Three weeks after launch, I sat in a meeting with a potential partner and watched their face go blank when I explained our pricing. Not confused. Blank. The kind of blank that means “I have no idea how this maps to my business, and I’m too polite to say so.”

We’d spent months building tiered pricing that made perfect sense from our side. Four tiers, clean feature gates, volume discounts. It was elegant. It was logical. And it was completely disconnected from how our customers actually think about value.

That meeting was the first of four pricing rewrites in six months. Each one taught us something we couldn’t have learned from a spreadsheet alone.

The mistake everyone makes (including us)

There are really only three ways to justify a price: cost-based (mark up what it costs you to deliver), competition-based (anchor to what the market already pays), or value-based (charge a fraction of the value or savings you create). Most founders default to the first one. We did too.

The problem with cost-plus pricing is that your customer doesn’t care what it costs you to deliver. They care what it’s worth to them. And the gap between those two numbers is where all the interesting pricing decisions live.

When we first priced the product, we started with our infrastructure cost per identity check, added a margin, and arrived at a per-check price. Technically correct. Strategically useless. Because a per-check price means nothing to a wealth management firm trying to figure out whether your platform will save them money on client onboarding.

Version 1: Per-check pricing (the logical mistake)

Our first model was simple: charge per identity verification. Max 10 cents per check, with volume discounts stepping down to 8 cents above 100,000 monthly checks. Four tiers — Free, Standard, Premium, Enterprise — gated by features and volume.

On paper, this was clean. In practice, nobody could calculate what it would actually cost them. A wealth manager with 80 active client connections running periodic data refreshes would need to estimate their monthly check volume, factor in the tier they’d land on, account for overages, and somehow arrive at a budget number. Too much mental math, too much uncertainty.

The feedback wasn’t “your price is too high.” It was silence. People couldn’t engage with the model at all.

Version 2: Per-user pricing (the overcorrection)

So we swung the other way. Flat monthly fee per user. Simple to understand, easy to budget for. But it created a different problem: it penalized our best customers. A firm with 350 wealth managers would pay 350x regardless of how much value they were extracting. Heavy users and light users paid the same. The firms that would benefit most were the ones getting the worst deal.

We also couldn’t differentiate between a small advisory practice with 25 wealth managers and a large institution with 350. The value per user was completely different across these segments, but our pricing pretended it was the same.

Version 3: Value-based, but we calculated the value wrong

This is where things got interesting. We decided to flip the model: instead of pricing based on what it costs us, price based on what it saves them. Calculate the actual cost of onboarding and maintaining a client today (hourly wage × time per event × external costs), calculate the same cost with our product, and the difference is the value we create.

The framework was right. The execution was wrong. We were calculating total value across the entire firm and then trying to capture a percentage. But the buyer wasn’t thinking in “total firm savings.” They were thinking “what does this cost me per client?”

We’d built a top-down model when the buyer needed a bottom-up story.

Version 4: Bottom-up value pricing (what actually works)

The breakthrough came when we rebuilt the model from the smallest unit up:

Step 1: Value per single client. What does it cost to onboard and maintain one client today? What does it cost with our product? The difference is the value per client. For a typical wealth manager, current onboarding cost was roughly €45 per client (blended hourly wage × time × external verification costs). With our product, that dropped to around €12. Value created: €33 per client.

Step 2: Value per user. Multiply by average clients per user. A wealth manager at a small firm handles about 50 clients. At a large institution, closer to 200. So value per user ranges from €1,650 to €6,600 annually, depending on segment.

Step 3: Value capture percentage. We don’t capture all the value. We capture a share that feels fair relative to what the customer keeps. We landed on different capture rates by segment: higher for enterprise (they get more value per user), lower for small firms (keep the barrier low).

Step 4: Sense check. Does the resulting monthly fee per user feel reasonable? Can a buyer look at it and immediately understand the ROI without a spreadsheet? If the answer to both is yes, the pricing works.

This model let us walk into a meeting and say: “Your onboarding cost per client drops from €45 to €12. You have 100 wealth managers averaging 100 clients each. Here’s exactly what that saves you, here’s what we cost, and here’s your net ROI.” One slide. No confusion. No blank faces.

Triangulate: cost is the floor, competition is the anchor, value is the ceiling

Looking back, the deeper lesson isn’t that value-based pricing is the right answer. It’s that no single method gives you a defensible price on its own.

We now triangulate three lenses every time we revisit pricing:

Cost-based answers: what’s the floor? Sum what it costs to serve one customer at scale (infrastructure, support, amortized dev, payback on acquisition cost). Add the margin you need. That’s your sanity check, not your target. If your price is below this number, you’re choosing to subsidize, and you should know exactly why.

