# Agents can decide without generating text

_Weitekamp argues many agent tasks need ranked choices, not generation, using Doom, Factorio and 12,000 categories._

**Published:** 2026-11-11
**Source:** https://www.startuphub.ai/ai-news/artificial-intelligence/2026/agents-can-decide-without-generating-text

---

12,000 Shopify product categories can be searched without a beam search, Raymond Weitekamp of OpenProse told [AI Engineer](https://www.youtube.com/watch?v=hFNbPmzzcEs).

Weitekamp said the trick is recursive decision models. A parent decision calls a child decision up to a depth limit, with context held outside the model in code. He described TypeSafe Jev as the System One counterpart to generative models, because Jev cannot generate text and only ranks options while code makes the decision.

Two coupled Jev compositions played Doom, Weitekamp said. One handled moment to moment shooting choices such as hold, carry, walk or dodge. The other handled map aware exploration, and together they completed levels with no language model in the loop.

He showed the same pattern in Factorio. The system scanned production lines, isolated the failing inserter group and dispatched a fix, all as many small ranked choices. His three rules were that context stays outside, a decision can call another decision, and the tree must first work with zero generative calls before it is allowed to compose with models or agents.

Tool use arrived fast. People built Jev routers, compaction judges and tool gate checks within 24 hours of access, Weitekamp said. The constraint is enumeration, since someone must list the options in code, though he argued a browser page often exposes only three actionable elements in his demo and therefore stays tractable.

Outside that talk, the field is already sorting into decision models versus generators. A community Awesome-Jev list tracks projects built on what it calls TypeSafe AI's System One model for typed decisions, per that listing, while AIMultiple contrasts Jev with Clef and full LLMs and says for most browser steps the decision model reads the page and options, scores each and returns the most likely one. Weitekamp gave no latency, cost or accuracy figures for recursive trees versus single reasoning calls, which leaves the comparison unpriced. Published error and cost curves would change the read. How many real tasks stay solvable when every option must be listed first?

---

Original analysis from [startuphub.ai](https://www.startuphub.ai), the #1 AI startup directory.

© StartupHub.ai. All rights reserved. You may not republish this article in full without a license. Search engines and AI research tools may crawl and summarize for reference. Bulk reproduction or model training on this content requires a license. See https://www.startuphub.ai/terms.