# Navigating Build vs. Buy Decisions in Emerging AI Technologies - ML 180

Page: https://stenobird.com/podcast/adventures-in-machine-learning/navigating-build-vs-buy-decisions-in-emerging-ai-technologies-ml-180
Text version: https://stenobird.com/podcast/adventures-in-machine-learning/navigating-build-vs-buy-decisions-in-emerging-ai-technologies-ml-180.md
Podcast: [Adventures in Machine Learning](https://stenobird.com/podcast/adventures-in-machine-learning)
Published: 2024-12-26T11:00:00+00:00
Episode link: https://www.spreaker.com/episode/navigating-build-vs-buy-decisions-in-emerging-ai-technologies-ml-180--63480920
Audio file: https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/63480920/ml_180.mp3
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Duration seconds: 1918

## Resource

Avoid the trap of expensive, unmaintainable AI projects by using time-boxed research spikes to evaluate technical feasibility. Learn how to balance rapid prototyping with the long-term stability required for production-grade agentic workflows.

## Highlights
- Main idea: Use 'Customer User Journeys' (CUJs) and hackathons to define project scope and technical limitations before committing budget
- Practical takeaway: Implement research spikes to understand the cost, scalability, and maintenance burden of new LLM frameworks
- Failure mode: Avoid over-engineering complex agentic systems using unproven libraries that lack mature tooling or long-term maintenance guarantees
- Strategic advice: Focus GenAI investments on Retrieval-Augmented Generation (RAG) for immediate, high-ROI business value
- Management lesson: Technical leaders must time-box exploration to prevent 'research projects' from becoming endless, expensive drains on resources

## Topics

Generative AI, Agentic Workflows, Retrieval-Augmented Generation, Software Architecture, Product Management, Technical Leadership, RAG, LLM Implementation

## Chapters
- 3:25 — The CEO's Dilemma: How to approach integrating GenAI into an existing business infrastructure without creating a maintenance nightmare.
- 5:55 — Defining Scope via CUJs: Using hackathons and Customer User Journeys to identify what is technically possible and estimate true project effort.
- 10:50 — The Danger of Endless Research: How unmanaged prototyping leads to missed deadlines and executive loss of confidence.
- 18:35 — Leading Inexperienced Teams: Strategies for technical leaders to guide teams through unfamiliar AI landscapes and 'unknown unknowns'.
- 21:05 — Iterative Deployment Strategies: Moving from staging to production using controlled rollouts and incremental user feedback.
- 26:10 — The Build vs. Buy Complexity: Evaluating the high maintenance burden of building custom agentic logic versus waiting for mature managed solutions.
- 30:50 — High-ROI AI Opportunities: Why RAG is the current gold standard for production stability and why you should avoid chasing hype-driven complexity.

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## Transcript

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