Not a ticket PM
Backlog grooming with no customer contact and no outcome ownership? We'll both be frustrated within the first sprint.
Product Manager · Builder · Hyderabad, India
Product Manager
The PM who talks to users Monday, writes the spec Tuesday, argues with engineering Wednesday, ships Thursday, reads the data Friday.
6+ yrs
6 industries
70% F100
Live SaaS MVP
Security · Marketplace · Retention · Health · EdTech
Or jump straight here — who are you?
01 — Evaluation cockpit
Build your rubric. I'll match the evidence to it.
Senior PMs scan for signal against what they need — not every bullet. This mirrors that process. The site is the product demo.
01Who is evaluating?
02What must be true to hire me?
03How much depth do you need?
Evidence match to rubric—
02 — The argument
"Titles are cheap. The right call when data is thin and the org disagrees — that's the actual job."
Six years across domains that punish shallow PM work: enterprise DevSecOps, global marketplace funnels, retention analytics, regulated healthcare, ed-tech 0→1 — plus a live SaaS I built and shipped myself. Not breadth for the CV. Pattern transfer under constraint, compounded.
0Years shipping product
0Industries — patterns transfer
0F100 context · current role
0Live SaaS · shipped solo
03 — Proof vault
Decisions with receipts.
Decisions with receipts.
Click any card to open.
Integrity note — I don't inflate roles, round up metrics I didn't own, or list tools to look technical. Direct references available on request.
04 — Judgment lab
Two calls I'd defend in your debrief
Pick a move first — then see the reasoning ladder.
Context — E-commerce marketplace. Listing completion is 40% below target. GMV is bleeding. Leadership wants a roadmap fix in Q2. Engineering has 6 weeks of capacity. What is your first move?
What I actually did — and why it was the only defensible call
Mapped the full seller journey before touching a single pixel. Found 3 exact drop-off points via funnel analysis. Ran targeted UX experiments at those leaks — not a six-week rewrite, not a support band-aid. Built dashboards the ops team used daily for months after.
ObserveFunnel geometry before opinion. 3 leaks beat 40 assumptions.
BetLearning speed under deadline beats looking decisive.
NoFull redesign: too slow to learn. Live support: treats symptoms, not root cause.
SignalDiscovery → sequencing → experiment design → operational metrics. Without saying those words in a single meeting.
Context — DevSecOps platform, Fortune 100 customers. Enterprise clients request 20+ new package ecosystem integrations. Your research lead wants 5 marquee integrations instead — better for ARR. One team. One quarter. What do you recommend?
What I shipped — and the regulatory timing behind it
Breadth across formats plus SBOM compliance ahead of regulation, with enterprise betas before GA. Security engineers instrument daily in CI/CD — not in integration showcase slides. Daily workflow coverage compounds. Marquee demos don't.
ObserveSecurity engineers triage in pipelines — formats cover daily toil, marquee integrations cover sales QBRs.
BetSBOM before the law = market lead. Regulatory tailwind is rare — use it.
No5 marquee integrations that demo well but don't reduce the 1,000-alerts-per-day problem.
05 — Radical honesty
For PMs reviewing this site
When I'm not your hire
The best PMs disqualify fast. This saves us both from a painful 90-day mistake.
Not a slide-deck PM
If success is measured in decks delivered — not experiments shipped and metrics moved — I'm the wrong hire.
Not a lone wolf
I push back on engineering and design before committing. If your culture punishes that tension, I won't thrive.
The portfolio is itself the product demo
06 — Builder proof
I don't wait for the title "builder PM"
Open source · Live · Public · 2026
TokenLens
Engineering teams spending $500–5,000/month on AI coding tools have no idea if they're spending it wisely. Existing tools show cost charts. None tell you why a session cost 4× more than average, or that one config change halves the next bill. No one had built the intelligence layer on top of the data.
I built it. TokenLens assigns every project an A–F Efficiency Score, auto-generates recommendations with dollar savings estimates, detects anomalous sessions, and calculates a developer ROI multiplier — all from local logs, zero cloud dependencies, zero external packages. Full backend, REST API, SPA dashboard, and a built-in pitch deck. Shipped solo.
Market gap → product differentiation → full-stack build → open source release. Same loop I'd run with your founding team.
LIVE DASHBOARD · Click to view on GitHub ↗