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Why Agents Don't Scale: It's an Engineering Problem, Not an AI Problem

blog.r-lopes.com

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Re: Why Agents Don't Scale: It's an Engineering Problem, Not an AI Problem

#3

Post by sermakarevich »

I think they do scale:

-- check this bug report from AMD where they say they run fleet of 50 agents 24x7 https://github.com/anthropics/claude-code/issues/42796

-- here I am running 3 coding agents 24x5 (not yet 7 so far) https://news.ycombinator.com/item?id=48520757

I was using multi-coding agents for poc projects first, now for production research and poc second and soon plan to get to production.

Re: Why Agents Don't Scale: It's an Engineering Problem, Not an AI Problem

#4

Post by dovelome »

sermakarevich wrote: post #3

I think they do scale: -- check this bug report from AMD where they say they run fleet of 50 agents 24x7 https://github.com/anthropics/claude-code/issues/42796 -- here I am running 3 coding agents 24x5 (not yet 7 so far) https://news.ycombinator.com/item?id=48520757 I was using multi-coding agents for poc projects first, now for production research and poc second and soon plan to get to production.

I like what you are doing! I suggest you create a proxy service that will route the traffic to the AI provider.

You can cache questions and answers heavily and use a B25 search with a vector embedded to retrieve the best results for you.

   RAG pipeline
   ├── BM25 + TF-IDF + RRF retrieval
   ├── cross-encoder reranking
   ├── knowledge-graph entity linking
   └── multi-angle intent detection
        │
        ▼
   LLM synthesis  (Claude / local models)

Re: Why Agents Don't Scale: It's an Engineering Problem, Not an AI Problem

#5

Post by dovelome »

dovelome wrote: post #4
sermakarevich wrote: post #3

I think they do scale: -- check this bug report from AMD where they say they run fleet of 50 agents 24x7 https://github.com/anthropics/claude-code/issues/42796 -- here I am running 3 coding agents 24x5 (not yet 7 so far) https://news.ycombinator.com/item?id=48520757 I was using multi-coding agents for poc projects first, now for production research and poc second and soon plan to get to production.

I like what you are doing! I suggest you create a proxy service that will route the traffic to the AI provider. You can cache questions and answers heavily and use a B25 search with a vector embedded to retrieve the best results for you. RAG pipeline ├── BM25 + TF-IDF + RRF retrieval ├── cross-encoder reranking ├── knowledge-graph entity linking └── multi-angle intent detection │ ▼ LLM synthesis (Claude / local model…

Check it out: https://blog.r-lopes.com/how-it-works
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