‍Introduction: Why Products Are Built in Conversations Before Code

Before a single engineer opens an editor, before the first prototype is sketched, before sprint planning begins, products are already being shaped by language.

Not code.
Not architecture.
Not tooling.

Language.

The earliest conversations around a product consistently determine its trajectory. These conversations carry assumptions, expectations, and interpretations that are rarely examined directly. A sentence that seems harmless can alter scope, timelines, complexity, or priorities without anyone noticing until the project is deep in delivery.

Misalignment rarely comes from malice or incompetence. It comes from words that feel obvious but actually hide multiple possible meanings.

This article breaks down the most commonly used statements clients say—statements every designer, developer, founder, or product manager has heard hundreds of times. For each, we’ll explore:

• what the client thinks they are saying
  
  
• what the team hears
  
  
• what the statement really means in practical terms
  
  
• the hidden decisions buried inside the phrase
  
  
• how to translate it into clear, actionable product direction
  
  

The goal is not to criticise clients.
The goal is to understand the gap between spoken language and product reality—and to close it.

1. “We want something simple.”

What clients think they’re saying

“Please don’t overcomplicate this. We want the product to feel clean and easy to use.”

What teams often hear

“Build a small, light, minimal product.”

What this statement actually means

A desire for simplicity on the surface, without sacrificing capability under the hood.

Here’s the quiet irony of product development:

Simplicity is almost always the result of sophisticated problem-solving, not the opposite.

Think of “simple” products people love:
Google’s homepage, Apple’s Notes app, Spotify’s player.
Their interfaces are simple because enormous complexity has been hidden beneath them.

The hidden questions inside “simple”

To translate “simple” into actionable requirements, the real questions are:

• Simple for whom? (Customers? Admins? Staff?)
  
  
• Simple in which moments? (Registration? Daily use? Payments?)
  
  
• Simple compared to what? (Competitors? A previous system?)
  
  
• What complexity must be hidden rather than removed?
  
  

Why the phrase is dangerous if taken literally

Teams sometimes remove functionality in the name of simplicity, only to realise later that the product no longer solves the core problem.

“Simplicity” is not about features. It’s about mental load.

A clearer translation

“We want the product to feel effortless, even if it requires complex logic beneath the surface.”

2. “We want it scalable.”

What clients think

“We don’t want the product to collapse if we grow.”

What teams hear

“Build a robust architecture from day one.”

The actual meaning

“Scalable” usually concerns future-proofing rather than present needs. But scalability is not a single decision—it’s a series of trade-offs.

Scalability affects:

• database choices
  
  
• hosting strategy
  
  
• queueing and caching
  
  
• how features are modularised
  
  
• how data is stored and retrieved
  
  
• cost flexibility
  
  

The hidden issue

Scalability can triple the effort of a project if it’s built for growth that won’t happen for years.

Many early-stage products need “scalable enough,” not “enterprise-grade from day one.”

A better translation

“Build for realistic short-term growth, but design in a way that allows future scaling without rewriting everything.”

3. “We want it fast.”

This phrase has two meanings, often delivered simultaneously:

A. Fast to build (timeline)

Clients want quick delivery.

B. Fast for users (performance)

Clients want the product to feel fast.

These two priorities often clash.

The hidden trade-offs

Speed of development vs speed of performance vs speed of change.

• If you want fast performance, you may need heavier engineering work.
  
  
• If you want fast delivery, you probably need to simplify features.
  
  
• If you want fast future changes, you must invest in clean architecture now.
  
  

You can have all three—just not at the same time.

A clearer translation

“We want speed, but we need help prioritising which kind of speed matters most for our stage of growth.”

4. “We’ll send you a few examples of what we like.”

What clients think

“It’s helpful to show visual direction.”

What teams hear

“These examples define the scope, complexity, and UX expectations.”

The truth

A set of screenshots or competitor links rarely shows the architecture, logic, or hidden behaviour behind the design.

Why examples can be misleading

• A visually simple interface might require advanced systems.
  
  
• A beautiful design might depend on expensive third-party services.
  
  
• A competitor’s feature might have taken years to evolve.
  
  

What examples actually do

They communicate taste, not requirements.

A better translation

“Here’s what inspires us visually—help us understand what it would take to achieve a similar experience.”

5. “We want it to work like [big company].”

Amazon, Uber, Airbnb, Spotify—these names come up constantly.

What clients mean

“We want this experience to feel frictionless, intuitive, and polished.”

What teams hear

“Replicate a product built by a thousand-engineer team with unlimited budgets.”

The gap

Large companies have:

• huge data sets
  
  
• vast engineering teams
  
  
• advanced operational systems
  
  
• years of refinement
  
  
• dedicated teams for each component
  
  

A startup or small organisation cannot match this on day one—and should not try.

The productive interpretation

Rather than copying the product, identify the principles behind it:

• one-tap actions
  
  
• minimal cognitive load
  
  
• strong onboarding
  
  
• helpful defaults
  
  
• resilience in edge cases
  
  

A better translation

“We want the experience-level quality of big tech, but shaped realistically for our scale.”

6. “We want AI in the product.”

