The “Signal Farming” Trap: How Startup Founders Accidentally Optimize for VC Attention Instead of Product–Market Fit

Founders rarely choose to abandon product–market fit (PMF) in favor of investor attention. It usually happens gradually, through incentives that feel rational in the moment: a pitch competition here, a “milestone” dashboard there, a carefully orchestrated PR spike that buys another month of runway.

Over time, a company can become excellent at producing signals—the credible, legible markers that VCs use to infer quality—without becoming excellent at producing value—the thing customers pay for, stick with, and tell others about.

This is the signal farming trap: optimizing the business for what funders can measure quickly, rather than what customers prove over time.

This article takes a contrarian stance: many common startup rituals (demo days, traction updates, press, social metrics, fundraising narratives) are not neutral. They shape strategy. They can distort product priorities, hiring, and even ethics. And they can leave a company with impressive fundraising outcomes and weak market outcomes.

But it’s not as simple as “fundraising is bad.” Venture capital exists for a reason, and signals exist because uncertainty is real. The goal is to distinguish:

Below is a framework to spot when the substitution is happening and how to correct course.

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1) What are “signals,” and why do VCs rely on them?

In early-stage investing, ground truth is scarce:

So VCs use signals—proxies that correlate with outcomes across a population of startups.

Common examples:

These aren’t irrational. They’re part of how capital markets operate under uncertainty (see venture financing and information asymmetry literature; foundational concepts appear across works like Akerlof’s "The Market for Lemons" on asymmetric information, and venture signaling research in entrepreneurship journals).

The problem is that once founders understand the signals, they can start producing them directly—sometimes consciously, often unconsciously—without building the underlying product value that the signals are meant to indicate.

That’s signal farming.

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2) Why founders drift into signal farming (even when they know better)

The trap isn’t about intelligence. It’s about incentives and time horizons.

2.1 Fundraising has a shorter feedback loop than product truth

But PMF often takes:

Founders naturally gravitate toward the loop that rewards them sooner.

2.2 Runway converts attention into survival

If you’re low on runway, VC attention isn’t vanity—it’s oxygen. That’s why the most dangerous signal farming happens when:

Runway pressure pushes founders to optimize for what closes a round, not what creates durable customer pull.

2.3 Accelerators and demo days can bias toward performative progress

Accelerators can be enormously valuable—especially for networks, recruiting, and speed. But demo-day culture can inadvertently reward:

If the company internalizes “look investable” as the primary goal, it may postpone the messier work of building something people truly rely on.

2.4 Social proof loops are addictive

Startup Twitter/LinkedIn, podcasts, newsletters, and press can create a loop:

This loop can outcompete the quieter loop of retention, customer support, and incremental product quality.

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3) The most common forms of “traction theater”

“Traction theater” is the staged performance of progress. It’s not always fraudulent; it’s often a set of choices that maximize investor excitement while minimizing the revelation of underlying weakness.

3.1 Vanity metrics dressed as growth

Examples:

Why it works: Many investors (especially generalists or those moving fast) accept surface growth as a proxy for demand.

Why it fails long-term: Companies eventually hit the wall of unit economics and retention reality.

References/anchors:

3.2 One-time spikes mistaken for repeatable channels

These can be useful, but they’re not a channel until they’re repeatable and scalable.

A classic smell: “We grew 40% last week.” If that growth is from a one-off event, it’s not learning, it’s fireworks.

3.3 Logo collecting without depth

Enterprise founders know this well:

Those can be legitimate steps. But a company can end up collecting logos instead of building a product that survives procurement, integration, security review, and renewal.

A practical question: Do you have referenceable champions and renewal intent, or just a slide?

3.4 Demo magic with hidden scaffolding

Wizard-of-Oz approaches can be smart during discovery (they’re a known technique in lean experimentation), but signal farming happens when:

3.5 Narrative arbitrage

This is when the company continuously rebrands to match investor fads:

Good companies evolve. Signal-farming companies reshuffle adjectives faster than they accumulate customer proof.

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4) When signals distort product strategy and team priorities

Signal farming isn’t just a marketing issue. It changes what the company builds.

4.1 Roadmaps become investor calendars

The roadmap is anchored to:

rather than to customer learning cycles.

This creates an anti-pattern:

In B2B, this is lethal. Reliability and trust are the product.

4.2 Teams optimize for “pitch readiness” instead of customer value

You see priorities like:

All of these can be legitimate at the right time. The distortion happens when it pulls the company away from:

4.3 Hiring shifts toward optics

Hiring can become signal farming too:

A subtle version: hiring people who are great at telling the story rather than making the story true.

