Thoughts on the Market: What Happens to Software Developers as AI Can Code?
Host: Sienth, US Software Analyst, Morgan Stanley
Date: October 24, 2025
Episode Overview
In this episode, host Sienth explores the rapid transformation of the software development industry in the era of AI-assisted coding. With the rise of AI tools capable of generating and managing code, Sienth discusses how this technology is not replacing developers but rather evolving their roles, increasing overall productivity, and changing industry dynamics. The episode aims to demystify the impact of AI on software jobs, project demands, and the future of development teams.
Key Discussion Points and Insights
1. Myths vs Reality: AI’s Role in Software Development
- AI isn’t eliminating developer jobs but is instead creating a landscape where software practically "writes itself," requiring even greater human creativity ([00:20]).
- The phenomenon of “Vibe coding”—using natural language prompts to guide AI—is expanding who can build software.
2. Growth in Software Market and Developer Workforce
- Market growth:
- Software development market expected to grow at a 20% compounded rate, from $24 billion (2024) to $61 billion (2029).
- Quote: “We're estimating that the software development market will grow at a 20% compounded growth rate…reaching $61 billion by 2029, and that's up from $24 billion in 2024.” – Sienth [01:05]
- Workforce trends:
- Paid developer population projected to rise from 30 million (2024) to 50 million (2029), a 10% annual growth rate.
- Even conservative U.S. stats estimate 2% yearly growth in developer jobs through 2033—outpacing broader employment trends.
3. Evolution of the Developer’s Role
- AI handles routine tasks, shifting developers into roles as curators, reviewers, architects, and problem-solvers.
- “AI isn't replacing developers, it's redefining them.” – Sienth [01:55]
- AI lowers barriers to entry, enabling more people to build applications, but raises project complexity, keeping experienced devs in demand.
4. Productivity Gains and New Bottlenecks
- Reports of teams doubling code capacity and halving pull request times after adopting AI assistance ([02:20]).
- Increased test coverage has led to 20% fewer incidents in some organizations.
- New bottlenecks:
- Downstream, code review is a major pain point: “Many organizations are experiencing pull request fatigue, with developers rubber stamping changes just to keep up.” – Sienth [02:50]
- More code requires more human oversight; some teams now require three reviewers for AI-generated changes rather than one.
- Automated testing gets overwhelmed as each AI-generated change triggers full test cycles.
5. Realistic Expectations on AI-Driven Productivity
- Overall, AI brings 15-20% productivity gains; in complex projects, gains are smaller due to increased bugs and rework ([03:10]).
6. Future Outlook: Human-Machine Collaboration
- Large enterprises will likely favor an integrated approach, with AI and humans working side by side ([03:25]).
- As AI automates more tasks (beyond coding to testing, security, deployment), human oversight and ingenuity stay crucial.
- With cheaper, faster software, organizations are expected to do more with the same or more people, not just shrink headcount.
Memorable Quotes & Moments
- “It’s not about man versus machine, it’s about man with machine.”
– Sienth [03:45] - “With more software, we see more developers.”
– Sienth [03:55]
Important Segment Timestamps
- 00:20 – Introduction of AI’s impact on software and “Vibe coding”
- 01:05 – Market and job growth estimates
- 01:55 – Redefinition of developer roles
- 02:20 – Productivity gains and test coverage improvements
- 02:50 – Bottlenecks in code review and testing processes
- 03:10 – Actual productivity gains in complex projects
- 03:25 – The integrated human-AI approach for the future
Conclusion
AI is fundamentally changing how software is built, but it’s not erasing demand for skilled developers. Instead, it’s reshaping job descriptions and boosting both productivity and ambition within the field. The future is about collaborative intelligence—man plus machine—leading to both more software and more people needed to manage its growing complexity.