Competitive answers: what does the market already accept? Benchmark adjacent products. This anchors your pricing to what customers already pay elsewhere, which is where their reference point lives whether you like it or not. The risk is picking the wrong peer set; pick three peer groups, not one.

Value-based answers: what’s the most we could charge? Quantify time saved, risk avoided, costs eliminated. Apply a willingness-to-pay rate (10–15% is a common starting point for new products). This gives you the ceiling, the most defensible long-term story for sales, and the ROI math the buyer will use internally.

The right price is somewhere in the overlap. When we first priced the product, we used only one lens (cost) and ended up with a number that was technically defensible and commercially inert.

Pick the right structure (and don’t be afraid of a hybrid)

Once you have a price, you have to decide how to charge for it. Per seat? Per unit of usage? Flat platform fee?

The honest answer is that almost everyone interesting ends up with a hybrid. We’ve recently been working with an AI platform serving customer support teams that landed on a two-part tariff: a flat monthly platform fee that gets you access and unlimited users, then per-unit consumption rates for the modules you actually use (per word translated, per QA review). Volume tiers bring the per-unit rate down as customers scale. A 10% multi-module discount nudges expansion. Annual commitments get a further discount in exchange for predictability.

It works because each piece does a different job. The platform fee establishes a stable relationship and covers fixed costs. The consumption fee aligns what the customer pays with what they get. The volume tiers reward growth. The annual discount pulls cash forward and reduces churn risk.

If you want to push this further, three-part tariffs (platform fee + bundled usage + per-unit overage) tend to capture even more value. Behavioral research suggests customers on a three-part tariff increase their usage by around 15% versus less than 1% for those on a pure two-part tariff. The bundled allowance changes how they think about consumption.

This matters more than ever for AI products. When the buyer’s mental model is “I’m replacing seats with agents,” your pricing structure has to make that math obvious. A pure per-seat model under-prices the actual leverage. A pure consumption model gives the buyer pricing anxiety. Most teams we see end up somewhere in between, with a platform fee that establishes the relationship and consumption-based pricing that aligns with the value delivered per ticket, per interaction, or per outcome.

What we actually learned

Start from the customer’s smallest unit of value. Don’t model total firm savings. Model the saving per client, per transaction, per ticket, per whatever your customer naturally thinks in. Then build up. People can intuitively validate small numbers (”€33 saving per client sounds about right”) in ways they can’t validate large ones (”€2.4M in total savings” triggers skepticism, not confidence).

Segment early, even if your segments are rough. A 25-person firm and a 350-person firm aren’t just different sizes, they’re different businesses with different economics. We defined three segments (Small, Medium, Large) with different assumptions for clients per user, usage patterns, and value capture rates. The segments were imperfect, but having them at all meant we could tailor conversations instead of forcing one story onto everyone.

Build the model so the buyer can play with it. The single most effective sales tool we created wasn’t a pitch deck, it was a spreadsheet where the prospect could plug in their own numbers (number of users, clients per user, current cost per event) and see their specific ROI. When the buyer builds the business case themselves, they own it. That’s worth more than any pricing page.

Your pricing is a communication tool, not just a revenue mechanism. The reason Version 1 failed wasn’t that the numbers were wrong. It was that the model couldn’t be understood in a meeting. Pricing needs to be explainable in one sentence. Ours is now: “You pay a percentage of the value we create per client, and you keep the rest.”

Treat pricing as a moving target, not a launch decision. Demand curves shift as your brand strengthens, reference customers accumulate, and ROI evidence builds. We now revisit pricing quarterly and re-index annually (CPI plus a small premium). The teams that get pricing right aren’t the ones who pick a perfect number on day one. They’re the ones who build a feedback loop and use it.

Common pricing mistakes worth avoiding

A few patterns we keep seeing in other founders’ pricing, often the same ones we made:

• Building a model that’s clever behind the scenes but opaque on the surface. Complexity is fine internally. The buyer should still be able to explain what they’re paying for in one sentence.

• Waiting too long to move to annual prepay. Annual contracts smooth churn, generate cash, and force the renewal conversation once a year instead of twelve times. Push for it earlier than feels comfortable.

• Treating pricing as static. If you haven’t touched your pricing in two years, your pricing is wrong. Markets move, you move, your pricing has to move too.

• Forgetting to embed concessions in the proposal. Mid-market procurement teams will negotiate. If you don’t leave room, you’ll either lose the deal or lose margin you didn’t plan to lose.