What clients think

“AI will make the product smarter and more competitive.”

What teams hear

“Unclear scope. Possibly unnecessary complexity.”

The core issue

AI is not a feature.
AI is a capability that solves specific problems—if those problems exist.

Hidden questions

• What decision is the AI making?
  
  
• What data will train it?
  
  
• What risks exist if the AI is wrong?
  
  
• How often must it improve?
  
  
• Does AI actually solve the user need—or is it a branding desire?
  
  

The danger

AI often gets added where simpler automation or logic would perform better.

A clearer translation

“We think AI might add value—help us determine where (and if) it genuinely improves outcomes.”

7. “We don’t know exactly what we want yet.”

What this really means

“We understand the problem but not the solution.”

This is perfectly normal.

The hidden opportunity

This moment is where true product work happens—mapping user behaviours, identifying constraints, validating assumptions.

The risk

Without structure, exploration becomes endless revision.

The productive approach

Convert uncertainty into:

• user journeys
  
  
• problem statements
  
  
• prioritised features
  
  
• measurable outcomes
  
  
• constraints and boundaries
  
  

Without these, projects drift.

The real translation

“We need help transforming unclear ideas into clear decisions.”

8. “We just need the backend/front-end only.”

What clients think

“Dividing responsibilities makes the project cheaper.”

What teams hear

“This could create gaps that are hard to coordinate.”

The reality

Front-end and back-end are not independent layers. They are deeply intertwined.

A “back-end only” request still requires:

• understanding the user flows
  
  
• agreeing data structures
  
  
• coordinating error states
  
  
• syncing timing and interactions
  
  

A “front-end only” request still requires:

• backend endpoints
  
  
• data shape
  
  
• system logic
  
  
• authentication details
  
  

A clearer translation

“We want to divide responsibilities, but we need alignment to avoid miscommunication and hidden technical assumptions.”

9. “It’s just like [another system], but with a few changes.”

Hidden truth

There is no such thing as “just like… but.”

That combination of words hides enormous complexity.

Changing anything in a system—data structure, workflow, permissions, automation—creates cascading effects.

Why this phrase appears

Clients use something they already know as an anchor point.
It helps them conceptualise the direction.

Why it’s risky

A familiar reference can trick teams into underestimating how different the new product actually is.

A better translation

“We're using this system as a conceptual reference, not a literal blueprint.”

10. “Can we add just one more small feature?”

In almost every project, a moment arrives when someone says, “It’s tiny — it won’t change anything.” It’s a natural instinct. On the surface, the feature seems harmless, self-contained, and insignificant. But product teams know there is no such thing as a truly isolated addition. Every feature interacts with something else, and those interactions create complexity that isn’t visible at first glance.

A seemingly simple checkbox might require new validation rules.
A new filter might require changes to how data is stored.
An extra button might introduce an entirely new permission state.
And a small workflow tweak might force updates to analytics, onboarding, or caching.

What appears tiny in interface terms can be enormous in architectural terms.

This is why product teams often respond cautiously to small feature requests late in the development cycle. They’re not resisting agility; they’re protecting coherence. Behind each addition lies a chain reaction that spreads across UI, logic, data, and maintenance. Even minor changes can create misalignment between earlier assumptions and new requirements.

Timing Is Everything

Adding a feature is rarely the problem.
Adding it at the wrong moment is.

Introducing a feature early may be easy and inexpensive. Introducing the same feature late, after other components rely on established patterns, could require restructuring work that far outweighs the feature itself.

This is why the question must shift from:
“Is the feature small?”
to:
“What will this feature touch?”

A More Productive Framing

The more helpful conversation is not about size at all. It is about impact and timing.

A clearer, more transparent translation becomes:
“We’ve discovered a new need — help us understand the consequences of adding it now, and whether it’s wiser to include it later.”

This framing supports better prioritisation, minimises disruption, and ensures the product evolves thoughtfully rather than reactively.

11. “We want to future-proof everything.”

The intention

Avoid rebuilding later.

The consequence

Overbuilding too early.

Future-proofing sounds responsible, but it often builds for a hypothetical future that never arrives.

The better approach

Design the system to adapt, not to predict.

A clearer translation

“Make future changes possible without needing to rebuild the foundations—but don’t optimise prematurely.”

12. “We’ll handle the content ourselves.”

What clients think

“We’ll fill in the text and images later.”

What teams know

Content is not an afterthought—it is the backbone of UX.

Without real content:

• layouts break
  
  
• flows feel different
  
  
• tone misaligns
  
  
• onboarding doesn’t make sense
  
  
• compliance is missed
  
  

A clearer translation

“We plan to provide content, but we need guidance on structure, tone, and constraints so the product works properly.”

13. “Users will figure it out.”

Hidden meaning

“We don’t want to overthink UX.”

The problem

Users rarely “figure things out.”
If something is unclear, confusing, or effort-heavy, they leave.

By the time users complain, you’ve already lost the ones who won’t.

A clearer translation

“Let’s prioritise usability testing to validate whether our assumptions are correct.”

14. “We’ll fix it after launch.”