4.4 Incentives start to drift

Internally, people learn what gets rewarded:

rather than:

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5) The case for signals (the balanced view)

Signals aren’t inherently bad. In many cases, signals are the best available data.

5.1 VCs need heuristics

Given the volume of startups and the uncertainty involved, VCs must triage.

High-quality signals:

5.2 Fundraising itself can be a strategic tool

Capital can buy:

For some businesses (deep tech, biotech, hardware, infrastructure), venture funding is often essential.

5.3 Some “theater” is just communication

A clear narrative and clean metrics aren’t deception; they’re how you communicate.

The line isn’t “polished vs unpolished.” It’s:

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6) A framework: How to detect signal farming in your startup

Here’s a practical diagnostic framework: The Signal–Value Alignment Map.

Step 1: List the top 10 signals you’re currently optimizing for

Examples:

Be honest. Include the implicit ones (e.g., “founder Twitter presence”).

Step 2: For each signal, write the underlying customer value it’s supposed to indicate

Examples:

Step 3: Test the causal link: does the signal force value creation?

Ask:

If you can hit the signal while customers remain indifferent, it’s a high-risk signal.

Step 4: Identify “substitution pathways” (how you could fake it without lying)

This is key. Many distortions are non-fraudulent. They’re just selective optimization.

Examples:

If substitution pathways are easy, the signal is vulnerable.

Step 5: Add a “truth anchor” metric that’s hard to fake

Good truth anchors:

PMF is context-dependent, but retention + willingness to pay is hard to argue with.

References/anchors:

Step 6: Create a “signal budget”

Decide explicitly how much time you will spend on investor-legible work:

…and cap it.

A common operating rule for early PMF stage: 80–90% of effort goes to customer value and learning, 10–20% to fundraising readiness. The exact ratio varies, but the key is that it’s intentional.

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7) Practical countermeasures (without becoming anti-VC)

7.1 Replace milestone goals with learning goals

Instead of:

Use:

These produce compounding value even if fundraising timing shifts.

7.2 Build an “investor-safe” metrics stack that doesn’t distort behavior

Your investor update metrics should be the same ones you use to run the business.

A simple set:

If you find yourself maintaining one dashboard for investors and another for reality, you’re drifting.

7.3 Pre-commit to integrity in metric definitions

Write definitions down:

This prevents subtle slippage under pressure.

7.4 Slow down the narrative churn

If your positioning changes every few weeks, it’s usually a smell.

A better approach:

If you must pivot, articulate:

7.5 Incentivize the team around customer outcomes

In performance reviews and team rituals, celebrate:

If the loudest celebration is “we got a term sheet,” don’t be surprised if the culture optimizes for the next one.

7.6 Fundraise in tighter bursts

Fundraising can sprawl and consume the company.

Try:

This reduces the chronic attention tax.

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8) Red flags: How you know the trap is already sprung

These are patterns that show up across companies stuck in signal farming:

That last one is particularly telling.

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9) What to do if you’re already deep in signal farming

You can unwind it, but you have to be concrete.

9.1 Declare a “PMF reset” period

A reset is not a vibe; it’s a scoped project.

Timebox it (e.g., 6–10 weeks) and measure progress with truth anchors.

9.2 Shrink burn to reduce fundraising dependence

Signal farming thrives when survival depends on constant capital.

Reducing burn (even temporarily) buys you the freedom to pursue product truth:

This is unglamorous and often decisive.

9.3 Rebuild around a single “core loop”

If you have PMF, you can usually describe a loop:

If you don’t have a loop, you have a sequence of campaigns.

Focus on the smallest loop that could work, then iterate.

9.4 Be honest with investors (good ones will respect it)

The best investors prefer:

over continued theater. If an investor punishes honesty, that’s information too.

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10) Closing view: Don’t confuse legibility with inevitability

Signal farming is ultimately a confusion between:

A startup can be highly legible—beautiful deck, famous angels, crisp metrics—without being inevitable.

PMF is not a narrative. It’s a sustained behavioral pattern in customers:

Use signals, but don’t worship them. The best version of venture-scale success is when your fundraising story is simply the byproduct of a product that customers would miss if it disappeared.

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References and further reading (non-exhaustive)

If you want, I can also add a short “Founder checklist” appendix (one page) or rewrite this for a specific startup type (B2B SaaS, devtools, consumer social, marketplaces, AI products), because the truth-anchor metrics differ by category.