Give Your AI Agent a Domain-Specific Language
AI-powered financial modeling finally works now. One of the key ingredients that made that possible for us is we gave the LLMs we use a domain-specific language (DSL) in which to operate. If you're using AI for something complicated that needs to be done repeatedly and are seeing limited or inconsistent success, a DSL might help you unlock the capability you seek.
- ▪AI-powered financial modeling finally works now.
- ▪One of the key ingredients that made that possible for us is we gave the LLMs we use a domain-specific language (DSL) in which to operate.
- ▪If you're using AI for something complicated that needs to be done repeatedly and are seeing limited or inconsistent success, a DSL might help you unlock the capability you seek.
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Record
| Original publisher | Modeloptic |
| Canonical URL | https://www.modeloptic.com/blog/give-your-ai-agent-a-dsl |
| Publication time | Mon, 05 Oct 2026 22:05:15 +0000 |
| Retrieval time | 2026-10-05T22:11:55.689Z |
| Last seen | 2026-10-05T22:11:55.689Z |
| 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 | 2PzFDWSsBQF7 · 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
AI-powered financial modeling finally works now. One of the key ingredients that made that possible for us is we gave the LLMs we use a domain-specific language (DSL) in which to operate. If you're using AI for something complicated that needs to be done repeatedly and are seeing limited or inconsistent success, a DSL might help you unlock the capability you seek. Why a DSL? LLMs currently have two major constraints: They have amnesia: Unless you train your own model on your particular domain, it must re-ingest any information you want to give it related to your domain every time you talk to it. They are context-constrained: They can only manage so much information at one time. The more information they have in working memory, the worse they perform.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Modeloptic.
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