Toolsday

November 10, 2026 · Last updated on November 5, 2026

AI Toolsday: Real AI, Real Agile, Real Workflows

# Continuous Improvement

Practical AI workflows for Agile teams

Pressure-Test Your Epic Value Statement Before LPM

You’ve shepherded an Epic through the Funnel into the Review stage. The business need feels urgent, the vision seems clear, and the draft Epic Hypothesis Statement is filled out.

Then you bring it to Lean Portfolio Management (LPM).

Instead of a smooth approval to move into Analysis, the conversation grinds to a halt:

“How do we actually measure if this is working before we spend $800k?”

“Isn’t this leading indicator just describing delivery progress rather than business impact?”

“What makes this an Epic instead of three unrelated Features bundled together?”

In SAFe, Epics represent substantial investments requiring significant analysis and governance. When Epic Value Statements are vague, metrics are lagging, or scopes are inflated, proposals stall in portfolio reviews.

This week’s workflow uses AI as a critical evaluator and institutional skeptic. Before stepping into the room with LPM, you'll put your Epic through a rigorous stress test to challenge your assumptions, sharpen your leading indicators, and isolate the smallest viable experiment.

📌 Before You Start

The AI tools featured in this workflow are examples, not requirements. Every organization operates under specific data governance policies, approved platforms, and Lean Portfolio guardrails.

The goal of AI Toolsday is to share practical workflows you can adapt using the tools available to you—whether that is Microsoft Copilot, Claude, ChatGPT Enterprise, or Google Gemini.

Focus on the workflow, not the tool.

Enterprise Data Tip: Epics often involve strategic corporate roadmaps, competitive advantages, or forward-looking financial targets. Never paste proprietary market strategy, customer PII, or unreleased commercial IP into public AI models. Use sanitized or abstracted terminology if using non-enterprise instances.

🛠️ Tools Used

Claude (or your preferred analytical LLM):

Why it’s here: Claude excels at structured critique, spotting subtle logical fallacies, and questioning unverified assumptions without defaulting to enthusiastic agreement.

ChatGPT Enterprise (or Microsoft Copilot): Why it’s here: Once gaps are flagged, ChatGPT is ideal for quickly refactoring concise, testable Lean Business Case sections and validation spike definitions.

Your Enterprise LPM Tool (Jira Align, Targetprocess, or Kanban Board): Why it’s here: The system of record where your validated Epic Hypothesis Statement, Non-Functional Requirements (NFRs), and MVP definitions ultimately live.

⚙️ How It Works

Step 1: Lay out the raw Epic Hypothesis Statement

Start with your draft Epic using the standard SAFe format:

For [target customers/users]

Who [do something or experience a pain point]

The [solution/initiative name]

Is a [solution category]

That [delivers core value or key capability]

Unlike [current state, competitor, or alternative]

Our solution [provides key differentiator or innovation].

Include your initial draft of Business Outcomes, Leading Indicators, and any known Non-Functional Requirements (NFRs).

Step 2: Unleash the "LPM Skeptic" in Claude

Instead of asking AI to “make this sound better,” instruct it to act as an uncompromising Lean Portfolio governance reviewer.

Ask Claude to evaluate:

The Problem Definition: Is the problem clearly distinct from the proposed solution?

Scope Inflation: Does this describe a single focused outcome, or is it an unwieldy umbrella program disguised as an Epic?

Causality Gaps: Does the statement prove why this specific solution is the best way to hit the outcome?

Hidden Dependencies: What architectural or operational foundations are being assumed without explicit Enablers?

Step 3: Interrogate your Leading Indicators

The most common failure in an Epic Value Statement is confusing a leading indicator with an output milestone.

Milestone: "Roll out the new portal to 100% of branch users by Q3." (This measures activity, not economic return.)

Leading Indicator: "Within 30 days of launch, 25% of customers in pilot region complete digital onboarding without calling support." (This measures early behavior that validates the hypothesis.)

Prompt the AI to inspect your indicators: “Which of these metrics actually give early proof that our business hypothesis is true, and which ones merely measure that we delivered code?”

Step 4: Refactor the Minimum Viable Product (MVP) and Validation Spikes

Bring Claude's critical evaluation into ChatGPT to restructure the Lean Business Case components.