On the surface, “We’ll fix it after launch” sounds pragmatic. It implies flexibility, openness to iteration, and a willingness to shape the product around real user feedback rather than theoretical assumptions. In an ideal world, this mindset promotes learning and prevents teams from over-polishing features nobody needs.

However, there is a crucial distinction between iterating intelligently and deferring essential decisions. And this distinction often gets lost in early conversations.

Teams know, from experience, that not everything can be “fixed later”. Some foundational choices—architecture, data structure, onboarding logic, navigation hierarchy, integrations, security patterns—become significantly more expensive and time-consuming to modify once the product is in the wild. The cost curve of change is not linear; it spikes dramatically once users are active, dependencies multiply, or compliance boundaries take effect.

Post-launch is an excellent moment for gathering behavioural insights, uncovering unexpected usage patterns, and validating hypotheses. But it is a terrible time to correct structural misalignment that should have been clarified before development began.

The Hidden Risks Behind the Phrase

When clients say “We’ll fix it later,” they often mean:

• “We don’t want to get stuck in lengthy debates now.”
  
  
• “We’re not fully sure what we want yet.”
  
  
• “We’d prefer to see it live before making a decision.”
  
  

All understandable instincts. But without careful framing, this mindset encourages ambiguity at precisely the stage when clarity matters most.

The result?
Teams build features on top of assumptions rather than decisions. When those assumptions prove incorrect, the team must rework not just the surface-level interface but deeper logic, flows, or data models. What could have been a small adjustment becomes a multi-sprint reconstruction.

The Healthy Version of “We’ll Fix It Later”

A productive interpretation of the phrase is not about delaying decisions; it is about categorising decisions.

Some elements must be correct at launch:

• the core user journey
  
  
• the product’s structural logic
  
  
• key data flows
  
  
• reliability and security foundations
  
  
• essential compliance requirements
  
  

Other elements can (and should) evolve:

• microcopy
  
  
• secondary features
  
  
• interface refinements
  
  
• expanded functionality
  
  
• growth-related enhancements
  
  

The more useful statement becomes:
“Let’s identify what needs to be right on day one and what can mature as we learn.”

This reframing protects the product from costly rework while preserving the value of iteration. It ensures that “fixing it later” becomes a strategic choice, not a blind hope.

15. “We just need the MVP.”

Why MVPs Fail More Often Than They Succeed

The term “MVP” is one of the most misused words in product conversations. It sounds efficient, strategic, and lean — a way to minimise cost and validate ideas quickly. But in practice, MVPs collapse when the intent behind them becomes distorted by expectations, assumptions, or organisational pressure.

A common misconception is that an MVP is simply a “lighter version” of the final vision. This framing is dangerous because it encourages teams to strip features based on size rather than purpose. The result is a product that is small, yes — but not meaningful. It lacks the element that actually produces learning.

A true MVP has one priority:
to reduce uncertainty.

That uncertainty may relate to desirability (do people want this?), feasibility (can this be built reliably?), usability (do users understand it?), or viability (will customers pay?). Each of these questions demands a different expression of “minimum”. Sometimes you need only a landing page. Other times you need a working prototype. Occasionally, the smallest learning unit is surprisingly complex because the behaviour being tested cannot be captured with a superficial interface.

The Role of Focus in MVP Success

One of the greatest risks to any MVP is the slow creep of multiple agendas. Each stakeholder adds “just one more” small requirement — a report for the operations team, a filter for marketing, a dashboard for leadership. None of these is harmful individually, but collectively they destroy the clarity of purpose. The MVP becomes a political artefact rather than a learning tool.

The moment an MVP becomes a tool to satisfy everyone, it stops being an MVP.

Another common failure is copying competitors. Teams assume that a feature exists elsewhere because it is essential. But a competitor’s features reflect their business model, stage of growth, user base, and constraints — not yours. Including a feature “because others have it” injects assumptions instead of testing them.

Reframing the MVP as a Decision-Making Tool

A real MVP is not an early product. It is a controlled experiment, disguised as one.

Its goal is not to impress users or deliver a polished experience — it is to trigger behaviour that reveals something important. When framed this way, the MVP shifts from “the first version of our app” to “the smallest, cheapest, fastest method to validate whether our idea is worth pursuing further.”

This translation is crucial:
“We need the smallest product that tells us whether the idea deserves further investment.”

That mindset protects teams from overbuilding, keeps focus razor sharp, and accelerates progress not through speed, but through clarity.

Conclusion: Better Products Begin With Better Conversations

Every phrase clients use carries meaning far beyond the words themselves. These statements reveal hopes, fears, pressures, expectations, and assumptions.

Successful product development does not begin with design or code.
It begins with alignment.

The real work is:

• unpacking vague statements
  
  
• turning abstract desires into concrete decisions
  
  
• questioning assumptions early
  
  
• identifying trade-offs
  
  
• clarifying what truly matters
  
  
• agreeing on what can wait
  
  

If teams learn to decode the everyday language spoken in early meetings, they prevent months of misdirection and build the right product—intentionally, not accidentally.

Good products are built with expertise.
Great products are built with clarity.

And clarity always starts with a conversation.

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