LEANcrush

Building the right product better and faster.

I help startups between Seed and Series A to gain more traction and reach Product-Market Fit (PMF) faster by implementing product discovery and delivery processes that allow them to quickly test and iterate business models.

Recent work:
• 🥫KraftHeinz Venture Builder: led team of 15 to test 30 ideas and deliver 3 MVPs to disrupt the $25b Food Market.
• 💰 Q.ai [backed by Forbes]: built team of 10 and delivered V1 AI-investor to 50k early access users.
• 💊 Menavitin by Pelion: launched a new healthcare product in Germany by executing discovery and design sprints.
• 🤖 Hulecos SA: launched discovery-and-design sprints with an MVP to validate a deep-tech and mobile app business.

By combining world-class methodologies such as Customer Development, Lean Startup, Business Model Generation,Value Proposition Design, Jobs-to-be-Done, you’ll be able to: uncover Big Opportunities, Test Riskiest Assumptions and Build Desirable Products.

Fractional Product Leader

Techstars

Mentored +50 startups on:
- Workshopped with +50 startups on PMF Discovery
- Designing their value proposition, identify critical assumptions to find critical risks 
- Building product and launching experiments
- Multiple industries such as education, health, mobile app, SaaS, eCommerce, and fintech.

Startup Mentor for Product-Market Fit

Toptal

I work as a Product Leader solving pressing product challenges and giant market opportunities.

- Launched an award-winning Robo-investor for Forbes as Interim VP Product
- Led a corporate Venture Builder for Kraft-Heinz

A.Team

I helped A.Team to increase the quality of their network by evaluating +5k PM Profiles and interviewing 350 Product Managers (Designers & Marketers) to find superstar builders from companies like Dropbox, Microsoft, Uber etc.

Lead Product Manager & CPO Interviewer

Founder Institute

Worked with +180 startups:
- Identifying assumptions within their business model and building experiments to validate them.
- Building customer journeys, interviewing customers, defining value propositions and customer segments, analysing existing alternatives, prioritising unmet needs and building MVPs for innovative business industries (health, mobile app, SaaS, eCommerce, finance).
- Voted #1 mentor by startups.

Startup Mentor (Customer Development, Product Discovery)

The Kraft Heinz Company

Leading a 15 team of builders to launch innovative companies to disrupt the food industry.

- Designed Discovery and Delivery Sprint Process
- Trained team and Executed multiple sprints
- Results: 300 innovative ideas mapped, 30 validated, 3 MVPs launched

Head of Venture Builder

Building the next generation of ventures to disrupt the food and beverage industry.

Digital Ventures Lead

Fintech co. (backed by Forbes)

Led the creation, since inception, of consumer fintech mobile investing app (backed by major publishing giant Forbes).

- Defined the value proposition, business model and positioning.
- Built 1st prototype and validated assumptions by surveying 1000s of prospects and interviewing 100s.
- Crafted a product vision, strategy and product feature roadmap with job and user stories. 
- Led design sprints to build several iterative MVPs and user-tested with 100s of users.
- Built marketing material ie. landing pages and videos to help gather over 40k early access users
- Led agile development with scrum to deliver an Alpha 1.0, 2.0, and Beta 1.0 (fully working and compliant).
- Managed design, development and marketing projects involving +15 people

The app has garnered multiple Global Fintech Awards.

Interim VP Product

Proudsugar

Built a team of domain domain experts and contracted to high growth startups to help them grow:

- Openme (acq. by Rowl):
Led a team of seven, added analytics, launched surveys, optimized customer journey, built a testing roadmap, redesigned UX, and launched continuous A/B tests for eCommerce Openme.com.

- Plug.dj:
Led a team of nine, added analytics, surveyed and interviewed, redesigned UX, road mapped, and launched  continuous A/B tests for Plug.dj to increase activation, retention and revenue (a web/mobile music startup with 7 million users).

- Pluto.tv (acq. by Viacom):
Worked with a team of seven, implemented web analytics and created dashboard reports for Pluto.tv (an internet TV startup that sold to Viacom for $300 million). This led to identifying product conversion problems, UX redesigns and better KPIs.

- MROSupply: 
Led a team of six, implemented web analytics, interviewed/surveyed customers, identified opportunities, redesigned UX and launched continuous A/B tests for MROSupply (eCommerce with 1 million SKUs for mechanical parts) resulting in an +$5 million/year sales.

- Discuto
Led a team of five for Discuto.io (a B2B SaaS ideation and collaboration platform with +20,000 users), implemented analytics, performed user surveys/interviews, launched a UX redesign, resulting in higher onboarding of 35%, as well as 2x retention.

Co-founder | CEO | CPO

Javier Rincon

Freelance CRO and Web Analytics practitioner. Helped companies establish a web analytics infrastructure to gain insights on major KPIs. Then worked with CRO methodologies to increase main business and product metrics.

- Moviepilot (acq. by Webedia):
Worked with a team of 15, added analytics, did user research, built an opportunity roadmap, and launched continuous A/B tests for Moviepilot (a movie content platform that sold to Webedia), resulting in higher engagement metrics eg. +520,000 active onboarded users/year.

