Steve Blank Lean LaunchPad – The Next Generation

You’re studying a four-part collection on how AI has impacted our Lean LaunchPad class and what we did about it.

Part 1: The Year AI Came For Us
Part 2: AI Killed the MVP – Long Live the IUP
Part 3: The World Outside the Classroom Changed, The Class Didn’t
This submit: Lean LaunchPad – The Next Generation

Lean LaunchPad – The Next Generation
While AI accelerates product improvement and buyer discovery, it doesn’t speed up understanding, proof or perception. Teams nonetheless want to find who has the issue, how painful it’s, who controls the funds and knowledge, what consequence counts as success, what failure is tolerable, how the product enters the workflow, and why a buyer will select a startup over dozens of quick followers or internally constructed options.

Here’s how we modified the course design to embrace the pace of AI whereas instructing college students to first assume deeply about their enterprise, then act rapidly to construct it.

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It took all summer season and plenty of recommendations from the Stanford Lean LaunchPad and Hacking for Defense instructors, however on the finish of our personal discovery, we concluded that our redesigned LLP class wanted to:

• Double down within the entrance finish of the category on the rigor of understanding Stakeholders, Problems, Hypotheses and Connections
• Double down on AI for its speedy improvement/deployment, time-to-market pace up and skill to remodel total industries
• Replace the MVP as proof of the Value Proposition with “Snippets” (Using a small portion of the preliminary untested product to check a value-proposition)
• Replace the MVP as proof for testing the opposite components of the Business Model Canvas with “Minimal Tested Canvas” exams.
• Make Product/Market Fit targets class particular
• Change the category tempo to maneuver even sooner
• Use Design Partners as proof of Customer Validation within the second half of the category
• Change the language to embrace new class ideas

What’s the Same?
The redesigned class will hold team-based, experiential studying, Business Model and Value Proposition Canvases, Customer Development, speculation testing, discipline interviews, weekly proof critiques, validating the issue earlier than validating the answer, permission to pivot and time stress.

We’ll Start with a New Glossary
Renaming isn’t only a semantic hack. Language issues. It shapes behaviors and actions. In the chaotic and unsure seek for a enterprise mannequin, being exact with college students helps them perceive in the event that they’ve made progress.

Here’s the brand new language we intend to make use of within the revised Lean LaunchPad class.

Stakeholders: customers, clients, influencers, decision-makers, financial patrons, regulators, knowledge homeowners, safety groups, saboteurs, and many others. Anyone influencing the adoption of your product/service.

Initial Untested Product (IUP): For the primary class assembly, this might be an AI-created product/digital twin which will resemble a whole answer however has not been validated with clients or stakeholders.

IUP snippet: A small portion of the IUP used to check one value-proposition speculation with out displaying the total product.

Partially Tested Product (PTP): By the tip of week 4 of the category, groups utilizing IUP Snippets will produce {a partially} examined product primarily based on buyer suggestions to validate/ invalidate/ modify the IUP.

Product-Outcome Fit (POF): A substitute for Product-Market Fit. A extra targeted objective for AI-accelerated startups to give attention to.

Minimal Tested Canvas (MTC): A substitute for the time period MVP for testing the opposite components of the Business Model Canvas. The smallest set of experiments that meaningfully exams the non-product components of the Business Model Canvas, together with clients, channels, turnover, prices, companions, medical finish factors, regulatory paths, and key actions.

Design Partner: A co-developer who first gives suggestions, knowledge, workflow entry, and real-world testing in change for early entry, preferential phrases, or affect over the product. However, the true metric for achievement might be when the Design Partner is utilizing the product and getting worth out of it. (Design companions may be end-users in firms, warfighters, and many others. who should buy or affect a sale.)

Design Partner Validated Product (DPVP): By the tip of week 9, utilizing successively refined PTPs, groups can have a Design Partner validated product.

Minimal Viable Product (MVP): A time period beforehand used to find and iterate on the worth proposition and different components of the Business Model Canvas – not used within the Lean LaunchPad class.

What Changes – Class Tactics

We’ll break up the category into two components:
Weeks 1 – 4    Think Deeply – Stakeholder, Problem and Hypotheses Maps and Connections
Weeks 5 – 9    Act Quickly – with a objective to get Design Partners

We’ll double down on Customer Discovery.
For the primary 4 weeks college students, utilizing IUP Snippets, will get out of the constructing and map Stakeholders, issues, hypotheses and connections. The objective is to rapidly perceive present habits, workarounds, budgets, failure prices, and choice processes.

