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Beachhead Workbook

Fill the 4-layer framework in for your product. Every cell is a question — click it and type your answer. It saves to this browser automatically as you go. Narrow 30+ ideas to one defended beachhead with a 90-day plan.

🔒 Private by default. Your answers are saved only in this browser and are never uploaded. They leave your device only if you choose “Share my pick.”

Work this as a kill-funnel (Munger's inversion): at each layer ask “what would kill this candidate?” so weak ones die early and cheap. Every form cell is a question; every worked example is the answer for one product. Click any dashed cell to start typing — your answers persist on this device. When you're done, hit Print / PDF in the toolbar to share your defended pick. Stuck on a cell? Open a worked example: B2B SaaS · Consumer.

How this works

Click a cell, type your answer. The toolbar tracks your progress and autosaves — no account, no login.
Start with Section 0 (your product context), then work down through the four layers.
Each section's substrate-legend tells you which data source feeds each cell.
Revisit Section 5 every 2 weeks — the workbook is the document that compounds.
Your answers live only in this browser. Use Print / PDF to export or share them.

Section 0 — Frame the product

Set the context for everything that follows. The framework doesn't change; the product's stage determines which substrate feeds which cell.

Product name

↓ e.g. "Acme — data observability for ML pipelines"

One-line

↓ What does it do, who is it for, why now

Stage

↓ Pre-launch / Live / Growth / Mature

Substrates available

↓ Which substrate bundle fits (community / B2B SaaS / enterprise / pre-launch / pre-launch + opencli X-LI)

Planning horizon (Voje)

↓ 3-month / 6-month / 12-month / 18-month target

L1Baylands — pick the candidate beachheadsLayer 1 of 4

The 30+ opportunity brainstorm, narrowed to 4 candidates, scored against Aulet's 12-cell matrix and Moore's 3 conditions. v2 narrows to 4 candidates (not 5-10 as in v1) per Voje's proximity discipline — focus beats coverage.

Step 1.1 — The 30+ brainstorm (any substrate)

Substrates that work for this: founder intuition + customer conversations (Aulet classic); social listening (30+ adjacent communities); market reports (30+ industry × use-case combinations); CRM / sales data (30+ customer attributes); SEO data (30+ keyword clusters).

↓ [list 30+ market opportunities — one per line, no filtering]

Step 1.2 — Narrowed to 4 candidates (with substrate signal per)

v2 narrows to 4 because Layer 2 (Voje proximity) is a binary filter, and 4 is the right number to test against the proximity criterion without spreading the team thin. Substrate signal: 1-sentence per candidate.

↓ [4 candidates, each with: name + 1-sentence substrate signal]

Substrate-legend (Step 1.2): the substrate for "narrowed to 4" is the 30+ brainstorm + your team's GTM planning horizon + the proximity test you'll run in Layer 2. Don't try to be comprehensive; be ruthless about which 4 deserve a full matrix fill.

Step 1.3 — Aulet 12-cell matrix (per candidate, with substrate)

Candidate	Industry	Application	End-user	Benefits	Lead Customers (name 5-10)	Market	Charact-eristics	Partners/ Players	Size of Market	Compe- tition	Platform	Complem. Assets
↓ C1	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓
↓ C2	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓
↓ C3	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓
↓ C4	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓	↓

Substrate-legend (Step 1.3): most cells come from founder knowledge + market reports; "Lead Customers" needs named handles, which means customer interviews OR opencli X-LI search OR sales-call logging. "End-user," "Benefits," "Characteristics" need at least 3-5 customer interviews. "Platform" and "Complementary Assets" are founder knowledge.

Step 1.4 — Moore's 3 conditions (per candidate, with substrate evidence)

Candidate	(a) similar products bought — substrate evidence	(b) similar sales cycle — substrate evidence	(c) word-of-mouth — substrate evidence	Pass?
↓ C1	↓ [which interview, win/loss, comment]	↓	↓	↓ PASS / FAIL
↓ C2	↓	↓	↓	↓
↓ C3	↓	↓	↓	↓
↓ C4	↓	↓	↓	↓

L2Voje — pass the proximity testLayer 2 of 4

For each candidate that passes Layer 1, the framework demands a per-candidate proximity check: can we actually dominate this in 3-18 months? A planning-horizon constraint, not a substrate question.

Candidate	Can we dominate in 18 months? (Y/N + why)	What would "dominate" look like? (concrete metric)	If no, what's the blocker?
↓ C1	↓ Y / N + reason	↓ e.g. "1k newsletter signups, 100 tool installs, 5% conversion"	↓
↓ C2	↓	↓	↓
↓ C3	↓	↓	↓
↓ C4	↓	↓	↓

L3Solanki — pass the defender-loyalty testLayer 3 of 4

The HUL-Nihar case (1993-2006) is the layer-3 test: a beachhead with high pain and high resonance can still fail if the defender's brand loyalty is stronger than your launch force. The substrate: 5 defenders, 5 metrics each.

