In 2026, the AI landscape looks very different from just a few years ago.
The Myth of Custom Models
Most startups assume:
- AI product = custom model
- Competitive edge = proprietary training
In reality, this is rarely true.
Where Real Differentiation Comes From
Winning AI products focus on:
- Data pipelines
- UX and workflow integration
- Reliability and monitoring
- Cost control and latency
Foundation Models Are Good Enough
Modern models are:
- Highly capable out of the box
- Constantly improving
- Cheaper to use than to replace
For most teams, customization adds cost, not value.
The Dev Shop Perspective
We help teams:
- Integrate AI safely and pragmatically
- Avoid unnecessary ML complexity
- Build systems that scale with usage, not hype
Final Thoughts
In 2026, smart AI products are engineered — not over-trained.