👋 Ertuğrul Çavuşoğlu — Product & AI Leader
      Co‑founder & CEO at Mindlid (Google‑featured). Previously led Emma Up (Apple‑featured). I build AI products that raise adoption, cut cost per task, and harden quality.
- Mindlid — Google showcase
 - Emma Up — Apple feature · Reuters, Yahoo & Yahoo Finance · 12k‑view user story
 - UserGuiding — Covid Meter & Resource Center · 2× Top‑5 Product Hunt
 
Product & technology leader (7+ yrs) across consumer AI, SaaS & IoT. Led cross‑functional teams (LLM, backend, mobile, design). I use lightweight, evidence‑driven frameworks (A→O, MAP, OEL‑7, V→O) to ship fast without breaking trust.
Work
Use this grid to browse case studies. Each card opens a detailed case page.
Mindlid — Case Study
Role: Co‑founder & CEO / Acting CPO (2024– )
One‑liner: Non‑clinical emotional‑wellness app showcased by Google for context‑aware AI.
Context & Team
- Anticipated GenAI’s #1 consumer use case (companionship/therapy) pre‑HBR validation.
 - Assembled founding team across AI, product, design, and mobile (senior contributors).
 - Two strategic pivots to a differentiated non‑clinical scope with clear guardrails.
 
Problem → Bet
- People want an accessible, private way to feel seen, relieved, and hopeful—without clinical claims.
 - Bet: structured, therapy‑inspired programs + tone customization + couples mode can reach mass adoption if reliability and cost stay in check.
 
Constraints
- Investor‑safe: privacy, safety, non‑clinical language.
 - Cost/latency targets per route; eval gates before shipping.
 - Small team, rapid iteration cadence.
 
What I led
- Product vision & operating system (V→O); roadmap & success metrics.
 - Program design (Couples, Quick Relief, Tone Customization).
 - LLM stack & reliability: PCW‑3 (prompt • context • workflow), EQA‑5 (evals‑as‑QA), CEAS‑6 (cost).
 - Early GTM loops, activation instrumentation, research & usability cycles.
 
Key Decisions
- Non‑clinical scope with crisis resources and refusal policies.
 - “Outcome before output:” A→O tests weekly (OEL‑7).
 - Context discipline + caching to keep CPT low; validator/formatters for safety.
 
Results (selected)
- ≥90% purchase intent across 100+ early users.
 - Google showcase at Gemini Embeddings launch (context‑aware emotional AI).
 - Demo + teaser unlocked partner and investor interest.
 
Refs: HBR: How people are really using GenAI (2025) · Google Developers Blog: Gemini Embedding
Emma Up — Case Study
Role: Head of Product & Technology (Founding Team) · Emma — The Sleep Company (2023–2025)
One‑liner: Apple‑featured sleep & habit coach; covered by Reuters, Yahoo & Yahoo Finance.
Context & Team
- Led Backend, AI, QA Automation, Flutter, and Design inside a 1,000‑employee org.
 - Rebuilt the app to PMF; leveraged high‑traffic web and paid channels.
 
Problem → Bet
- Fragmented sleep advice didn’t translate into sustained behavior change.
 - Bet: combine passive signals + habit coaching + crisp onboarding to drive retention and revenue.
 
What I led
- End‑to‑end redesign and growth systems (onboarding, paywall, retention loops).
 - LLM features analyzing 19 sleep & habit parameters for personalized challenges.
 - Integration with Asleep (Korea) for hands‑free, sound‑based tracking.
 - Data plumbing, instrumentation, and experiment cadence (weekly).
 
Key Decisions
- Checkout integration for direct EBIT impact.
 - “First value in minutes” onboarding; reduce cognitive load and steps.
 - Price/plan experiments aligned to habit momentum.
 
Results (selected)
- Two‑digit million‑euro EBIT impact via checkout integration.
 - 7.8× improvement in 6‑week retention (qualified users).
 - 20× improvement in Month‑3 subscription retention vs prior year.
 - €500k+ internal funding secured to scale the AI Sleep Coach.
 
Demos: User Testimonial (12k views) · Launch Video
UserGuiding — Case Study
Role: Product Manager (2019–2021)
One‑liner: Drove adoption and growth; Top‑5 Product Hunt ×2.
Context
- Mid‑market SaaS with self‑serve onboarding.
 - Needed higher feature discovery and stickiness without heavy services.
 