Step 3.1 — Name the 5 defenders

↓ [list 5 defenders — products, platforms, or communities that occupy the space you're entering]

Step 3.2 — Defender-loyalty probe (5 defenders × 5 metrics)

Defender	(1) Vendor-pitch mod-pin rate (0-3)	(2) "I trust X" comment count / month (0-3)	(3) NPS-equivalent on the defender (0-3)	(4) Switching-cost survey (0-3)	(5) Market-share trend (0-3)	Total / 15	Verdict
↓ Defender 1	↓	↓	↓	↓	↓	↓	↓ Safe / Caution / Kill
↓ Defender 2	↓	↓	↓	↓	↓	↓	↓
↓ Defender 3	↓	↓	↓	↓	↓	↓	↓
↓ Defender 4	↓	↓	↓	↓	↓	↓	↓
↓ Defender 5	↓	↓	↓	↓	↓	↓	↓

Scoring: 0 = no loyalty / low bar; 1 = some; 2 = significant; 3 = entrenched, switching cost high. Total ≥ 10 = defender is unsafe to attack directly; 5-9 = caution, position differently; ≤ 4 = safe to enter. Substrates for each metric: (1) social listening + mod logs, (2) social listening + comment search, (3) customer interviews + surveys, (4) customer interviews + win/loss, (5) market reports + your own sales data.

L3.5Munger — pressure-test the pickThe differentiator

Layers 1–3 probe the market externally (size, proximity, defender loyalty). This layer probes the internal failure modes — the buyer's psychology and your own incentives — because that's where the pick usually breaks. Five sub-tools; fill them from whatever data you have, and mark every guess as a guess. It catches the failure the other layers miss.

3.5.1 — Inversion pre-mortem

Assume the beachhead has already failed 18 months out. Work backward: list the ways it died (most-likely first); for each, the earliest signal you could have caught, and the guardrail inversion forces you to build now.

#	Kill-path (how it died)	Earliest signal	Inversion-derived guardrail
1	↓ most-likely failure	↓ what you'd see first	↓ what to build now to prevent it
2	↓	↓	↓
3	↓	↓	↓

Rank by likelihood, not by fear. The top kill-path is the one your Test Cards (L4) must target first.

3.5.2 — Buyer-bias probe

Walk the major decision biases for your specific buyer. For each: how it shows up in their behaviour, your counter-move, and which Test Card validates that the counter-move works.

Bias	How it shows up for this buyer	Counter-move	Validating Test Card
Status-quo / inertia	↓	↓	↓ TC #
Commitment / consistency	↓	↓	↓
Social proof	↓	↓	↓
Incentive-caused bias	↓	↓	↓
Loss aversion	↓	↓	↓
Authority / doubt-avoidance	↓	↓	↓

A bias with no counter-move is an open risk; a counter-move with no Test Card is an untested assumption. Both must surface.

3.5.3 — Incentive audit

List each incentive baked into your own model. For each: who it actually serves, the misalignment risk if it pulls against the customer, and the realignment that keeps your promise honest.

Incentive in your model	Who it serves	Misalignment risk	Realignment
↓ e.g. a recurring fee, a usage meter	↓	↓	↓
↓	↓	↓	↓
↓	↓	↓	↓

"Show me the incentive and I'll show you the outcome." The dangerous one serves you while quietly contradicting your headline promise.

3.5.4 — Opportunity cost

Choosing this beachhead means not choosing another. Name the wedge you're deferring, what deferring it costs, and the trigger that flips the cost.

The wedge this beachhead defers	What deferring it costs us	When the cost flips (trigger to revisit)
↓ the strong runner-up from L2	↓	↓ an observable signal, not a feeling

3.5.5 — Lollapalooza check

Do the forces from the layers above stack? List what pulls for the pick and what pulls against — then name what kind of problem this beachhead actually is, because a stack of forces usually reveals one compounding problem that reframes the whole GTM.

Forces stacking FOR	Forces stacking AGAINST
↓ what compounds in your favour	↓ what compounds against you

So what KIND of problem is this beachhead, really?	How that reframes the GTM (and the metric that proves it)
↓ acquisition? retention? trust?	↓

This is the payoff of the section. If you can't name the kind of problem in one word, you haven't pressure-tested hard enough.

L4Test Card — operationalize the beachhead hypothesisLayer 4 of 4

Once you've picked a candidate that passes Layers 1–3.5, write the per-week execution as Test Cards — targeting the riskiest assumptions the Munger layer surfaced. The cardinal rule: if you cannot fill in Step 4, you have not done the work.