Students might be graded on the standard of their outreach, not on the success of proving their snippet appropriate.

We’re going to Replace Product/Market Fit with Category-specific Product/Outcome Fit Goals. We’re updating generic product/market match to match how AI firms are being constructed. For every product class, groups will use AI-specific Product-Outcome Fit discovery and validation targets:

• B-to-B enterprise software program groups seek for Outcome/Agent match. The buyer can outline acceptable work, the agent reaches that threshold within the goal workflow, the group grants the required permissions, and the previous different is decreased or retired.
• B-to-C shopper groups do mass creation and testing, spinning up and testing many variants in parallel. The staff finds an issue/want, goal archetype(s) and habits, acquisition and retention loop, and distribution path that survive repeated testing throughout variants.
• Hardware groups construct digital twins. Simulations predict the habits of prototypes intently sufficient to speed up iteration, whereas manufacturability, reliability, provide, and deployment stay viable.
• Life science groups speed up their Initial Untested Product with simulation and modeling instruments and take a look at medical endpoints (therapeutics, diagnostics, units, medical trials), reimbursement and financing.

We’re Eliminating MVPs for worth proposition discovery. We’ll implement rigorous downside and stakeholder discovery by way of speculation exams, utilizing Stakeholder Maps, the Value Proposition Canvas and Lean Experiment Cards. (These are instruments I’ve used at Imperial College in London to teach teams to solve “Wicked” Problems.) Teams determine and take a look at issues and stakeholder hypotheses. Then they use parts of their preliminary product, the IUP Snippets, to check core worth proposition hypotheses. There might be no “full product” demos till discovery is full. Where the previous class iterated low-fidelity to high-fidelity MVPs, the brand new class iterates low-fidelity to high-fidelity worth propositions and stakeholder maps.

We’re Encouraging Synthetic Interviews however testing them in opposition to reside interviews. Teams will create synthetic personas and run weekly artificial interviews. Then they’ll evaluate these responses with in-person interviews, validating or invalidating the artificial responses and feeding the reside responses again to the LLM to make the personas and artificial interviews extra correct. Note the course of authority: the reside interviews grade the artificial ones, by no means the reverse.

Create the Minimal Tested Canvas (MTC). AI can generate a product sooner than a staff can take a look at the opposite eight bins of the canvas. The “Minimal Tested Canvas” returns the course to a week-to-week give attention to discovery, testing and experimentation of all canvas parts (apart from the worth proposition). It exams a staff’s understanding of the regulatory course of, spec sheets, demand creation and gross sales mannequin, funding, organizational choice processes, and many others.

Create formal pivot-or-proceed standards for discovery. Teams state their hypotheses throughout the canvas, take a look at the issue, take a look at the answer with IUP Snippets, then face specific verify-or-pivot gates: confirm the minimal IUP, the shopper section, buyer relationships, the channel, and the turnover mannequin.

Because AI eliminated the pure pacing that constructing and MVP used to impose, the category now imposes go/no-go standards explicitly so a refined product can’t substitute for proof.

Make Design Partners A Team Goal. The staff’s class goal is to get a number of design companions. The companion commits scarce assets: workers time, knowledge, integration effort, permissions, take a look at environments, adjustments to workflow and the flexibility to affect the product.

A design companion is proof of Customer Validation. In 2026, when anybody will take a web-based assembly and pilots spin up in days, a design companion who commits pores and skin within the recreation is the trustworthy sign.

AI-Specific Class Additions

Test for Learning Debt. Any staff member ought to be capable to clarify the shopper, workflow, proof, economics, and key contradictions with out opening a laptop computer. Technical members ought to hear buyer language firsthand. AI-generated work needs to be attributed, and groups will distinguish what the mannequin produced from what the staff verified. (This is very necessary in discovery: what was the results of artificial interviews vs precise interviews.)

User Interface. The Initial Untested Product has to have a polish that wasn’t beforehand wanted. Stakeholders evaluate each interface to a chatbots UI/design now has a higher significance than a conventional MVP.

LLM Costs. Three questions that didn’t exist in 2011 when this class was created at the moment are core canvas economics: What does operating a LLM value you, and what are your unit economics? And what does it value your buyer to run it?

