Lewis's essay makes a simple claim: one strange text doesn't ruin your day. Your interpretation of it does. Your mind fills in context, invents tone, assigns intent, and then runs on that invented story for hours. We think the same mechanism is doing real damage to how B2B founders approach LinkedIn engagement.
The same pattern that makes a period-instead-of-exclamation-point wreck your mood is what makes B2B founders misread LinkedIn signals and abandon engagement strategies that were actually working. One odd reply, one post that underperforms, one influencer who doesn't reciprocate: the brain spins a narrative. That narrative usually leads to the wrong tactical response. Knowing the pattern is most of the fix.
The signal-reading problem on LinkedIn
LinkedIn is an ambiguous communication environment. Comments go unacknowledged. Reactions arrive with no context. A post you spent real time on gets twelve impressions. A throwaway observation gets three hundred.
Founders we work with consistently describe the same spiral: they engage thoughtfully for a few weeks, then something breaks the rhythm. The influencer they've been commenting on posts something that draws a lot of attention but none of it flows back. A comment they wrote gets buried under sixty others. A reply from someone important reads as cold.
The brain, faced with ambiguity, doesn't stay neutral. It generates an explanation. And the explanations it generates tend to be unflattering: you're in the wrong community, your comments are bad, this person doesn't respect you, the whole strategy is broken.
That explanation then drives behavior. Founders pull back. They start second-guessing what to write. They migrate to different influencers without a principled reason. They reduce their cadence right when consistency would have paid off.
None of the original signals actually told them to do any of that. The signals were ambiguous. The behavior came from the story, not the data.
Why this hits B2B founders harder than most
A B2B founder using LinkedIn as a pipeline channel has revenue and relationships at stake. That raises the interpretive pressure. When a signal feels off, the cost of being wrong about it feels real. So the brain works harder to assign meaning to ambiguous signals, which means it also works harder to invent meaning when none exists.
B2B LinkedIn's feedback loops are slower than consumer social. Pipeline movement can lag visible engagement by six weeks. That lag is where pattern-seeking fills the vacuum.
The founders who survive that lag without abandoning the strategy aren't more patient by temperament. They have a clearer operating model. They've decided in advance what a signal means and what it doesn't, so ambiguous inputs have less room to trigger the narrative machine.
What the essay gets right, and where we'd push further
Lewis's piece is about personal relationships and emotional reactivity. The mechanism he describes is accurate: the gap between a signal and a response is where your mind writes fiction. A period instead of an exclamation point. A slower reply. A slightly different look across a room.
The fix he implies is awareness. Notice when you're doing it. Question the story.
We'd add one layer specific to LinkedIn strategy: build the interpretation framework before the signals arrive.
If you decide ahead of time that a post underperforming means nothing about strategy and only means you haven't found the right moment to engage in that thread, the underperformance doesn't create a vacuum. The vacuum is where the harmful narrative lives.
Concretely, this means:
- Set a minimum engagement window before you evaluate whether a creator relationship is producing anything. Six to eight weeks, minimum.
- Define what "working" looks like before you start. For most B2B founders, that means connection requests from target-profile people or direct messages that reference something you commented on. Not reactions. Not follower counts.
- When a specific signal feels off, write down what you actually know versus what you're inferring. The list of what you actually know is almost always short.
The tactics people reach for when the story kicks in
The most common tactical responses we see when founders start reading ambiguous signals as bad news:
Switching creators. The instinct is that the audience isn't right. Sometimes that's true. More often, the founder hasn't given the relationship long enough to compound. Switching resets whatever equity was building in that comment section.
Changing the comment style. A founder who was writing substantive, specific comments starts writing shorter, safer ones after a few posts feel ignored. The shorter comments are less likely to get noticed, which confirms the narrative, which produces shorter comments still.