• Asking the wrong price discovery questions. Don’t ask “what would you pay?” Ask “what are you currently paying for the alternative?” Relative beats absolute every time.

Your turn

We’ve attached two resources below that you can use today:

The Pricing Strategy Prompt — a structured prompt you can feed to any AI assistant along with your product details. It walks through the same value-based pricing framework we used: identifying your customer’s unit of value, modeling current vs. new cost, segmenting, and setting capture rates. It’s the thinking tool that got us from Version 1 to Version 4.

The Pricing Model Template — a simplified version of the spreadsheet we use in sales meetings. Plug in your own segments, cost assumptions, and value capture rates. It calculates per-client value, per-user value, and total revenue potential automatically. Designed to be handed to a prospect so they can model their own ROI.

What pricing model are you using, and how did you land on it? We’re curious whether other founders went through the same iteration cycle or found a shortcut we missed. Drop a comment or reply, we read everything.

Resource 1: Pricing Strategy Prompt

Copy this into Claude, ChatGPT, or any AI assistant along with a description of your product and customer.

I need help building a value-based pricing model for my product. Here’s the context:

[Describe your product: what it does, who uses it, what problem it solves]

Walk me through these steps:

1. UNIT OF VALUE: What is the smallest unit of value my customer experiences? (e.g., per transaction, per client served, per hour saved, per ticket resolved). Help me identify the right unit based on how my customer naturally thinks about their work.

2. CURRENT COST: Help me estimate what it costs my customer to handle one unit today WITHOUT my product. Break it down into: labor cost (hourly wage × time), external/tool costs, and opportunity cost if relevant. Ask me clarifying questions to get realistic numbers.

3. NEW COST: Now estimate the cost per unit WITH my product. What time is saved? What external costs are eliminated? What’s the new per-unit cost?

4. VALUE CREATED: Calculate the value per unit (current cost minus new cost). Then help me think about how many units a typical customer handles per month/year.

5. CUSTOMER SEGMENTS: Help me define 2-3 customer segments (e.g., small/medium/large) based on volume, team size, or usage patterns. For each segment, estimate: units per user, number of users, total value created.

6. VALUE CAPTURE: What percentage of the value created should I capture as my price? Consider: competitive alternatives, customer willingness to pay, my cost to serve, and what leaves enough value on the table that the ROI is obvious.

7. TRIANGULATION CHECK: Compare the price you’ve derived against (a) the cost floor (what it costs me to serve one customer at scale, plus margin) and (b) the competitive anchor (what similar products charge). Does the value-based price sit comfortably above the floor and within reach of the anchor? If not, what needs to change?

8. SENSE CHECK: For each segment, calculate the implied monthly price per user. Does it feel reasonable? Can I explain it in one sentence? Would a buyer immediately understand the ROI?

9. PRICING STRUCTURE: Based on the above, recommend a pricing structure (per-user, per-unit, tiered, two-part tariff, or hybrid) and explain why it fits my market.

Present the final model as a simple table showing: segment, value per unit, units per user, value per user, capture rate, and price per user.

Resource 2: Pricing Model Template

Below is the structure of our pricing model. Build this in a spreadsheet (or copy it into an AI and ask it to generate the formulas for you).

=== INPUTS (change these for each prospect) ===

Segment: [Small / Medium / Large]

Number of users: [e.g., 25 / 100 / 350]

Clients per user: [e.g., 50 / 100 / 200]

Hourly wage (blended): [e.g., €55]

--- Current process (without your product) ---

Time per event (hours): [e.g., 0.75]

External cost per event: [e.g., €5]

--- New process (with your product) ---

Time per event (hours): [e.g., 0.15]

External cost per event: [e.g., €2]

--- Your pricing ---

Value capture rate: [e.g., 20-30%]

=== CALCULATIONS ===

Current cost per client:

= (Hourly wage × Time per event) + External cost

= (€55 × 0.75) + €5 = €46.25

New cost per client:

= (Hourly wage × New time) + New external cost

= (€55 × 0.15) + €2 = €10.25

Value created per client:

= Current cost - New cost

= €46.25 - €10.25 = €36.00

Value per user (annual):

= Value per client × Clients per user × Events per year

= €36 × 100 × 1 = €3,600

Your price per user (annual):

= Value per user × Capture rate

= €3,600 × 25% = €900

Customer keeps per user:

= Value per user - Your price

= €3,600 - €900 = €2,700

ROI for customer:

= Customer keeps / Your price

= €2,700 / €900 = 3.0x

=== TOTAL REVENUE POTENTIAL ===

Revenue per segment:

= Price per user × Number of users

= €900 × 100 = €90,000/year

Your cost to serve: [your platform cost per user]

Gross margin per user: [price minus cost to serve]

Pro tip: build this as a live spreadsheet and hand it to your prospect during the sales meeting. Let them change the inputs. When they build the business case themselves, they sell it internally for you.