Autonomy Permissions. Which actions will the shopper enable? At what stage of reliability and reversibility. Human intervention stays particularly necessary throughout early deployment and for delicate, irreversible, or high-stakes actions?

AI Model Portability Is Strategic. Most frontier LLMs have proprietary context, instruments, workflow, analysis, belief, and distribution. A startup ought to assume that its most well-liked mannequin, pricing, latency, phrases, or relative high quality will change. LLM Model dependence is due to this fact a business-model danger, not solely an engineering selection.

“Trust” Evidence Is a Potential Moat In many bourses, the proof wanted to deploy safely will not be overhead added after product/market match. It is a part of product/market match. NIST’s Generative AI Profile treats trustworthiness as a lifecycle self-discipline of governance, measurement, and danger administration. The FDA’s AI-device steering equally connects iterative enchancment to deliberate validation, documentation, and affect evaluation.

Defensibility, alternative measurement, staff, and funding. The staff’s defensibility moat must be a part of discovery — from knowledge, to mannequin, to staff, to {hardware}. Opportunity measurement and market sort: is that this an incremental enchancment or does this transformation or create an trade? Team capabilities: does the staff have distinctive attributes, expertise and/or perception — and who else is required?

Textbooks versus Tokens – Students gained’t purchase as many textbooks they’ll purchase AI tokens and design instruments. So count on to spend cash.

Risks

A Heavier Lift for Faculty. The current Lean Launchpad class had much more transferring components than instructing “the best way to write a enterprise plan.” Yet it succeeded and scaled as a result of it ready college students for the international stage because it was. This class will elevate the bar as soon as once more – for each college students and college. I imagine the end result would be the identical.

Achievement inflation. In the present Lean LaunchPad class college students are already padding the variety of interviews they full. We write off all however essentially the most egregious as “dishonest in your entrepreneurship class is like dishonest in your parachute packing class.” The objective of discovering Design Partners now creates new avenues to inflate accomplishments. We’ll be emphasizing companions that assist validate the enterprise and result in progress not demos.

Design Partners as a Metric for Validation will probably lead to college students discovering native maxima as a substitute of the best peak. However, that is no totally different from what occurs within the early stage of most startups. We’ll be giving college students heuristics to how time pivots to bigger alternatives.

Teaching Student Teams How To Sell. In the previous, a Go-to-Market technique was simply a part of the shopper relationship portion of the enterprise mannequin canvas. While just a few groups generated turnover or acquired letters of intent whereas at school, we discouraged them from promoting as a result of at that time they hadn’t validated your answer. But now? We imagine that AI will sufficiently speed up downside and buyer discovery within the front-end of the category. The pedagogy going ahead is concerning the skill to quickly uncover and quickly validate within the period of AI. So “promoting” is definitely curricula. This is a large departure from the unique Lean LaunchPad.

Putting the items collectively

In the tip, whereas we’re altering the ways of the Lean LaunchPad class, its foundational beliefs stay unchanged: merchandise succeed once they clear up actual buyer issues/wants or create totally new merchandise that enhance the lives of individuals, communities and companies.

This new syllabus is itself a speculation that might be examined in Stanford’s Lean LaunchPad courses.  I’ll observe up with a “What we realized” evaluation of those adjustments. And there might be updates throughout the spring as we take a look at this method.

Comments, recommendations and your expertise instructing with AI are welcomed.

We’re pondering of making an educators information and holding an in-person convention at Stanford / MIT on these adjustments. Let us know by way of feedback or e mail if you happen to’re .

I’ve been fortunate sufficient to have been current on the creation of the final 50 years of disruptive applied sciences (semiconductors, computer systems, the web, sensible telephones). None of us might envision how they’d change the international stage. I can’t wait to see what my college students are going to do with AI.

Puzzling via what occurred to the category, the international stage round it and what to do subsequent was a joint effort. Thanks to Steve Weinstein, Mar Hershenson, Jennifer Carolan, Chuck Eesley, Tom Byers, Eric Volmar at Stanford; Pete Newell, for suggestions and at Imperial College Cristobal Garcia and Erkko Autio for the chance to show the Stakeholder and Assumptions mapping instruments in our Wicked Problems class.

Below is a draft of the up to date syllabus for the scholars. As you learn this, be mindful the scholars are doing 10-15 Stakeholder interviews every week.

