Understand This Before You Use AI To Build Software ft. Chris Guthrie
Notas del episodio
AI has made software easier than ever to build. That does not mean every internal tool should become the backbone of your business.
In this episode, Bryan sits down with Chris Guthrie to break down the growing temptation inside cannabis companies to vibe code internal tools, dashboards, CRMs, ERPs, and operational systems in the name of saving money.
The problem is not the first version. The problem is what happens two months later, when a field does not map, the workflow breaks, the person who built it is unavailable, and a production team is now relying on code nobody fully understands.
Chris explains the difference between a useful AI-built prototype and an enterprise-grade system that can survive real operators, messy data, security needs, compliance, multiple departments, M&A diligence, and future FDA-style requirements.
This conversation covers why descriptive data does not create predictive insight, why Google Sheets to vibe coding can become a path to failure, and why the real AI opportunity starts after the business has clean data, clean processes, and a system strong enough to trust.
This episode covers:
- The weekend build that fails
- Descriptive data will not predict
- Clean books before M&A
Chapters
00:00 The Rise of AI in Software Development
03:07 Challenges of Internal Software Development
06:09 Understanding What 'Works' in Software
09:10 The Risks of Vibe Coding
12:05 The Importance of Established Infrastructure
14:58 Cost Considerations in Software Development
17:56 Predictive Insights and Data Utilization
21:13 Defining Core Business Focus
23:17 The Challenges of AI Implementation
27:00 Understanding AI's Limitations
28:58 The Importance of Data Governance
31:11 Navigating Change Management in Cannabis
35:51 Preparing for Industry Evolution
40:09 The ROI of ERP Systems
Our Links:
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At Eighth Revolution (8th Rev), we provide services from capital to cannabinoid and everything in between in the cannabinoid industry.
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