Step 4.1 — Beachhead assertion (the decision)

The chosen beachhead, in one sentence:

↓ [The chosen beachhead, named in one sentence. e.g. "r/MLOps is the beachhead: 100k+ subs, MLOps maturity pain, mod team that respects OSS-first tooling, defenders (Datadog, Grafana) at 11/15 — caution not kill."]

Step 4.2 — 3 Test Cards for the next 6 weeks

Test Card 1 — [action name]

Step 1: Hypothesis

↓ We believe that [substrate signal: which interview, win/loss, comment, data point]...

Step 2: Test

↓ To verify that, we will [specific action, time, place]...

Step 3: Metric

↓ And measure [metric] with [substrate tool]...

Step 4: Criteria

↓ We are right if [pass threshold]

↓ We are wrong if [fail threshold — be specific]

↓ Pivot on fail: [next experiment]

Test Card 2 — [action name]

Step 1: Hypothesis

↓

Step 2: Test

↓

Step 3: Metric

↓

Step 4: Criteria

↓

Test Card 3 — [action name]

Step 1: Hypothesis

↓

Step 2: Test

↓

Step 3: Metric

↓

Step 4: Criteria

↓

Section 5 — The 3-month + 6-month + 12-month checkpoints

Aggregate the Test Cards and the layer-pass verifications into layered checkpoints. v2 extends the 90-day gate to 3 + 6 + 12 months because some substrate signals (defender loyalty, named-lead-customer relationships) only stabilize over longer horizons.

5.1 — Beachhead decision

The beachhead is: __________ [Layer 1 ✓ Layer 2 ✓ Layer 3 ✓ Layer 4 in progress] [Verdict: pursue / pivot / kill]

5.2 — 3-month checkpoint (5 success criteria + 5 risks)

#	Criterion	Threshold	Substrate	Result (3 mo)
1	↓	↓	↓	↓
2	↓	↓	↓	↓
3	↓	↓	↓	↓
4	↓	↓	↓	↓
5	↓	↓	↓	↓

5.3 — 6-month checkpoint (additional 3 criteria, beyond the 3-month)

v2 adds the 6-month gate because the 3-month gate is for execution discipline; the 6-month gate is for positioning — has the brand earned the curator-first posture, did the defender-loyalty probe reveal a name, are named-customer relationships converted to references?

#	Criterion (6-month)	Threshold	Substrate	Result (6 mo)
1	↓ Position: has the brand been recognized as curator (not vendor)?	↓	↓	↓
2	↓ Defender probe refinement: have 5 defenders been re-scored?	↓	↓	↓
3	↓ Reference customers: named customers converted to case studies	↓	↓	↓

5.4 — 12-month checkpoint (additional 3 criteria, beyond the 6-month)

v2 adds the 12-month gate because that's the typical runway window for pre-launch → first revenue. By 12 months the team should know whether the chosen beachhead is durable or needs a pivot to the next candidate.

#	Criterion (12-month)	Threshold	Substrate	Result (12 mo)
1	↓ Revenue concentration: % from beachhead	↓	↓	↓
2	↓ Wedge progress: have adjacent candidates started converting?	↓	↓	↓
3	↓ Defender-response: have any of the 5 defenders pivoted?	↓	↓	↓

5.5 — 5 risks (3-month horizon; carry forward)

#	Risk	Detection substrate	Mitigation
1	↓	↓	↓
2	↓	↓	↓
3	↓	↓	↓
4	↓	↓	↓
5	↓	↓	↓

Done. Now you have: 4 candidate beachheads that pass the 4-layer framework, a defended pick with substrate evidence per layer, 3 Test Cards for the next 6 weeks, and layered checkpoints at 3 + 6 + 12 months with 11 success criteria + 5 risks. The workbook is substrate-agnostic — the same structure works whether your substrate is Reddit, customer interviews, win/loss, or X.com + LinkedIn named-handle search via opencli.

What to do next: print this page (or copy the HTML), fill in the cells for your product, share with the team. Update Section 5 every 2 weeks. The cardinal rule: if you cannot fill in a Step 4, you have not done the work.

↑ Home Worked example: B2B SaaS →

A substrate-agnostic application of the 4-layer framework. The framework is the test; the substrate is the data. Made by VE LAB. Companion: framework essay.

#	Criterion	Threshold	Substrate	Result (3 mo)
1	↓	↓	↓	↓
2	↓	↓	↓	↓
3	↓	↓	↓	↓
4	↓	↓	↓	↓
5	↓	↓	↓	↓

#	Criterion	Threshold	Substrate	Result (3 mo)
1	↓	↓	↓	↓
2	↓	↓	↓	↓
3	↓	↓	↓	↓
4	↓	↓	↓	↓
5	↓	↓	↓	↓

#	Criterion	Threshold	Substrate	Result (3 mo)
1	↓	↓	↓	↓
2	↓	↓	↓	↓
3	↓	↓	↓	↓
4	↓	↓	↓	↓
5	↓	↓	↓	↓