Problem → Bet
- Users weren’t finding help at the moment of need.
 - Bet: Resource Centers + guided prompts + better analytics would lift activation and usage.
 
What I did
- Discovered & shipped Resource Centers (contextual help hub).
 - Built analytics with BigQuery and PostgreSQL; instrumented core features.
 - Launched Covid Meter and refined guided prompts for timely value.
 
Results (selected)
- 60% adoption of Resource Centers in 2 months (beta).
 - Top‑5 Product Hunt ×2.
 - +40% engagement on core features.
 - ARR +500% (~10% MoM); supported a $1M seed round.
 
EMnify — Case Study
Role: Growth Product Manager (2022–2023)
One‑liner: PLG improvements across onboarding and evaluation flows.
Problem → Bet
- Activation friction and time‑to‑value blocked growth.
 - Bet: checklists + interactive help + prepaid/eval flow redesign would speed value and lift conversion quality.
 
What I did
- Onboarding Checklists v1 + Interactive Help.
 - Prepaid balance & evaluation card flow redesign (shortened steps, clearer value).
 - Integrated PQL initiatives with Salesforce.
 
Results (selected)
- Activated users ↑41% in 3 months; new daily record for evaluation orders.
 - Time‑to‑value ↓90% (1h25 → 9m).
 - Incentives campaign drove 54% of evaluation orders; signup→activation ↑20%.
 
Frameworks & Advisory
🧪 Light‑touch, outcomes‑focused advisory (TAVOS AI Labs). I help non‑competing teams ship useful, affordable, reliable AI features and tighten PLG.
Signature frameworks
- A→O Cycle — Start with a measurable Outcome, test the riskiest Assumption, ship only after a PASS.
 - V→O Product OS — Compass → Outcomes → Discovery → Moves/RATs → OEL‑7 → Delivery → Readout.
 - MAP — Motivation • Ability • Prompt — pick the biggest leak, run one high‑power experiment.
 - OEL‑7 — Define → Design → Build → Launch → Read → Decide (in 7 days).
 - PCW‑3 — Prompt • Context • Workflow for LLM quality.
 - EQA‑5 — Evals‑as‑QA: reliability, safety, regression control.
 
Advisory scope
- AI feature scoring
 - LLM routing and cost discipline
 - Evals harnesses
 - Activation, paywall, retention clinics
 - Deck and pitch tune‑ups
 - Portfolio support for funds and accelerators
 
Operating principles
- Time‑boxed (≈4–6 hrs/wk), no direct emotional‑wellness competitors, clean data and IP separation.
 
Talks & Press
Podcast
Podcast: “AI in 5” — AI in 5
Press
- Reuters: Discover how Emma — The Sleep Company is helping people across the globe to awaken their best
 - Yahoo: Emma’s sleep app gets major AI upgrade to help track and improve your sleep
 - Yahoo Finance: Emma — The Sleep Company Launches its Own Digital AI Sleep Coach, Emma Up
 - Emma Up User Testimonial (12k views)
 - Mindlid Google showcase — Gemini Embedding: Powering RAG and context engineering
 - Product Hunt Top‑5 — Resource Center · COVID‑Meter
 
About
I’m a product and technology leader focused on AI‑powered consumer and SaaS products. I co‑founded Mindlid, a Google‑showcased emotional‑wellness app, and previously led Emma Up, an Apple‑featured sleep and habit coach covered by Reuters and Yahoo Finance. My work has driven multi‑million‑euro impact, ≥90% purchase intent, and multiple Top‑5 Product Hunt launches. Through TAVOS AI Labs, I advise startups and VC portfolios using lightweight, evidence‑driven frameworks to raise adoption, cut cost per task, and harden reliability.
Education & Certifications
- Law (CUSL, Magna Cum Laude), University of Cologne
 - Stanford Continuing Studies — Product Management (GPA 4.00)
 - Reforge — Product Strategy; Mastering Product Management
 
Honors & Awards
- Transparency Award (Youth) — Transparency International Turkey (grant by Swedish Consulate‑General)
 
Publication
- Life Processed (2024) — short guide to transformative self‑improvement with AI (REST, RISE, MAP)
 
Volunteer
- Product School — Product 200 Founding Member
 
Skills
Product Leadership · LLM Systems · PLG and Growth · RAG/Context · Prompt and Workflow Design · Evals‑as‑QA · Analytics
Contact
✉ Let’s work together
Email: ertugrul@ertugrulcavusoglu.com
      LinkedIn: linkedin.com/in/ertugrulcavusoglu