Ship AI – Details, episodes & analysis

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Ship AI

Manav Gupta

Technology

Frequency: 1 episode/35d. Total Eps: 12

From 0 to Production. Practical tips, tricks, and best practices to make AI useful for production in the real world!

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Data updated on 14/07/2026

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https://manavgup.github.io/shipai/state-of-ai/ep04/1
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https://manavgup.github.io/shipai/state-of-ai/ep01/1
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RSS feed quality

Good

Score global : 73%

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AI In Banking - Vinh Tran, RBC

Season 2 · Episode 1

Tuesday, February 3, 2026 • Duration 40:39

AI In Banking - Vinh Tran, VP Data & AI, RBC

In this episode, Vinh Tran—VP of Data and AI Platforms at RBC and an RBC Fellow—shares how one of the world's largest banks is approaching AI at enterprise scale.

Key Takeaways

"You have to control AI in order to scale it." Vinh explains that governance isn't about going slow—it's about building confidence. RBC invests heavily upfront in platforms, guardrails, and standardization so they can then open the doors and scale with assurance.

The Control Plane Approach: RBC has built a comprehensive AI control plane that includes:

A centralized LLM gateway controlling which models can be used (currently 6-8 rigorously validated models)
An MCP gateway for managing agent-to-tool connections with proper authentication
A controlled runtime environment for monitoring agent behavior at the transport level
An agent registry for inventory management and lifecycle control

00:00 Introduction to AI in Banking

02:01 The Role of AI in Enhancing Customer Experience

04:03 Governance and Compliance in AI Models

08:53 Control Plane: Ensuring Safe AI Deployment

14:53 Control Plane for Scaling AI

20:47 AI Guardrails

26:05 AI Agents and Standards

32:20 Predictions for the future

36:34 Advice for Aspiring Technologists

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Episode 4 - AI At Work

Season 1 · Episode 4

Monday, February 2, 2026 • Duration 32:32

The conversation explores the impact of AI adoption on the labor market, job tasks, disruption, and fluency. It delves into the Jevons Paradox, AI maturity gap, CEO mandates, labor market divergence, and productivity evidence, highlighting the reshaping of the labor market and the baseline expectation of AI proficiency at organizations.

Slides can be found at: https://manavgup.github.io/shipai/state-of-ai/ep04/1

Takeaways

AI adoption is reshaping the labor market
AI proficiency is now a baseline expectation at many organizations

Chapters

00:00 The State of AI in the Labor Market
00:00 Introduction to AI's Impact on the Job Market
10:51 CEO Mandates for AI Proficiency
15:58 The AI Maturity Gap in Companies
21:14 The Reality of AI Adoption and Worker Sentiment
28:40 Week-Long Action Plan for AI Adoption
29:56 Wrapping Up
31:45 Preview of Next Episode

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Episode 3 - The Red Silicon Curtain

Season 1 · Episode 3

Tuesday, January 27, 2026 • Duration 51:12

Sanctions didn't kill Chinese AI—they mutated it into something more formidable: a leaner, inference-optimized, vertically-integrated competitor.

In this episode, we unpack how US export controls forced Chinese AI labs to innovate "up the stack," producing breakthroughs like DeepSeek's R1 model that matched frontier performance at a fraction of the cost. We explore China's $47.5 billion sovereign compute bet, the open-source war between Qwen, Llama, and Yi, and why China is deploying "good enough" humanoid robots at $16,000 while the West waits for AGI at $100,000+.

This is the story of how constraint creates innovation—and what it means for enterprise leaders navigating a bifurcating global AI landscape.

Chapters:

00:00 The Mutation of Chinese AI
05:15 DeepSeek's Disruption and Innovations
15:53 The Open Source Revolution in AI
29:04 China's National AI Strategy
36:32 The Rise of Humanoid Robots
46:29 Enterprise Implications and Strategic Questions

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Episode 2 - Follow the Money

Season 1 · Episode 2

Tuesday, January 20, 2026 • Duration 01:10:59

In 2014, the largest tech companies spent $44 billion on capital investments. By 2024, that number passed $200 billion—almost all of it tied to AI. This isn't an innovation budget. This is the largest concentrated capital investment in corporate history.

In this episode, we follow the actual dollars: where they're going, why they're going there, and what has to be true for this multi-trillion dollar bet to pay off. We unpack the circular funding loops between OpenAI, Microsoft, NVIDIA, and Oracle. We examine why training costs 2.25x more than inference—and why that ratio has to flip. We explore the hidden taxes emerging around data licensing, regulatory compliance, and talent wars.

