

Discussion summary
DeepSeek's verification loop increased its Web-Bench score from 20 to 80, matching Opus at a seventh of the cost. The method involves iterative skill-based testing to improve LLM performance.
What the discussion says
- Some see it as marketing for a SaaS product.
- Others note it mimics techniques used by Anthropic and OpenAI.
- The approach uses multiple skills like debugging and visual testing.
“Verification loop took DeepSeek from ~20 to ~80 on Web-Bench.”
“It uses skills in a loop to help LLMs solve tasks better.”
Comments
Hacker News
by _aavaa_
by sozal
by rightbyte
The skills can be found here:
https://github.com/ironbee-ai/ironbee-devtools-skills/tree/m...
Question that was left unanswered:
How much longer does a 4x DeepSkeep loop took compared to Opus?
by bel8
Join the discussion
Write your take first — we'll ask for email only when you're ready to publish.
- Hacker News
- Seems interesting, but buried under a mountain of written slop.by _aavaa_
- Fair on the length. The verification loop took DeepSeek from ~20 to ~80 on Web-Bench, matching Opus at ~7x less cost. Curious if the method holds up for you.by sozal
- It is marketing for some SaaS thing. However, I think something like this, "verification loops with some sort of tricks", is what Anthropic and "OpenAI" do behind the scene with their interfaces.by rightbyte
- From what I understood, the gist of it is that uses a bunch of skills in a loop to help LLMs solve the tasks better via browser-testing, debugging, visual-testing, etc..
The skills can be found here:
https://github.com/ironbee-ai/ironbee-devtools-skills/tree/m...
Question that was left unanswered:
How much longer does a 4x DeepSkeep loop took compared to Opus?
by bel8
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