Ramit Agarwal

Senior PM shipping 0-to-1 consumer & developer products. 4+ years across RTC, SDK / API platforms, and AI. A career, modeled as a neural net.

aramit757@gmail.com
scroll to activate the network
// highlights
// the network

career.forward()

2018 — 2022Input LayerLNMIIT · B.Tech CS2021 — 2022SDE InternHuddle012022 — 2025Product ManagerHuddle012025 — presentSenior Product ManagerHuddle01Side projects · NowOutput LayerWhat the net predicts
Achievement
Skill
Moment
// optimizing

gradient.descent()

loss = α·(1−Impact) + β·(1−Ownership) + γ·(1−Curiosity). Each epoch is a career checkpoint. Watch the ball roll, or hover a dot.

epoch →loss ↑ε0ε1ε2ε3ε4
weights @ epoch 0
Impact0.10
Ownership0.15
Builder's Curiosity0.55
loss0.77
ε0 · init // weights initialized — curious, but unproven
lr0.60
epoch 00 / 04
// layer index
L0 · 2018 — 2022
Input Layer
LNMIIT · B.Tech CS

The signals that get fed into the network.

3 neurons
L1 · 2021 — 2022
SDE Intern
Huddle01

Wrote the integrations. Learned the stack from the inside.

6 neurons
L2 · 2022 — 2025
Product Manager
Huddle01

Moved from writing code to writing specs, growth loops, and dashboards. Scaled Meet 3x YoY and SDK usage 10x.

13 neurons
L3 · 2025 — present
Senior Product Manager
Huddle01

Owning launch execution end-to-end. Launchpad, KYC, growth loops, and cross-functional strategy.

8 neurons
L4 · Side projects · Now
Output Layer
What the net predicts

The forward pass keeps going.

4 neurons