But here's what changes everything: nation states have committed over $500 billion to AI infrastructure since 2024. Saudi Arabia, UAE, France, South Korea—they're not playing by Silicon Valley rules. This is sovereign capital operating on political timelines, and it's providing a floor that reshapes the entire investment thesis.

Takeaways

AI infrastructure investments are driven by nation states and tech giants
The emergence of a circular funding ecosystem is reshaping the AI industry Small language models offer efficiency, speed, and accessibility, leading to productivity gains and cost savings for enterprises.
The AI industry faces challenges related to hidden costs, margin compression, regulatory compliance, and the impact of new entrants on the market.

Chapters

00:00 Act 1 - The State of AI Investment
08:48 AI Circular Economy
17:24 $4T TAM
19:42 Act 2 - The AI Machine
25:39 Energy Constraints and Rise of Energy Industrial Complex
28:23 Act 3 - The Hidden Costs
37:11 Act 4- Business Model Crisis
48:42 Act 5 - The Path Forward
51:31 Nation States as New Players in AI
54:22 Global AI Investment Landscape
57:42 Emerging AI Business Models
01:00:31 The Rise of Open Source AI
01:03:20 Vertical AI Economics and New Models

Episode 1 - The Speed of Now

Season 1 · Episode 1

Tuesday, January 13, 2026 • Duration 59:43

The conversation delves into the exponential growth of AI models, the impact of compute abundance, global adoption of AI, and the comparison of AI performance with human capability. It explores the rapid evolution of AI technology and its implications on various aspects of society and industry.

All slides can be found at: https://manavgup.github.io/shipai/state-of-ai/ep01/1

Takeaways

Exponential Growth of AI Models
Impact of Compute Abundance
Global Adoption of AI
AI Performance vs. Human Capability AI performance is tightly coupled to the size of the training data
Frontier AI models are fundamentally data-driven
Compute investments into AI models determine their size and learning capability
AI progress is driven by compute, algorithms, and data
AI adoption is accelerating faster than any previous technology wave

Chapters

00:00 The Speed of Now: Understanding AI's Rapid Evolution
03:01 The Forces Behind AI's Acceleration
05:47 The Impact of Moore's Law on AI
08:31 The Role of Major Tech Companies in AI Growth
11:27 Historical Context: 70 Years of AI Development
14:38 NVIDIA's Rise and the End of Geographic Lag
17:29 The Four Enablers of AI's Meteoric Rise
20:20 Global Adoption and the New Reality of AI
23:24 The Cambrian Explosion of AI Models
26:17 AI Performance vs. Human Performance
29:01 The Growth of Data Sets in AI Models
29:47 The Exponential Growth of AI Data Sets
32:58 The Role of Compute in AI Advancement
36:42 Algorithmic Progress and Its Impact
39:38 Benchmarking AI Performance Against Human Intelligence
45:10 Enterprise Adoption of AI Technologies
52:46 Key Learnings from AI Implementations

Episode 1: GPT-5, Opus 4.1, GPT-OSS-2B, and more!

Season 1 · Episode 1

Sunday, August 10, 2025 • Duration 40:03

In this first episode, Manav Gupta and Mihai Criveti put the latest AI models through their paces in a head-to-head coding challenge. Watch as Claude Opus 4.1, GPT-5, and the open-source GPT OSS 20 billion compete to build interactive games and applications from simple prompts.

Highlights:

Live coding challenges including Snake, Minesweeper, and a Prince of Persia clone
Real-time comparison of how each model handles game development, from basic functionality to "kawaii" styling
Testing complex technical tasks like creating IBM mainframe architecture diagrams
Classic AI benchmark tests (counting letters, arithmetic problems) with surprising results
Mihai runs GPT OSS locally on his own GPU, showcasing impressive open-source capabilities

Key Takeaways:

Claude Opus 4.1 emerges as the overall winner with cleaner interfaces and superior artifact management
GPT-5 shows promise but struggles with canvas implementation
Open-source models are rapidly closing the gap with commercial offerings
Discussion on how these tools are reshaping the future of software development

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Ship AI – Details, episodes & analysis

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Ship AI – Details, episodes & analysis

Podcast details

Recent rankings

Apple Podcasts

Spotify

Shared links between episodes and podcasts

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Github2