Image credit: Matheus Bertelli via Pexels

Doesn’t matter if you’re building a consumer product, B2B software, or sending rockets to Mars. The first thing we write when starting a new business or project is an investment memo. Not a plan. Not a pitch deck. 5 to 8 pages, for an audience of nobody, on what we think the problem is, the target customer, why now, the solution, why you are the one to solve it, and how to get it into the hands of paying customers.

This sounds obvious until you notice that almost nobody starts here. The usual order is the opposite. Open a spreadsheet, scrape an ICP list, run the TAM math, and only after a few weeks of that try to articulate what you actually believe. You end up a month deep in research about a problem you never properly defined.

This matters more now than it used to, because of AI. Used to be that getting good information took real time. Now you can run a deep research report in half an hour. You can have a competitor map by lunch. The constraint has moved. It used to be the research itself. Now it’s knowing what to point the research at, and that part still has to come from a human writing down what they believe.

What this is

We spent this weekend building a Claude Skill that walks a founder through writing an Investment Memo for a new business. The memo is a 5 to 8 page Word document, written in full prose. We tested, iterated, and used the skill on ourselves.

The skill is open source and sits here: github.com/third-vector-eu/claude-skills.

The process

The skill runs five phases. You don’t need to memorise them, but knowing what’s coming helps.

1. Calibrate. It asks how familiar you are with the domain. Are you a domain expert who has lived in this market for a decade? Adjacent, with related but not identical experience? Or exploring new territory? The answer changes how the rest of the interview runs. Domain experts get harder questions. Explorers get more research support and more humility prompts.

2. Interview.Section by section, the skill walks you through the twelve parts of the memo. Problem, target customer, why now, solution, founder-market fit, business model, go-to-market, competition, customer discovery, risks and falsification, milestones, the ask. For each section it asks three or four sharp questions and runs parallel web research on market signals, competitors, and “why now” evidence. Every answer gets reflected back before moving on.

3. Draft. It writes the full memo in prose. Every major claim gets tagged either [Conviction] or [Hypothesis], so you and any future reader know which parts are earned and which parts are bets.

4. Critical review. This is where the skill earns its keep. It runs the draft against a fourteen-point checklist built around the specific failure modes of early-stage memos. Fluff that looks like content. Contradictions between sections. Weak claims. Missing evidence. Confidence outrunning reality. It then asks you the three sharpest questions, the ones you should sit with this week.

5. Iterate. You answer the critiques. The memo gets revised. A companion document captures the open questions and next experiments that fell out of the review, which becomes the punch list for your next 30 days.

The full process takes between 1.5 and 3 hours, depending on how deeply you think through each answer. Sit with the questions. The slower answers are usually the better ones.

Why write this yourself

You cannot outsource founder conviction. You cannot outsource the felt sense that you are a credible person, or at least a plausible one, to build this company. The act of writing the memo isthe thinking. Someone else writing it for you means you still have to do the thinking later, except now you have a document that sounds like you didn’t.

There is a second, quieter reason. The memo is the spine of everything downstream. The pitch deck is an extract of the memo. The website copy is an extract of the memo. The sales messaging, the hiring pitch, the first three blog posts, the cold email to a design partner, the opening talk at your first conference. All of it references the memo. If the memo is weak, every artefact downstream is weak. If the memo is sharp, every artefact downstream inherits the sharpness.

Write it once. Properly. Then the next month’s work compounds off it.

It is a living document

The first draft is not the final draft.

You will have ten conversations with prospects and realise your ICP is wrong. You will price something and watch three buyers flinch at the number. You will discover a competitor you had missed. You will learn that the pain point you thought was most acute is actually second, and the real urgency sits elsewhere.

Come back to the skill. Run it again. Revise the memo. What changed between v1 and v2 is where your learning actually lives. Keep the old versions. The delta is the story of your company.

Our tip: read it out loud

When the draft is done, read it out loud. To your co-founder. To your partner. To a patient friend.

Reading it out loud does two things at once. You catch yourself hedging. You hear the sentences where you lose conviction halfway through and start padding. Your voice gets softer. You speed up. You know, as you are reading, which paragraphs do not earn their space.

At the same time, the people listening start asking questions. And the good ones really hurt. The questions you haven’t thought about yet. The questions you were hoping no one would ask. Those are the ones you write down, and the answers you go find this week.

