We couldn't send production data to an LLM provider, so we self-hosted one
The article explains why traditional chatbots struggle with production support because they lack access to live customer data, configuration, and code context. It describes how the bottleneck in support is often limited data access and knowledge silos rather than a lack of intelligence. The author proposes a self‑hosted LLM that can query code repositories and production data through specialized servers to provide accurate, context‑aware answers.
- ▪Support tickets often require simultaneous insight into a customer's row‑level data, configuration, and the relevant code path, which is rarely available to support staff.
- ▪Providing broad read access to production data creates compliance and security risks, so access is typically restricted to a small team, creating a bottleneck.
- ▪Standard LLM chatbots that only reference documentation cannot answer questions that depend on live state and logic, limiting their usefulness in production support.
- ▪The proposed solution involves a self‑hosted LLM paired with custom code and data servers that allow the model to retrieve and reason over code symbols, configuration values, and migration history.
- ▪Implementing such a system aims to reduce context‑switch overhead and accelerate issue resolution without compromising data privacy.
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,228 of its stories.
Story provenance
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Medium |
| Canonical URL | https://medium.com/@rahulgolwalkar/the-support-agent-that-actually-reads-your-code-and-your-production-data-b3d9ee03ec0a |
| Publication time | Mon, 10 Aug 2026 05:49:11 +0000 |
| Retrieval time | 2026-08-10T05:50:45.982Z |
| Last seen | 2026-08-10T05:50:45.982Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | TtMrgeeQZomt · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Artificial IntelligenceSoftware EngineeringCustomer SupportData PrivacyAi Agents In ActionThe Support Agent That Actually Reads Your Code and Your Production DataRahul Golwalkar9 min read·Just now--ListenShareWhy “just add a chatbot” fails at production support, and what actually works.The ticket nobody wantsIt is 4pm on a Thursday. A customer says an approval did not fire for one worker, on one date, in one org. Everything else is fine.Tier 1 checks the docs. Nothing. They escalate.Tier 2 pulls up the admin console, sees the record, and it looks correct. So this is probably a bug.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Medium.
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