The Perks of Assuming Good Intention

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My NoSmalltalk session with Shreyas Katta

by Albert Schiller

In professional interactions, particularly in India, there's often a premium placed on maintaining a certain image – projecting competence, agreeableness, and control. It’s a strategy aimed at acceptance and avoiding friction. Yet, my conversation with Shreyas Katta revealed a counter-strategy, one he terms "earning people".

Far from being passive, this approach appears almost algorithmic, a conscious system built on principles that seem counter-intuitive: radical authenticity, the tactical deployment of vulnerability, and a default setting of assuming good intent. It's a method that rejects curated personas in favor of a more complex, ultimately more robust, way of building professional trust and connection.

Authenticity as the Base Layer : Beyond Being "Nice"

Shreyas posits that the simplest, yet most effective, starting point is "just to be myself". He argues against the exhausting effort of trying to be "appropriate," "nice," or constantly seeking acceptance by conforming to others' perceived ideals.

His logic is pragmatic: people ultimately connect with who you are, not a fluctuating concept of who they think you should be. Trying to match an external ideal is inefficient and unsustainable. Authenticity, while seemingly effortless ( "it's really easy for one to be themselves" ), becomes the necessary base layer upon which trust can be built. However, this isn't naïve self-expression; it’s the crucial first step in a system that requires subsequent processing.

Vulnerability as a Feedback Mechanism

Authenticity, by definition, exposes flaws and vulnerabilities alongside strengths. Shreyas contends that hiding these – layering over insecurities like jealousy, for example – hinders trust because others cannot understand the real source of behavior. More critically, hiding flaws prevents the individual from receiving and processing necessary feedback for improvement.

Therefore, allowing vulnerabilities to surface isn't a weakness in his system; it's the essential input mechanism. He explicitly reframes potential criticism not as something to be "bogged down by," but as "feedback" to be processed.

If someone perceives him negatively (e.g., "Albert thinks I talk a lot"), he takes that data point and calibrates his behavior accordingly, tempering his natural tendencies based on the specific interaction. It’s a dynamic process of adjustment, using real-time interpersonal data to refine his approach.

"Early on I learned that I need to be vulnerable... but I also need to be open towards the feedback that I will receive."    

Assuming Good Intent: Optimizing the Equation

The final crucial component of this algorithm is the default assumption of positive intent in others. When faced with potentially negative interactions – someone being upset or disagreeing – Shreyas consciously avoids attributing malice.

He operates on the principle that the issue is likely situational ("Maybe he just can't talk to me about it") rather than intentional ("Albert is upset with me").

This assumption isn't about being naïve; it's a strategic choice to keep communication channels open and give the "equation a better chance". By assuming good intent, he creates space for clarification and resolution ("Hey, Albert, you couldn't speak earlier, could we speak now?") rather than shutting down based on a potentially incorrect negative inference. This proactive framing directly enables the process of resolving disagreements through healthy dialogue, which he views as essential for strengthening trust.

Shreyas Katta's method for "earning people" is more than just interpersonal advice; it's a deduced system. It starts with the efficiency of authenticity, uses the exposure of vulnerability as a data input for calibration, and optimizes for positive outcomes by defaulting to an assumption of good intent.

It's a logical framework designed to build genuine, resilient professional relationships by acknowledging, rather than hiding, the inherent complexities and imperfections of human interaction. It requires conscious effort, moving beyond simple ease to active processing and adaptation, but offers a potentially more robust and sustainable path to earning trust than curated agreeableness ever could.

5 Lessons with practical values

What's next?

Shreyas Katta isn’t performing for approval, he’s building systems for connection. In our May feature of Alba’s NoSmalltalk, we decode his algorithmic approach to trust, where authenticity and vulnerability drive professional relationships. And in the next blog, "Beyond Talent", Shreyas explores why relying on raw ability isn't enough and how shifting from coasting to conscious effort is key to sustainable growth in modern workspaces.