Your turn

The skill is on GitHub: github.com/third-vector-eu/claude-skills.

Write yours. Read it out loud. Tell us where it breaks.

Building a go-to-market is not a single strategy document. It’s a sequence of phases, each with a gate you need to pass before moving on.

• Phase 0 (Setup): Get your file storage, AI tools, and foundational skills configured before you do anything else.

• Phase 1 (Foundation):Write your investment memo, map the product value, size the market. If TAM/SAM doesn’t hold up, go back.

• Phase 2 (Validate):Define your ICP, build a target list, run experiments. If the messaging doesn’t land, refine and repeat.

• Phase 3 (Scale): Build the machine. Content, sales process, CRM, inbound, pipeline generation, pricing, KPIs, onboarding, win/loss analysis. Gate: repeatable wins and consistent pipeline velocity.

• Phase 4 (Expand): Grow what you have. Feature release process, upsell/cross-sell, pricing review.

• Strategy (parallel): Runs alongside Phase 3 and 4. Full TAM/SAM deep-dive, unit economics, budget planning, forecasting, annual GTM strategy.

Every step comes with deliverables: AI skills, guides, prompt-templates, and tools. And six processes never stop running: your investment memo, ICP definitions, product experimentation, pricing, positioning & messaging, and customer feedback.

The full process at a glance

We built an interactive flowchart that maps out the entire go-to-market process. All 25 steps, three gates, the strategy track, and the deliverables for each step. You can toggle between a high-level overview and the detailed version.

View the interactive GTM flowchart →

The rest of this article walks through each phase and explains why they’re in this order.

Why order matters

Most go-to-market advice skips the sequencing. You get a list of things you should do, tactics that worked for someone else, a framework with four quadrants. What’s missing is the order, and the gates that tell you whether you’re ready for the next step.

We recommend a structured, gated go-to-market process that starts from first principles and scales to a full annual strategy. We split it into five phases, each with clear steps, and each ending with a checkpoint. If you pass the gate, you move on. If you don’t, you go back and fix what’s broken.

For every step in the process, we provide four types of deliverables. Skills are specialized instructions that teach AI models specific workflows, styles, or domain expertise, allowing them to perform complex, repetitive tasks efficiently. Guides are deep-dive articles with practical how-tos or frameworks for the team. Prompt-templates are structured prompts you configure with your own context and run tasks. And tools are software recommendations for the infrastructure you need.

Let’s walk through it.

Phase 0: Setup

Before you build anything, make sure your basics are in place. This sounds obvious, but we see teams jump into outreach or content creation with no shared file structure, no AI tooling configured, and no shared language around what they’re building.

Three things to sort out first. Set up your shared file storage and connect the AI tools you’ll use throughout the process. Configure your foundational AI skills (such as the humanizer, so your output doesn’t read like a chatbot wrote it), tone of voice, formatting standards. And feed your AI the right context: industry keywords, jargon, a high-level description of what you’re building. Context in, quality out.

This takes a day. Maybe two. But it saves you weeks of rework later.

Phase 1: Foundation

“What are we selling, to whom, and is the market big enough?”

You start with an investment memo. This is a founder exercise. You write down the value, the product, the target market in a short, crisp document. Think of it as an internal pitch, something anyone on the team can read and immediately understand what you’re doing and why.

From there, you do product and value mapping. What do we aspire the product to be? What value do we expect it to deliver? This matters especially when you’re not building a mass consumer product. In B2B, thinking explicitly about value delivery is the foundation of everything that follows, from positioning to pricing to how you structure your sales conversations.

Then you size the market. Back of the envelope only. You can kill yourself on TAM/SAM analysis, and many teams do. At this stage, you just need to know: is this market big enough to be worth pursuing? A quick top-down and bottom-up estimate. If the answer is no, you go back to step one and rethink your product or your target.

That’s Gate 1. Pass it, and you continue.

After the gate, you do a quick competitive landscape scan. Who else is in this market? How do they position themselves? What problems do they claim to solve? This is not a detailed battle card exercise. That comes later. This is orientation.

Then revenue target math. You probably have an ARR or MRR goal. Work backwards. How many logos do you need? What deal size does that imply? What kind of sales motion can realistically support that volume? If you need to sign 200 enterprise clients in your first year without a sales team, that number is telling you something. Either your target is unrealistic, your pricing needs to change, or your go-to-market motion needs to be fundamentally different.

The phase ends with an MVP definition. What are we building? Who are we selling to? What are the minimum product requirements to test our assumptions?

Phase 2: Validate

“Does our value land with the right people?”

