Put the Agent Inside the Workflow
LLM Applications Put the Agent Inside the Workflow A hybrid LLM application pattern that combines a predefined workflow with adaptive agent behavior Shuai Guo Aug 1, 2026 8 min read Share Generated by GPT-Image 2 When building an LLM application, one of the first design decisions we have to make is: Workflow or agent? The workflow paradigm follows a sequence we define in advance. This makes the application very easy to understand, and gives us clear control over how information moves from one stage to the next.
- ▪LLM Applications Put the Agent Inside the Workflow A hybrid LLM application pattern that combines a predefined workflow with adaptive agent behavior Shuai Guo Aug 1, 2026 8 min read Share Generated by GPT-Image 2 When building an LLM applic
- ▪The workflow paradigm follows a sequence we define in advance.
- ▪This makes the application very easy to understand, and gives us clear control over how information moves from one stage to the next.
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| Original publisher | Towards Data Science |
| Canonical URL | https://towardsdatascience.com/put-the-agent-inside-the-workflow/ |
| Publication time | Sat, 01 Aug 2026 13:00:00 +0000 |
| Retrieval time | 2026-08-01T13:08:28.196Z |
| Last seen | 2026-08-01T13:08:28.196Z |
| 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 | mih5RvXjeQZY · 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 |
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| 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
LLM Applications Put the Agent Inside the Workflow A hybrid LLM application pattern that combines a predefined workflow with adaptive agent behavior Shuai Guo Aug 1, 2026 8 min read Share Generated by GPT-Image 2 When building an LLM application, one of the first design decisions we have to make is: Workflow or agent? The workflow paradigm follows a sequence we define in advance. This makes the application very easy to understand, and gives us clear control over how information moves from one stage to the next. It works well when we know which operation should happen at each stage. For more open-ended questions, however, the next useful action may depend on what the system discovers along the way.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Towards Data Science.
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