AI strategy & adoption

Podcast

Why great AI products are all about the data

Lenny's Podcast Product Career Growth December 29, 2024

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AI strategy & adoption 10

Product-market fit 8

Long-term planning 6

• LLMs are only as good as the data you give them — model is the easy part.
• Enterprise SaaS incumbents are protected by business rules, not UX or code.
• Most PMs fail by staying inside the building instead of synthesising outside signals.

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AI strategy & adoption

YouTube

How 2024 proved the GPT wrapper myth wrong and broke in favour of startups

Y Combinator December 13, 2024

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AI strategy & adoption 9

Business models 7

Case studies 5

• Application-layer startups — not OpenAI — built 2024's breakout AI products.
• Open-source Llama ended monopoly pricing; product execution now beats model access.
• YC batches hit 10% weekly growth on average for the first time ever.

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AI strategy & adoption

YouTube

Five AI SaaS ideas disrupting the $14 billion business process automation market

TK Kader December 8, 2024

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AI strategy & adoption 9

Business models 7

Funnels 5

• AI agents can replace human data-entry workers cheaper and with fewer errors
• The most profitable SaaS targets are boring, mission-critical back-office roles
• Five concrete roles — from claims processing to compliance — ready to automate now

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AI strategy & adoption

YouTube

Data is the new oil: how to avoid wasted AI investment

Lean Startup Co. December 3, 2024

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AI strategy & adoption 9

Data & analytics 7

• Your proprietary operational data beats any general model.
• Most AI failures trace back to data problems, not model choice.
• Design the model as swappable; build the system around it.

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AI strategy & adoption

YouTube

Lean AI adoption: a human-first framework for corporate AI deployment

Lean Startup Co. November 29, 2024

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AI strategy & adoption 9

Processes & SOPs 7

Customer discovery 7

• AI projects fail at the human-organisation interface, not the technology layer
• Test your riskiest assumption first — skip the rest until forced to confront them
• Metered funding: only commit resources when evidence from real users justifies it

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AI strategy & adoption

YouTube

How leaders can become AI-savvy without becoming technologists

Coaching for Leaders November 25, 2024

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AI strategy & adoption 9

Management 7

• 80% of AI projects fail because leaders delegate instead of lead.
• AI augments human strengths — treating it as a replacement is a dead end.
• Human hype, not the technology, is the real driver of AI disappointment.

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AI strategy & adoption

YouTube

Vertical AI agents could be 10x bigger than SaaS

Y Combinator November 22, 2024

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AI strategy & adoption 9

Business models 7

Niche selection 6

• AI agents eat SaaS costs and headcount — the far larger line item.
• Selling to the team being replaced guarantees internal sabotage.
• Find a boring, repetitive admin job — that is your billion-dollar idea.

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AI strategy & adoption

Podcast

Bill Gates on AI, climate, global health, and education

Masters of Scale November 16, 2024

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AI strategy & adoption 10

Founder interviews 8

• AI is collapsing decade-long innovation timelines to years.
• Cheap cow interventions could cut 5% of global emissions.
• Most Africans never see a doctor — AI can change that.

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AI strategy & adoption

YouTube

Lean AI practices for building products people actually want

Lean Startup Co. November 15, 2024

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AI strategy & adoption 9

Customer discovery 7

• Starting with technology first is the most common and costly AI mistake.
• You can't pick the strongest use cases upfront — treat AI as a portfolio.
• Done well, AI disappears into the experience; users don't notice it at all.

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AI strategy & adoption

Podcast

How to become and thrive as an AI product manager

Lenny's Podcast Product Career Growth November 14, 2024

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AI strategy & adoption 9

Roadmapping 7

Identity & self-belief 5

• No ML PhD needed — prototyping with AI tools is now the entry ticket.
• Building 'ChatGPT on our data' is the most common AI PM mistake.
• Staying IC long-term demands energy, wandering, and amplifying customer signal.

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AI strategy & adoption

YouTube

How o1's reasoning capabilities unlock real-world startup applications

Y Combinator November 14, 2024

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AI strategy & adoption 9

AI tools & automation 7

Business models 6

• Same prompts that failed on GPT-4o worked immediately on o1.
• Proprietary eval sets — not the model — are the defensible startup moat.
• o1 moved GigaML's complex case accuracy from 0% to 85%.

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AI strategy & adoption

YouTube

How to productize AI in regulated enterprises without wasting time and money

Lean Startup Co. November 1, 2024

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AI strategy & adoption 10

Processes & SOPs 8

Hiring & recruitment 6

• Most AI fails at productization, not prototyping — governance is the gap.
• Discovery workshops with business units beat AI-first approaches every time.
• Regulated workloads need a dedicated governance role most companies aren't hiring for.

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AI strategy & adoption

YouTube

What 10 trillion parameter AI models mean for founders

Y Combinator November 1, 2024

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AI strategy & adoption 9

Business models 7

Product-market fit 5

• O1's accuracy jump lets founders skip prompt engineering entirely
• Claude took 5% to 25% developer share in one YC batch
• Voice AI hit a real inflection point — call centres are next

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AI strategy & adoption

Podcast

AI as a new digital species: Mustafa Suleyman on the agentic future

Masters of Scale October 31, 2024

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AI strategy & adoption 9

AI tools & automation 6

Business operating systems 5

• Why AI's emotional intelligence matters as much as its accuracy
• Agentic AI needs 99% reliability — we're currently at 50–60%
• Small distilled models running on wearables are an untapped startup opportunity

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AI strategy & adoption

YouTube

A four-step framework for selecting and scaling AI use cases

Lean Startup Co. October 18, 2024

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AI strategy & adoption 9

Automation & tools 6

• Set success metrics before testing, not after — or you can't call failure
• Cheap test-and-learn phases beat $10M projects that fail at launch
• Change leadership, not technology, is the hardest part of scaling AI

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