You start with ICP definition. Ideal Customer Profile. This is a team exercise, not a solo founder activity. Get everyone who touches customers into a room, customer support, implementation, tech, sales, and define what your ideal client looks like. Crucially, define it using data points you can actually measure externally. “Companies that care about innovation” is not an ICP. “B2B SaaS companies with 50-200 employees, Series A or later, with a customer support team of 10+” is.

ICP will evolve over the lifetime of your company. It’s never fixed. But you need a starting point to test against.

Once you have your ICPs, you work on positioning and messaging. How do you speak to each type of ICP? What’s the persona within those companies? What problems do they lose sleep over? This is where a lot of teams skip ahead to outreach without doing the positioning work first, and then wonder why their cold emails get ignored.

Next, build your initial target list. Combine your ICP definition with externally measurable data points to populate a list of companies. Then find the right individuals within those companies. If you’re going after a consumer market, the company layer drops away. But for B2B, it’s always two steps: which company, then which person.

Now you design experiments. You’re going to run multiple outreach experiments in parallel, with short review cycles, testing different variables: messaging, channels, cadences, value propositions. Each experiment targets a specific ICP group. Minimum two, ideally four to six. The goal is to learn which combination of ICP, message, and channel actually converts.

Before you run those experiments, you need a pricing hypothesis. Prospects will ask about pricing early. If you don’t have a ballpark, you’ll get checked out of conversations fast. There are three approaches: cost-based, value-based, and competitive-based pricing. At this stage, you pick one direction and test it. The deep pricing work comes later.

Then you run aggressive outreach cadences, measure results, and collect feedback. What are the numbers telling you? What are prospects actually saying?

Gate 2: do you see emerging patterns? Do you understand how to reach your targets consistently? If yes, you move to scale. If not, you loop back to ICP definition and refine.

Phase 3: Scale

“How do we build the machine?”

Content comes first. Everything you learned in Phase 2, the messaging that worked, the objections you heard, the language your ICPs use, feeds directly into your content. A lot of content creation can be accelerated with AI now, but the quality of that content depends entirely on the quality of the input.

In parallel, you build three things: your sales process (how deals actually move through stages), your CRM and go-to-market infrastructure (the systems that capture everything), and your inbound engine (website, SEO, demos, content distribution). These three are interdependent and should be built together.

Once that infrastructure is in place, you systematize pipeline generation. Outbound and inbound, measured continuously. Pipeline measurement is where many teams start to feel real about their go-to-market. You’re no longer guessing, you’re watching deals move.

As deals progress through the pipeline, pricing becomes critical. This is where you move from hypothesis to real pricing work. Value-based, cost-based, or competitive, it doesn’t matter which framework, what matters is that you approach it as a discipline, not an art. We have dedicated guides and templates for this.

Define your metrics and KPIs. When you set up your CRM and sales process, you already started thinking about what to measure. But once pipeline starts flowing, you need to know how to act on those metrics. What we see a lot is that pipelines are based on hope rather than data. Conversion rates, pipeline velocity, deal cycle times, these are the numbers that tell you whether your machine is actually working.

In a separate workstream, you think about onboarding and first value delivery. If this breaks, pipeline doesn’t matter. How fast can you get customers live and delivering the value you promised? And you run win/loss analysis on every closed deal. Why did we win? Why did we lose? Link the answers back to your ICP definition.

Gate 3: repeatable wins and consistent pipeline velocity. Deals move through the pipeline at a predictable rate. Conversion rates are steady month over month. You can have different motions running side by side, different countries, different products, different segments. But each motion needs to be repeatable on its own.

Phase 4: Expand

“How do we grow what we have?”

Once you start onboarding customers, the cheapest revenue is sitting right in front of you. It’s always easier to sell to an existing customer where you’ve already done the legal work and built the relationship.

This phase covers three things. First, your feature release process. How do new features reach existing clients? Think release cadence, product marketing for existing customers, and pricing implications of new functionality. Second, your upsell and cross-sell strategy. What triggers an expansion conversation? What upgrade paths exist? How does the commercial team identify and act on those signals? Third, a pricing review against actual usage data, expansion revenue, and competitive moves.

The strategy track

Strategy runs in parallel with Phase 3 and 4. It doesn’t wait until you’ve built the machine. Once you have your foundation and your initial ICP validated, you should start planning ahead.

We always recommend planning at least a year out. It forces you to step back from the day-to-day. What do we want revenue to be? What can we invest to get there? How big does the team need to be, and what performance do they need to deliver? What’s the average deal size we need to sign?