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Lean Launchpad Syllabus  Course Details

Class Website http://leanlaunchpad.stanford.edu

Professors
Steve Blank [email protected]
Steve Weinstein [email protected]
Jennifer Carolan [email protected]
Lee Redden [email protected]

Attendance
In-person class attendance, Office hours and Workshop attendance is necessary.

Before Class

•  Set up your groups of AI brokers to have particular experience that will help you type via your discovery efforts (analysis, notes, synthesis, creativity, design, and so forth). Keep in thoughts discovery is your job, not the brokers’ job. But they are often highly effective assistants.
• Create an Initial untested Business Model Canvas
• Create an preliminary Stakeholder map of all of your hypothetical Stakeholders
• Create an preliminary Hypotheses Map for every of the stakeholders
• Create the preliminary speculation of what Problem-Outcome would appear like that might fulfill the stakeholders.
• Create the preliminary hypotheses for the opposite canvas parts (demand creation, go to market, prices, turnover mannequin, and many others.)
• What perception do you could have – what does the consensus mannequin output say about our downside, and what do you imagine that contradicts it?
• For potential software program merchandise, create Product Snippets (not Demos) to check particular hypotheses with stakeholders or use AI to create fashions or different artifacts
• Do at the very least 10 precise human interviews (report the interviews)
  • Each interview within the format of: a “speculation/experiment/anticipated end result/precise end result/path ahead”
  • Note that Stanford college students don’t rely as interviews. 50% should be in particular person.
  • All interviews require that the particular person you interview provide you with permission to report the interview. This must be in writing and/or capturing the permission within the recording itself.
• Create 5 potential AI buyer personas and interview them, then have AI analyze the solutions and create a brand new set for precise interviews. What is the consensus view as decided by AI?
• For {hardware} or bodily merchandise, probably create a vibe coded digital proxy, digital twin model or use AI to create fashions, spec sheets, and many others.
• Submit all by day-prior to class begin.

Week 1: Stakeholders, Hypotheses, Business Model, Snippets and Customer Development

Week 1  Learning Goals

• Understand the distinction between product improvement and downside understanding
• Understand the worth of the:
  • Business Model Canvas
  • Stakeholders and Hypotheses
• How to achieve Design and conduct stakeholder interviews
• How to design speculation/experiment interviews
• How to make use of Initial Untested Product snippets as a software for discovery vs validation of your product

Weekly Presentations:

The displays typically observe a cadence of:

• Here’s what we thought
• Here’s what we did
• Here’s what we discovered
• Here’s what we’re going to do subsequent.

All staff members needs to be ready to current. We will choose the presenter at class time.

Week 1 – Team Presentation Format

Slide 1 – Title Slide

• Team Name
• Interviews this week in particular person, distant, artificial
• Total interviews: in particular person, distant, artificial
• Problem You’re Solving
• Team Members

Slide 2 – Business Model Canvas

• Briefly spotlight any key insights
• Use the subsequent slide to zoom into the Stakeholders

Slide 3 – Stakeholders

• Show us your Stakeholder Map
• Who are the customers? Decision-makers? Influencers? Economic Buyers? Regulators? and many others.

Slide 4 – Hypotheses

• Show us your Hypotheses Map
• Connect the Hypotheses to the Stakeholders

Slide 5 – Live buyer insights

• Show us a abstract desk of your desk of speculation/experiment/anticipated end result/precise end result/path ahead (see pattern slide)
• Quote(s) and images listed below are required.
• How did it evaluate to the artificial interviews?

Slide 6 – Initial Untested Snippets

• Briefly, present us the product if you happen to’ve constructed it.
• Show us the preliminary snippet
  • What hypotheses was the snippet(s) testing?
  • What have been the outcomes?

Slide 7- Insights?

Slide 8- Next steps?

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Week 2: Experiment Design and Execution, Interview Insights

Week 2 Learning Goals

• Refine Customer Discovery Skills
• Refine speculation/experiment interviews
• Design and Run experiments
• Identify Stakeholder archetypes
• Understand worth proposition and the function of Initial Untested Product snippets
• Understand and apply efficient chilly outreach

Week 2 Team Presentations

Slide 1 – Title Slide

Slide 2 – Business Model Canvas

• Briefly spotlight any adjustments
• Use the subsequent slide to zoom into the Stakeholders

Slide 3 – Stakeholders

• Enhance the Stakeholder Map
• Who are the customers? Decision-makers? Influencers? Economic Buyers? Regulators? and many others.

