Harsh Reddy
Why they fit
- Problem -> Change -> Result 25%
The candidate provides clear examples of identifying manual operational friction and building automated tooling to resolve it, directly linking their actions to measurable reductions in manual effort and improved accuracy. However, detailed context on how the friction was originally detected is limited.
Where they fall short
- Evidence-Led Decisions −16 pts
The CV mentions prioritising features with the RICE framework and analysing logistics data, but does not provide examples of decisions being changed, stopped, or shaped by evidence, nor does it share the reasoning behind specific decisions.
- Carries Ambiguous Problems Through to Closure −16 pts
The candidate mentions cross-functional collaboration and streamlining workflows, but there is no specific evidence of navigating a messy escalation, handling failure, or driving an ambiguous issue through to closure with follow-up.
- Builds Repeatable Ways of Working −12 pts
The candidate has created PRD builders, workflow templates, and automated workflows to streamline operations. However, the CV does not clearly demonstrate that these artifacts were adopted and maintained by other team members as repeatable organizational practices.
| Criterion | Weight | Score | Weighted | AI reasoning | Evidence from CV |
|---|---|---|---|---|---|
| Independent Decision Ownership | 30% | 1/5 | 6.0/30 | The CV shows introductory internship experience where the candidate supported product strategy and roadmapping, sometimes directly alongside a Senior PM. There is no evidence of consequential, independent decisions made under uncertainty or trade-offs owned without senior guidance. |
|
| Problem -> Change -> Business/Operational Result | 20% | 2/5 | 8.0/20 | The CV connects interventions to specific metrics (e.g., retention, route efficiency, data accuracy), but frames them purely as solutions and results. It lacks explanation of the underlying operational or business problems being tackled. |
|
| Evidence-Led Prioritisation and Reversal | 20% | 1/5 | 4.0/20 | The candidate mentions prioritizing features using the RICE framework and market research. However, there is no evidence explaining specific evidence-led prioritization, decisions on what to stop, or any reversal of direction. |
|
| Creates Systems Others Run | 15% | 1/5 | 3.0/15 | The CV notes building automation workflows and a no-code toolkit project, but there is no evidence of establishing operating rhythms, team processes, or documentation standards adopted and run independently by others. |
|
| Multi-Party Resolution Under Pressure | 15% | 1/5 | 3.0/15 | The candidate mentions standard cross-functional collaboration and delivery across time zones. There is no evidence of managing escalations, high-pressure situations, post-mortems, or navigating multi-party conflict to resolution. |
|
| Total | 100% | 24 | The candidate presents intern-level experience with strong task execution and metric-driven bullet points across AI tool integration and feature delivery. However, the CV lacks evidence of independent decision ownership, evidence-based direction reversals, organizational system creation, or high-stakes stakeholder resolution expected of a Senior Product Manager. | ||
Scoring scale
- 0: No evidence in the CV
- 1: Indirect or participation-only evidence
- 2: Partial: some elements of the description, weak link to outcome
- 3: One clear example matching the description
- 4: Clear example with a visible result, candidate's own action linked to it
- 5: Repeated, strong examples fully matching the description, with results
Weighted contribution = score ÷ 5 × weight. Every quote is checked against the CV text; if none can be verified, the score is capped at 1.
Evidence
- “Built AI-based data scraping tool, improving data accuracy by 45% and cutting manual effort by 60%” · Problem -> Change -> Result
- “Built AI workflows to automate founder ops, reducing manual workload by 60% and boosting efficiency by 50%.” · Problem -> Change -> Result
- “Defined product roadmap and feature priorities using the RICE framework, aligned with ICP goals and market research..” · Evidence-Led Decisions
- “Analyzed logistics data to enhance fleet operations, boosting route efficiency by 30%” · Evidence-Led Decisions
- “Built AI workflows to automate founder ops, reducing manual workload by 60% and boosting efficiency by 50%.” · Builds Repeatable Ways of Working
- “Shipped PRD builders, roadmap boards, user personas, and automated check-ins using Zapier and embedded forms.” · Builds Repeatable Ways of Working
- “Collaborated cross-functionally across time zones, streamlining workflows and reducing go-to-market time by 3 weeks.” · Carries Ambiguous Problems Through to Closure
- “Owned product strategy by conducting user research, drafting PRDs, and accelerating feature rollout by 30%.” · Gets to the Source Before Designing the Fix
- Boosted website traffic 4.2X by launching first blogs ranked on Google/LLMs and defining SEO/GEO strategy at Troopod.
- Achieved 3.8X subscriber growth for Troopod's first newsletter via SEO and automation.
- Boosted retention by 40% and engagement by 35% through an AI WhatsApp chatbot at Supertext.ai.
- Reduced go-to-market time by 3 weeks and accelerated feature rollout by 30% at Supertext.ai.