The strategy track includes a full TAM/SAM analysis overlaid against your actual pipeline penetration. Unit economics validation, are we reaching our goals cost-effectively? Budget and resource planning, including headcount, ramp time, and performance targets. And forecasting, which used to be more art than science but doesn’t have to be. You can triangulate cohort analysis, conversion rates, bottom-up enterprise modeling, and velocity-adjusted weighted pipeline to build a forecast you can actually trust.

All of this feeds into your annual go-to-market strategy, reviewed quarterly, refreshed annually. If your business depends on year-end deals or chunky enterprise contracts, plan the timing of that strategy cycle carefully. You want your go-to-market plan ready before the new financial year starts.

What never stops

Six processes run continuously from the moment they start:

1. Your investment memo updates as you learn what works. It’s your elevator pitch for investors, for new hires, for anyone who needs to understand what you sell and why. Keep it current.

2. Your ICP definitions evolve as your product grows and your markets expand.

3. Product experimentation continues to validate whether product value and ICP align, ideally measured live within the product.

4. Pricing refines as you add functionality and close more deals.

5. Positioning and messaging sharpens with every customer conversation.

6. Customer feedback feeds back into everything, ICP definitions, product marketing, feature prioritization.

What’s next

In future Blueishprint articles, we’ll go deep on individual steps. Some will get their own article, others we’ll combine. We’ll share the skills, guides, prompt-templates, and tools for each step as we go.

Next up: the Investment Memo. How to write one, what it should contain, and why it’s the single document everyone on your team should be able to recite.

Factory image: Alan Wang (Pexels)

One of us is writing this with a product launch in three weeks that he’s not ready for. A digital identity vault going live at a public event. The plan is to launch “The Founding Hundred,” exclusive access for the first hundred people to sign up at €100 per month. A golden badge, early access, and the kind of FOMO we’re betting will get people moving. If we nail it, that’s €120K in annual revenue from day one. The product is still in progress. The website isn’t live yet. There’s no final decision on the consumer brand name. Scary? Sure. But we’ll take it as it comes.

That’s what building a business actually looks like. Not the polished version. The real one.

A few months ago, one of us called the other while setting up a new holding structure. “What accountant did you use for the BV again?” The same question had gone the other direction the week before, except that time it was about pricing tiers. The week before that, it was GTM sequencing. Different businesses, different markets, and yet every single week we were having the exact same conversation: “How did we do this last time?”

At some point the response was: “We need to stop calling each other and start writing this down.” And the reply: “Yeah, but properly this time.” That became The Blueishprint.

Who we are

Tim is 39. Friso is 33. We’re brothers-in-law, which means we didn’t choose to be family but we did choose to keep talking about business at every family dinner until everyone else left the table.

We’re not co-founders. We’re not building one thing together. We’re each starting our own businesses, in different markets, with different products. But our backgrounds are different enough that we keep filling in each other’s blind spots.

Tim has lived and worked across the US, Europe, and Asia. He’s built teams and delivered AI products across all of them and has this annoying ability to look at a business model and immediately spot the thing that doesn’t add up. Right now he’s building Third Vector, helping companies redesign their operations around agentic AI. Not adding tools to existing workflows, but rethinking how the work gets done.

Friso built Sentinels, an AI-powered transaction monitoring platform, and sold it to a strategic buyer. Eight years in total, from first pitch deck to acquisition integration and managing the post-acquisition phase. The product is now running at some of the largest financial institutions in the world. It was an incredibly fun ride with plenty of ups, downs, and more near-death experiences than we’d like to admit. The acquisition alone taught us more in six months of due diligence than in years of actually running the business.

Now Friso is building a digital identity vault. You store your personal data once, and when an institution needs something, you approve the request and the data flows over, verified and up to date. No more digging up passport scans. We’ll write a lot more about this one.

Between us we’ve started companies, raised tens of millions in funding, held roles at organizations we probably had no business being at, and survived enough mistakes to fill a very long spreadsheet. We both love building things. That’s the short version.

Introducing The Blueishprint

We’re both moving about ten times faster this time around. Partly because we’ve been here before and know which shortcuts are real and which ones will blow up in your face. Partly because of AI. The combination of experience and the tools available right now means we can build in months what used to take years.

So why keep all of this in our heads?

Most business content is either too abstract (”here are 7 principles of great leadership”) or too specific to someone else’s situation to be useful for yours. What actually helped us came from people who shared the messy middle. Not polished case studies from five years later, but real decisions, made in real time, before anyone knew how they’d turn out.

That’s The Blueishprint, which we’ll be publishing on Third Vector’s Substack.

