Developer Peter Steinberger has publicly endorsed a way of running AI inference that bypasses intermediaries, calling it "smart" and saying he was surprised it was not already the default.
AI inference · Developer endorsement
Peter Steinberger backs skipping intermediaries to make AI inference more predictable
He called the approach "smart" and said he was surprised it was not already the default. The product behind it has not been identified, and no benchmarks or technical details are available.
The path a request takes
Steinberger's concern was the middle layer between the app and the model.
Application
Sends the request
→
Intermediary layer
Gateway, router, or reseller that can change the model, alter settings, or add latency
→
Model
Produces the output
Application
Sends the request
→
Direct access
No middle layer in the path
→
Model
Produces the output
Why it matters
Inference quality, meaning how consistent a model's outputs are at runtime, is a practical concern for product teams.
Removing intermediaries may make results more predictable, a view some practitioners hold.
He had long advised avoiding these layers for this reason.
What remains unproven
The predictability claim has not been tested in the available material.
No published benchmarks, pricing, or technical documentation exist for the approach.
It is unclear whether it works across different models or what trade-offs it carries.
Bottom line
Read this as an informed developer's endorsement of a long-held preference, not a confirmed market shift.
Unknown
Who built the approach and what it is
Missing
Benchmarks, pricing, and documentation
Next step
Evidence on quality and whether direct access becomes standard
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