Product Analytics, Growth & CRO specialist

6Wunderkinder

Chief Marketing Officer for globally recognized Berlin startup, 6Wunderkinder, creators of Wunderlist with more than 2Million Downloads and new productivity app Wunderkit.

Building PMF Engines @ startups | Product Leader | Lean

Javier has +15 years experience building products that millions have used. 

• Startups: @Wunderlist (acq. by Microsoft), @Plug.dj, @Open.me (acq. by Rowl), @Pluto (acq. by Viacom), @Moviepilot (acq. Webedia).

• Venture Building: @LaSalle, @Forbes , @KraftHeinz

• Startup PMF mentoring & financing: @Keiretsu Forum, @Founder Institute and @Techstars.

• Industry: Business Intelligence @Oracle; System Analyst @Transmitton Siemens

He's also founder and builder; he ran a product agency in Berlin, co-founded a mobile social offers company in Madrid and launched an e-pharmacy out of University.

He has a MEng in Systems Engineering from Loughborough University in the UK. He's an avid learner, passionate about playing guitar and piano, storytelling in film and comics, war strategy, oil and gold drilling, railroads, and the expansion of empires.

If you want to grow in AI Evals, these are the top 12 experts worth following in 2025. 👇

These practitioners solve real evaluation problems in production and actually share what they learn.

1. Hamel Husain: 
Sets the standard for practical, production-ready eval frameworks.

2. Shreya Shankar
Sharpest thinking on LLM testing, data quality, and reliability.

3. Eugene Yan (Amazon) 
Turns complex eval concepts into actionable systems.

4. Aman Khan (Arize AI)
Building observability and eval tools used by Fortune 500s.

5. Manu Goyal (Braintrust)
Pioneering AutoEvals and production-grade eval workflows.

6. Vikram Chatterji (Galileo)
Building Evaluation Intelligence platform and Luna EFM models for enterprise AI.

7. Kritin Vongthongsri (Confident AI)
Building open-source eval infrastructure with DeepEval.

8. Peter Yang (Roblox)
Shows how product teams should actually approach AI evals.

9. Manouk Draisma (Langwatch)
Focused on end-to-end evaluation and observability for LLM apps.

10. Amy Chen (AI Evals & Analytics)
Teaching practical eval frameworks through hands-on courses and playbooks.

11. MAHESH YADAV (Google)
Ships production AI systems with rigorous eval processes.

12. Rogério Chaves (Langwatch) 
Building production-grade eval and observability infrastructure.

Who else is doing excellent work in evals? Drop names below.  👇

--
📌 Save this list and share with your network!

Fractional AI Head of Product | Evals | The bottleneck guy

We learned a big reason why AI isn’t reliable at scale from MongoDB's technical evangelist.

In my conversation with Apoorva Joshi (AI Developer Advocate at MongoDB), one insight stopped me in my tracks:

Many times your AI isn’t unreliable because it’s hallucinating.
It’s unreliable because it can’t keep all the information in memory, even when the model is advertised as if it can.

In this episode of Shipped AI, I’m joined by Adrian Tineo, Ph.D. (Fractional AI Consultant) and our guest, Apoorva Joshi, as we go deep into how modern AI systems actually behave in production, and why so many teams are still shipping AI on assumptions instead of reality.

We cover:
• The long-context myth: why “1M tokens” collapses to ~8k in practice
 • Hybrid retrieval: and why one method is no longer enough
 • Benchmarks vs evals: and how benchmarks mislead PMs
 • Agentic workflows: and where they really make sense
 • Where reliability breaks down: and how to design around it

In this clip Apoorva breaks down the long-context myth, and it explains a lot of the reliability issues teams shipping AI face today.
 
👇 Full episode:
 YouTube: https://lnkd.in/dr_TFZPW

#AI #LLM #ProductManagement

Talks about #productops, #leanstartup, #productdiscovery, #productmarketfit, and #productmanagement

Senior AI Developer Advocate @ MongoDB

MongoDB

Fractional AI Consultant

Farhad Azarbarzinniaz

Most teams don’t need more evals — they need the right ones.
Evals aren’t one-size-fits-all.

You can measure your agent factually, behaviorally, structurally… but what matters depends entirely on your use case.

In our latest "AI Rapid Roundtable", we explored how to make evals actionable.

Here’s what we covered with Bauke Brenninkmeijer (orq.ai / MLOps Community Amsterdam) and Adrian Tineo, Ph.D.:

◼︎ Why evaluating agents “in a billion different ways” can be confusing
◼︎ How grouping evals by use case helps teams find a meaningful baseline.
◼︎ Why starting with 10 well-chosen evals beats tracking 100 vanity metrics.
◼︎ How teams can layer in business-specific evals as they mature — instead of forcing generic frameworks.
◼︎ The real goal: turning evals into a feedback loop for better agents, not just better dashboards.

The truth is, evals aren’t about measurement — they’re about learning.
And the teams that learn fastest will be the ones that win.

👇 Watch the full episode → YouTube link in comments

#AI #Evals #LLMs

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Javier Rincon

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