Blue-ish-print. Because a blueprint implies you’ve got it all figured out. We don’t, and in the age of AI things are changing so fast that what we write today may become obsolete tomorrow.

And we won’t be the only ones writing. We’ll bring in co-authors who are building right now and have something specific to share. Every article comes with actual materials. The spreadsheet you can fill in that afternoon. The workshop agenda you can run with your team on Friday. We’ll share the actual tools we used. Prompts, Lucid charts, Claude skills, case studies. Not because we think our way is the only way, but because reading about a GTM strategy is useless if you can’t build one yourself the same afternoon.

The tightrope: product and GTM

Every time either of us starts a new business or project, the approach is roughly the same. You start with the basics: entity, legal, finance, tooling. Get those out of the way so they never become a bottleneck. Then you’re straight into the tightrope.

Product and GTM are a symbiosis. You can’t build something nobody wants, and you can’t sell something that doesn’t exist yet. They need equal attention. The problem is you can’t give them equal attention at the same time. Some weeks you’re deep in product, building, testing, iterating. Other weeks you’re all GTM, talking to people, running experiments, figuring out your channels. The skill isn’t doing both. The skill is knowing when to lean into one and pull back on the other without letting either one fall over.

In Dutch we call this koorddansen. Tightrope walking. And it’s the thing we see founders get wrong more than almost anything else. Either they build for months without talking to anyone, or they sell something they haven’t figured out how to deliver yet.

And the thing that ties all of it together is talking to prospects. That never stops. Every product decision, every GTM move comes back to what we heard in the last conversation. You can have the best frameworks in the world, but if you’re not talking to the people you’re building for, you’re guessing with extra steps.

The cadences need to line up. Operations, product, GTM. How often you review and plan, how fast you ship, how you find and close customers. When they’re out of sync you feel it immediately. You’re building something nobody asked for, or selling something that’s three sprints behind what you promised.

What’s coming

We’ve organized everything into four workstreams — GTM, Product, Finance, and Operations — all published under The Blueishprint.

GTM and Product start now. Finance and Operations will come when they become relevant. Every article comes with templates, prompts, and the actual tools we use. This isn’t a locked roadmap. If you tell us you want something else first, we’ll adjust.

Next week we kick off with getting your GTM strategy on paper. We’ll walk you through writing it, stress-testing it, and building the pipeline to actually execute it. From there the series goes into target lists, lead enrichment, CRM setup, sales sequences, and automated outreach.

The Product series starts with how we capture user feedback and turn it into shipped code, with AI doing most of the grunt work. We’ll share the full setup, from feedback intake to Linear tickets to deployment.

Beyond that: funding (do you actually need it), cap tables, hiring when AI has changed the game, and the personal stuff like how to actually take a holiday when you’re building a company.

The one we’re most looking forward to writing: “I Got Acquired in a Stock Deal. Here’s What Nobody Told Me.” Stock deal vs. cash deal, tax traps, earnout games, and everything that blindsided us. Almost nobody writes about this from the founder’s side.

How we write (and why process beats prompts)

Full transparency: one of us is dyslexic. For most of his career, writing was the last thing he’d volunteer for. AI changed that. We use AI to help us write, to turn messy thinking into clear sentences, to catch errors our brains skip over.

But the thing everyone gets wrong about AI right now? There’s an endless flood of articles about clever prompts and AI skills and “10x your productivity with this one trick.” Open deur, as we say in Dutch: garbage in, garbage out. A prompt is only as good as the thinking behind it. If you feed vague input into any tool, you get vague output.

AI helps us say it clearly. The thinking is ours. We mention this because we think more founders should talk about it. Using AI to write isn’t cheating. It’s a tool, like everything else. And it’s one of the reasons The Blueishprint exists at all.

The community

The Blueishprint isn’t a newsletter you read and forget about. We want to build something where founders and operators raise real questions and work through them together. Someone struggling with their pricing gets input from ten people who’ve been through it. The articles are just the start.

We have an open WhatsApp group you can join right now. It’s live, it’s messy, and people ask real questions in real time. No gatekeeping, no “premium tier.” Just people building things and helping each other figure it out.

Join here.

Your turn

Here’s our question for you: what’s the one thing you’re stuck on right now in your business? The thing you keep circling back to but haven’t cracked yet. Drop it in the WhatsApp group, reply to this email, leave a comment. We’ll either write about it, or someone in the community already has an answer.

And if you know someone who’s in the middle of building something right now, send this their way. The more people in the conversation, the better the answers get.

See you next Tuesday.

— Friso & Tim

Images: Tristar Pictures, Ivan S (Pexels)