- Improved data accuracy by 45% and reduced manual effort by 60% with an AI-based scraping tool at Lets Transport.
- Increased route efficiency by 30% and sped up data processing by 50% at Lets Transport.
- Increased lead conversion by 45% and revenue by 30% using AI-driven outbound automation at Bleedingedge Technologies.
Anonymised CV (exactly what the AI saw)
| | [PROFILE URL REDACTED] | : Portfolio EDUCATION Visvesvaraya Technological University Kalaburagi Bachelor of Engineering in Electronics and Computer Science 2022 – 2026 PROFESSIONAL EXPERIENCE Troopod – Remote (Bengaluru) July 2025 – Present Product and Growth Intern (Product) Defined product strategy for website revamp and SEO/GEO, launched first blogs ranked on Google/LLM’s, boosting traffic 4.2X Defined product roadmap and feature priorities using the RICE framework, aligned with ICP goals and market research.. Developed AI evals and guardrails, leading idea validation, PRD creation, and end-to-end product lifecycle management. Built and scaled first newsletter, achieving 3.8X subscriber growth via SEO and automation.. Supertext.ai – Remote (Bengaluru) Dec 2024 – May 2025 Product Manager Intern ( Founder’s Office ) Built AI WhatsApp chatbot using NLP and APIs, boosting retention by 40% and engagement by 35% Owned product strategy by conducting user research, drafting PRDs, and accelerating feature rollout by 30%. Collaborated cross-functionally across time zones, streamlining workflows and reducing go-to-market time by 3 weeks. Presented product roadmap to stakeholders, boosting adoption by 20% and enhancing operational efficiency by 25%. Lets Transport – Remote (Bengaluru) Nov 2024 – Jan 2025 Product Manager Intern Built AI-based data scraping tool, improving data accuracy by 45% and cutting manual effort by 60% Analyzed logistics data to enhance fleet operations, boosting route efficiency by 30% Drafted PRDs and automation strategies with the Senior PM to support data-driven decisions. Collaborated with engineering and ops to improve tracking systems and speed up data processing by 50%. Bleedingedge Technologies – Remote (Mumbai) Aug 2024 – Oct 2024 Founder’s Office Intern ● Led product execution and project delivery across cross-functional teams, achieving 100% sprint and roadmap success. ● Increased lead conversion by 45% and revenue by 30% using Apollo, Instantly, and AI-driven outbound automation. ● Built AI workflows to automate founder ops, reducing manual workload by 60% and boosting efficiency by 50%. PROJECT EXPERIENCE Micro PM Product Management Made Simple - Live Project ● Built MicroPM, a no-code toolkit that empowers student founders and aspiring PMs to manage product workflows with zero prior experience. ● Shipped PRD builders, roadmap boards, user personas, and automated check-ins using Zapier and embedded forms. InsightLoop AI-Powered Analytics for Product Teams -Live Project ● Built InsightLoop to democratize data analysis for junior PMs and product analysts—launched an AI-powered platform that answers plain-language data queries, reducing SQL dependency by 70%. ● Shipped core features including AI Query Assistant, Funnel Analyzer, A/B Test Analyzer, and SQL Tutor—enabling faster product decisions through cohort insights, retention breakdowns, and auto-generated feedback summaries. SKILLS Product Management: AI Evals , AI Guardrails, AI Prototyping, Roadmapping, Wireframing, Product Strategy, UI/UX, Analytics, Market Research, Prototyping, Lifecycle Management, Competitive Analysis Software Development: Java, Python, C/C++, Verilog, HTML/CSS, API Integration, React.js, Node.js Tools: Jira, GitHub, Trello, Figma, Google Analytics, Miro, Roadmunk, Mixpanel, Confluence, Amplitude, Firebase, Notion, Asana,,Google Analytics. EXTRACURRICULARS Moonturtleio – Failed Founder (No code Platform) Mar 2024 – Dec 2024 Buildspace N/W – Season 5 Graduate (Built Moonturtleio) Jun 2024 – Aug 2024 Learn as You Go – Subject Matter Expert (Solved Doubts for JEE/NEET Students) Oct 2022 – Nov 2023 [CANDIDATE] [EMAIL REDACTED]+91 94473 2081594473 20815 [CANDIDATE]-[CANDIDATE]-product
Interview brief
Briefs are written when you shortlist a candidate.
Email draft
An offer or rejection draft is prepared once you make a decision. Nothing is ever sent without your approval.
Audit trail (3)
- 9/29/2026, 11:36:39 AMsystemanalysis completed{"PM_score":34,"SPM_score":24}
- 9/29/2026, 11:36:39 AMsystemrole assigned best fit{"role":"PM","PM_score":34,"SPM_score":24}
- 9/29/2026, 11:29:32 AMsystemcv ingested{"file":"22_harsh_reddy.pdf","role":"AUTO","redactions":{"name":7,"email":1,"profile_url":1},"name_detected":true}