Tahir Shahzad Product Manager & Community Builder
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Selected Work

Product bets that moved the numbers: from AI at the gate to revenue in the app.

Each case leads with the problem, the call I made, and what actually changed after we shipped.

8 case studies
Teams of 4 – 22
Roles: PM · Product Owner · Agile Coach
All Work 08 0 to 1 01 Agile 01 AI 03 Discovery 01 Growth 01 Ops 03

More case studies

FeedSanitizer.com
0 to 1

FeedSanitizer.com

I had shipped Chrome extensions before, but always to a client spec. Build it, hand it over, and whether it is pleasant to use…

3
Platforms Supported
Discovery

Voice of Customer: Turning Silence Into a Roadmap Signal

The team was building features in silos, largely driven by internal opinion and assumption. There was no structured way to hear from actual users.…

In-app
survey channel reaching real users
Qual + Quant
combined feedback loop
2 quarters
of roadmap reshaped by real signal
Agile

Agile Transformation: Moving From Multi-Month Releases to a Two-Week Cycle

The team was not shipping. New features kept starting before existing ones were ready to release. Work was often functionally complete but never considered…

2 wks
release cycle
0
single points of failure
100%
backlog prioritized
Ops

Custom CRM System: Cutting Developer Support Load in Half

Customer support had no direct way to look up the account, order, or usage data behind a ticket. Every non-trivial question meant filing a…

50%
less developer time on support queries
30%
increase in support case throughput
1 tool
replacing ad hoc SQL requests
Growth

VoIP App Redesign: Fixing the Funnel Before Adding a New Revenue Line

Mobile top-ups, a core digital goods offering, were hard to discover inside the product. The user journey had grown organically over years and buried…

30%
increase in digital goods revenue
1 new
revenue stream (Gift Cards) launched
A/B testing
established as standard practice
AIOps

License Plate Recognition System: Removing the Manual Step, Eliminating Fraud

Manual toll booths depended on an operator identifying vehicle type and typing plate details by hand for every car. This was slow enough to…

100%
unmanned tolling lanes
0
manual data-entry fraud path left open
2
products shipped from one CV pipeline
AI

Facial Recognition App: Reuniting Missing Children

When a child goes missing, information is fragmented across three groups: the family that lost the child, the person who found them, and the…

3-way
intake from families, finders, and authorities
Automatic
match alerts above a confidence threshold
0 to 1
product built from scratch
How I work

The through-line across every case above.

The industries change. The operating loop doesn't.

01

Find the real bottleneck

Spend more time on the problem than most teams do. The obvious complaint is rarely the actual constraint.

02

Pick a wedge, not a platform

Ship the narrowest thing that changes a number this quarter. Platform ambitions come after proof.

03

Instrument before you optimize

If nothing is measured, no debate about "what's better" can be resolved. A/B, funnels, surveys — cheap to add, priceless later.

04

Coach the team, don't own the work

Sprints, retros, small increments. Predictability compounds. Heroics don't.

Interested in the fuller story on any of these?

Happy to walk through the decisions, tradeoffs, and what I'd do differently, over 30 minutes, no pitch.