Ask ChatGPT to draft:

A tightened, punchy Epic Hypothesis Statement.

Two truly predictive leading indicators with clear measurement methods.

Candidate Enabler Spikes or low-cost learning experiments needed to validate technical or market uncertainty before committing full implementation capacity.

Step 5: Human validation with your Epic Owner and System Architect

AI does not write portfolio policy, fund value streams, or decide architectural viability.

Take the AI’s critique and revised draft back to your Epic Owner, Enterprise Architect, and Product Managers. Evaluate the AI's challenges together:

Are the surfaced risks valid in our organizational context?

Can our telemetry systems actually collect the proposed leading indicators?

Are we prepared to pivot or stop if the leading indicators fail during the MVP phase?

💡 Why Agile Pros Care

In Lean Portfolio Management, capacity and funding are finite. Every hour an Epic lingers in the Portfolio Kanban due to ambiguous value propositions is an hour of delayed economic feedback.

Running this workflow:

Protects ART capacity: It prevents bloated, poorly scoped initiatives from entering the backlog under the guise of an "urgent" Epic.

Elevates the LPM conversation: Instead of spending review meetings debating basic definitions and fuzzy terminology, the team can focus on strategic alignment, investment horizons, and risk tolerance.

Embeds Lean-Agile metrics early: It forces the organization to define how value will be validated early through an MVP, rather than measuring success purely on whether a project was completed on schedule.

💬 Prompt to Copy

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You are an experienced Lean Portfolio Management (LPM) advisor and SAFe Practice Consultant (SPC).

Your goal is to critically pressure-test an Epic Hypothesis Statement before it is submitted to the Portfolio Review and Analysis stages.

Do not simply validate or polish my wording. Act as an institutional skeptic focused on Lean economics, fast feedback loops, and objective business outcomes.

Here is the draft Epic information:

[EPIC TITLE]:

[TARGET CUSTOMER/USER]:

[CORE PROBLEM/PAIN POINT]:

[PROPOSED SOLUTION]:

[EXPECTED BUSINESS OUTCOMES]:

[PROPOSED LEADING INDICATORS]:

[KNOWN CONSTRAINTS / NFRs]:

Please provide a critical evaluation addressing the following areas:

1. Hypothesis Rigor & Scope Check:

- Is this focused on a specific strategic outcome, or does it look like a collection of features bundled into an umbrella epic?

- What unstated assumptions are we making about customer behavior or technical viability?

2. Leading Indicator Audit:

- Evaluate each proposed leading indicator. Identify which ones merely measure output/implementation milestones versus those that measure early, quantifiable feedback on the business hypothesis.

- Suggest 2 alternative, highly measurable leading indicators that can be observed during the MVP stage.

3. The "Cost of Ignorance" & MVP Definition:

- What is the smallest viable slice of this Epic (MVP) that would allow us to validate or invalidate the hypothesis?

- What Enabler or Discovery Spike should we run to de-risk this initiative before committing full ART capacity?

4. Executive Skeptic Questions:

- Provide 4 tough, realistic questions an LPM committee member or Business Owner will likely ask about this Epic.

Distinguish clearly between factual critiques based on my input and hypotheses you are raising for the team to investigate.

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✅ Try It This Week

Take an Epic currently sitting in your Portfolio Kanban, backlog, or intake queue.

Isolate just the Expected Business Outcomes and Proposed Leading Indicators. Run them through the prompt above and ask:

“Which of these metrics can be measured during the MVP rollout, and which ones cannot be measured until 100% of the solution is deployed?”

If your leading indicators can only be measured after full deployment, work with your team to identify one behavioral signal you can observe within the first 30 days of initial release.

💬 Continue the Conversation

When Epics stall during Portfolio Review in your organization, what is usually the root cause?

Vague or unmeasurable business outcomes?

Disagreement on how to define the MVP?

Hidden architectural dependencies?

Debates over portfolio budget and capacity?

🤝 AI Toolsday Tip

AI can generate plausible-sounding business metrics and leading indicators, but it doesn't know whether your systems have the instrumentation to track them.

Treat every AI-suggested leading indicator as a candidate hypothesis. Before presenting a metric to LPM, confirm with your engineering teams and architects that the telemetry, events, or feedback loops required to measure it can realistically be built into the MVP.

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