMC)

Intro

Product Concept

Actions

Deliverables

Step 12: Brand Style Guide & Launch Plan

Intro

Product Concept

Actions

Deliverables

Phase 3: Build Readiness

Step 13: Product Requirements Prompt (PRP) & Product Requirements Document (PRD)

Intro

Product Concept