How Saral reads talent.

The moment AI could rewrite a resume to mirror a job description, the resume stopped being evidence and became marketing. Everyone who applies now looks qualified on paper, which means the paper tells you very little.

What still holds up is the trail of work: what shipped, when, and with whom. A commit, a launch, a case study, a long-form post. It is harder to fake at volume, and it is far more predictive of what someone will do in the role.

That is why Saral reads public work first and treats the profile as context, not proof.

Half of sourcing is finding capable people. The other half is finding capable people who would actually take the call. Most tools only solve the first half.

Switch intent combines tenure, promotion cadence, recent public activity and market movement into a simple read: likely to move, maybe, settled. It does not decide for you, but it tells you where to spend the first hour of the day.

Email works until it does not. For a large share of candidates in India, a WhatsApp message gets answered in minutes while the same message in an inbox sits unread for a week.

The catch is that WhatsApp needs a different voice: shorter, more direct, and often in Hinglish. Sequences that treat it as a third email perform like a third email.

Saral runs email, LinkedIn and WhatsApp as one sequence with a different register for each channel.