Reducing frequency. The logic is that less-frequent engagement will feel more considered and get more attention. What actually happens is that infrequent comments are harder for an algorithm to surface and harder for a creator to recognize. The reduced frequency produces worse results, which the narrative reads as confirmation.
All three of these are rational responses to the story the brain told. None of them are rational responses to what the data actually showed.
The operating model that doesn't get derailed
The founders we audit who build consistent inbound from LinkedIn engagement share one habit: they treat the engagement channel like a content distribution system, not like a social relationship.
A distribution system runs on schedule. You don't check whether the system "liked" your last post. You check whether it's running. Comments go out because that's how the system works, not because you're waiting to see how the last batch performed.
That framing also changes what counts as a signal worth acting on. Real signals in this model: DMs that reference your comments, profile visits that spike after a specific engagement, connection requests from people who match your ICP. Those are worth paying attention to.
Ambiguous signals: a post that got fewer reactions than you expected, a creator who didn't reply to your comment, a week where nothing seemed to move. Those go in the "system is running" bucket, not the "story time" bucket.
We've written about the mechanics of finding the right creators to engage with in finding the right influencers on LinkedIn, and about the broader case for engagement over posting in engaging vs posting on LinkedIn. The operating mindset described here is what makes both of those articles actionable over time rather than just in the first two weeks.
What to actually do when you notice the spiral starting
The spiral is recognizable once you've seen it a few times. You read something into a signal, you feel a mild version of frustration or doubt, and you start generating tactical alternatives. That's the moment.
When you notice it:
Write down the actual signal. Not what it means. What it is. "The post got 40 impressions" or "the creator didn't reply to my comment." That's it.
Then write down what you'd advise a founder you were coaching. Not yourself. A founder whose strategy you respect and whose engagement data looks identical to yours. You'd tell them to keep running the system. You'd point out that six weeks is not a statistically meaningful window. You'd probably also tell them to stop checking the reaction count every four hours.
Then do that.
</p> <h2> <a name="faq" href="#faq" class="anchor"> </a> FAQ </h2> <p><strong>Why does one bad LinkedIn post make me want to quit my whole engagement strategy?</strong></p> <p>Your brain treats ambiguous signals as meaningful even when they aren't. One underperforming post creates a gap in feedback, and the mind fills that gap with a narrative, usually a discouraging one. The narrative then drives tactical changes that aren't supported by the underlying data. Recognizing this pattern is the first step to not acting on it.</p> <p><strong>How long should I engage on LinkedIn before deciding if my strategy is working?</strong></p> <p>For B2B founders building inbound pipeline through engagement, six to eight weeks is the minimum window before you have enough signal to evaluate. LinkedIn's feedback loops are slower than consumer social, and pipeline movement often lags visible engagement metrics by several weeks. Evaluating before that window closes almost always leads to premature strategy changes.</p> <p><strong>What counts as a real signal that my LinkedIn engagement strategy is working?</strong></p> <p>Real signals include direct messages that reference something you commented on, connection requests from people who match your target customer profile, and profile visit spikes that follow specific engagement activity. Reaction counts, follower numbers, and whether a creator replied to a specific comment are not meaningful signals for a B2B pipeline strategy.</p> <p><strong>Why do B2B founders misread LinkedIn engagement signals more than other users?</strong></p> <p>B2B founders have something concrete at stake: revenue and relationships. That raises the interpretive pressure on any ambiguous signal. When a signal feels off, the brain works harder to assign meaning, which means it also invents meaning more readily. Pair that with LinkedIn's slow feedback loops and you have a reliable recipe for misreading a strategy that is actually working.</p> <hr> <p><em>This article was first published on the <a href="https://www.getchime.co/blog/weird-signal-stall-linkedin-day?utm_source=devto&utm_medium=republish">Chime blog</a>. For more on LinkedIn pipeline tactics, <a href="https://www.getchime.co/blog?utm_source=devto&utm_medium=republish">visit the Chime blog</a>.</em></p>