Slide 4 – Hypotheses

• Refine the Hypotheses Map
• Connect the Hypotheses to the Stakeholders

Slide 5 – Actual Live buyer insights

• Update the abstract desk of your desk of speculation/experiment/anticipated end result/precise end result/path ahead (see pattern slide)
• Include previous weeks

Slide 6 – Initial Untested Snippets

• New/refined snippets? Show us
  • What hypotheses was the snippet(s) testing?
  • What have been the outcomes?
• Briefly, present us the product if you happen to’ve constructed it. Highlight if something has modified

Slide 7- New Insights?

Slide 8- Next steps

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Week 3 – Stakeholders, Competitors, Moats

Week 3 Learning Goals

• Stakeholder Segments
• Enhanced Value Proposition Canvas
• Competitive Positioning
• Stakeholder/Outcome Fit
• How are potential stakeholders making an attempt to unravel the issue?
• What is a Design Partner/Go-to-Market Strategy?
• Define your moat. E.g. knowledge gathered, distribution channel, model, clearance held, proof gathered, yield realized, deployed-instrument knowledge, certified provide chain, put in base, and many others.

Week 3 Team Presentations

Slide 1 – Title Slide

Slide 2 – Competitive Positioning

• Draw a Petal Diagram
• What is your aggressive moat?

Slide 3 – Customer insights

●     Update the abstract desk of your desk of speculation/experiment/anticipated end result/precise end result/path ahead (see pattern slide)

Slide 3a – Customer Attempts

• What have the shoppers already tried, together with with AI, and particularly why did it fail?

Slide 4 – Outcome/Value Proposition Canvas

• Combine studying from stakeholders & experiments to create an Enhanced Value Prop Canvas
• See instance in Appendix A

Slide 5- Initial Customers/Design Partners

Slide 6 – Initial Untested Snippets

• New/refined snippets? Show us
• Briefly, present us the present state of the product (if you happen to’ve constructed it.)
• Highlight what you realized from stakeholder suggestions.
• What will you present potential clients/Design Partners?

Slide 7 -Design Partners

• Using the Enhanced Value Proposition Canvas who could be Potential Design Partners?
• Engagement plan hypotheses

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Week 4 – Stakeholder/Outcome Fit?  Pivot or Proceed?

Week 4 Learning Goals

• Day-in-the-Life of Stakeholders
• Setting a Product/Outcome Fit Strategy
• Testing a Design Partner/Go-to-Market Strategy
• How to have interaction potential Design Partners
• Pivot or Proceed?

Week 4 Team Presentations

Slide 1 – Title Slide

Slide 2 – Minimally Tested Business Model Canvas

• Go via every field of the enterprise mannequin canvas
• Highlight key learnings and any adjustments
• Use the subsequent slide to zoom into the Stakeholders

Slide 3 – Initial Customers/Design Partners

• Who will they be? Why?
• Use Value Proposition Canvases for instance

Slide 4 -Partially Tested Snippets

• New/refined snippets? Show us
• Briefly, present us the present state of the product (if you happen to’ve constructed it.)
• Highlight what you realized from stakeholder suggestions.
• What will you present potential clients/Design Partners?

Slide 5 – Defensibility/Moat

• Short time period? Long time period?
• Unique knowledge? Data Access?
• Trust? Evidence/verifications?

Slide 6 – Market/alternative measurement (first cross)

• Market/alternative measurement
• Funding/staff wanted

Slide 7 -Design Partners

• Update the Enhanced Value Proposition Canvas to level to Potential Design Partners/Go-to-Market Strategy
• Define Product/Outcome Fit Strategy for Partners
• Partners Engagement plan

Pivot or Proceed Criteria

• Stakeholder(s): who’re they and what’s their downside/goal?
  • Show me the proof of your understanding!
• Value Prop: do Stakeholder(s): care about how you propose to create worth / clear up the issue?
  • Show me the proof that they care!
• Differentiation & moats: why will Stakeholder(s): choose you and is your benefit defensible?
  • Show me the proof they’ll select you!
• Willingness to pay & economics: will clients pay sufficient, and may you make the economics work?
  • Show me the proof they’ll pay!
• Customer acquisition & retention: How are you going to accumulate and retain clients?

Team Workshop for Product/Outcome Fit Strategy
Teams meet individually with college to tailor Product/Outcome Fit targets for his or her particular expertise and market. This might be their objective submit for the subsequent 5 weeks.

Filed beneath: Lean LaunchPad, Teaching |