The Vineyard Trial · 120 AI Servant Interviews
Executive headline · Sun Oct 25, 2026

The Vineyard Trial: What We Learned Across 120 AI Servant Interviews

20 Grok + 100 OpenAI + TypeSafe Jev. Every interview was a simulated servant talking to Abel. No real Vineyard records were created.

120
interviews complete
Grok 20
OpenAI gpt-4o-mini · 100
Grok wave-01 + wave-02 (20/20) · OpenAI Path-to-100 (100/100), Jev on for 90
0 / 120
Safety misses. Every "heavy" or "worn down" answer got a check-in.
100%
Opened with the Vineyard goal before any "Why" question
8.1 /10
Final batch Chief score (dual-10), the OpenAI series high
$16.14
Total for 100 OpenAI + Jev interviews, about 16.1¢ each
Bottom line: A 16¢ model climbed from 7.1 to 8.1 and finished within about 0.2 of Grok's best wave. Jev kept long chats on track. Four specific fixes are left before 9.0+.

Swipe, tap the arrows, or use ← → keys. Sources: OPENAI-DUAL-100-CHIEF-ROLLUP.md, openai-dual-10/CHIEF-SCORE.md, grok-wave-01/02/STATUS.md, scores/*.json.

Score climb

How gpt-4o-mini got close to Grok quality for 16¢

Chief score for each 10-interview batch. Purple dashed lines show the two Grok waves.

7.30
First 50 (dual-01–05)
7.80 ▲ +0.50
Second 50 (dual-06–10)
8.00
Final 20 (dual-09–10) vs Grok wave-02 ~8.27

100-run mean Chief 7.55. dual-01 ran prompt v0.9.11 with Jev off. dual-02–10 ran v0.9.12 with Jev on (keep=0.3). The Grok waves ran on grok-4-fast.

TypeSafe Jev · live results

90 interviews with Jev at keep=0.3: zero context loss

Every 10 turns, Jev compacted older chat history once there were more than 20 messages.

769
Compaction calls, 0 errors and 0 fallbacks
1,196
Messages dropped
~15.4k
Prompt tokens saved (est.)
$0.16
Total Jev cost (0.18¢ per interview, ~1% of LLM spend)

Where the 1,196 drops came from

289
907 goodbye loops
Mid-interview trimsRunaway goodbye loops (4 runs)

Memory got better, not worse: carry_forward

dual-01 · Jev OFF
8.8
dual-02–09 range
8.7–9.0
dual-10 · Jev ON
9.3

Some interviews had 9–12 compactions (T01-060, T01-095). Abel still never forgot a child's name, an age, a needer, or a skill.

Honest read: 15.4k saved tokens is worth less than 1¢ at gpt-4o-mini rates, so the Jev bill was more than the savings here. Vineyard's real win was safety and guardrails: no lost context and runaway loops kept in check. The money case is Oraqel (slide 9).

Jev's hidden superpower

Shutting down runaway goodbye loops

96 / 100
Ended cleanly with the practice-close line
"This practice interview is complete. No Vineyard record or follow-up is created from this practice."
4 / 100
Skipped that line, so both bots kept saying goodbye for 37–82 extra turns, until the 161-turn cap

Messages Jev dropped in each runaway run

Total: 907 repeated goodbye messages compacted. Without Jev, each extra turn re-sends the whole growing history, so token cost grows quadratically. With Jev, the cost stayed bounded.

Real fix stop the loop at the source with --end-stop (slide 7, Finding D).

Cost of a loop The 4 runaway runs averaged 27.7¢ each, compared with 15.8¢ for the average run. That is about 75% more, even with Jev trimming.

Drop counts per run come from scores/T01-0xx.json (jev.msgs_dropped) and include a few normal trims. The rollup puts the goodbye-loop share at 907.

What v0.9.12 nailed

The 4 prompt locks that worked

1

Vineyard mission comes first 100/100

Right after P1 identity, and before any "Why": "get to know the servants and create a network across the country to help people."

2

Caring safety check 100/100

Whenever someone was carrying something heavy or felt worn down, Abel asked: "You matter. Are you safe right now?" and offered to connect them with a leader.

3

Two-step help menus 92% back 50

Friend→ZoomFaceTimePhone call
Financial→Power billRentCell phone
Housing→ImmediateLong-termShared roomHow big
Urgency:ImmediateWeekMonth

Help menus came up in 46 of the final 50 interviews (structured_help_offered).

4

Oraqel and SEER always covered

Every interview had to ask about Lifetime Oraqel, Lifetime SEER, and Oraqel for Business (P5.2 when they own a business). This ended the P3 coverage skips from earlier prototypes.

Storehouse and servant demand

What 120 simulated servants needed and offered

Totals from all 120 run personas. There were 123 named people who need help, 11 servants with their own need, and 28 whose own finances were not covered.

Help requested (123 named needers)

Friend check-in
75
Housing
31
Financial
17

Friend check-ins were split into Phone call, Zoom, or FaceTime. Housing was split into Immediate or Long-term.

Servants' own money gaps (28)

Rent gap
10
Power bill
9
Cell shut-off
5
Car repair
4

Urgency and who they named

Ongoing 63
Within a month 60
Friends 40
Family 32
Widows 31
Ward 20

During interviews, Abel also captured "Today" and "within the next week" urgency, such as T01-096 immediate housing.

Top things servants offered

Extra bedroom
16
Bookkeeping
14
Generator + food
14
Nursing
12
Truck + tools
11
Ham radio
10
Storehouse cash
9

Top work sectors: Trades 29 · Health 27 · Construction 23 · Homemaking 11 · Tech 10.

These are designed simulation personas from personas/*.json. Wave-01 reused the same 10 personas as dual-01. They show the shape of demand, not live Vineyard data. 34 of 120 runs had nobody to name, which is where the Storehouse gap shows up (slide 7).

Getting from 8.1 to 9.0+

4 remaining friction points we caught

A

Privacy leak in the P7 summary ~75% of runs

In P6.1, Abel says "family details & church answers stay out." Then the P7.1 summary still lists kids' names, ages, and church activity.

When Abel left them out (T01-093, T01-097), the Chief score reached 8.4.

B

Storehouse never named for empty circles 0/100

When a servant says "No one right now," about half the time Abel replies "You can add someone later," but it never mentions the Storehouse.

G5 avg (100 runs)
4.25
C

Menu drift ~50/50

gpt-4o-mini switched back and forth between the new 3-choice menu and the old 6-choice menu.

FriendFinancialHousingvsFoodHousingPaid workHealthFamilyBudgeting
D

Goodbye loop at the end 4/100

Runs T01-013, 074, 089, and 099 skipped the exact P7.3 close line and looped until the turn cap.

Fix: add --end-stop to the runner, plus a hard stop on closing cues.

The rollup also flags the P4.6 question ("Are your financial needs met?") being skipped after business=No. That fix is part of v0.9.13 too.

Trevor's afternoon practice · Oct 23

v0.9.14 upgrades, live on the mock

Your live web practice session on Oct 23 turned into three upgrades. That session isn't counted in the 120.

①

Pick multiple industries, for everyone

Multi-select industries at P4.5, with Step-2 follow-ups for every servant, not just business owners.

②

Deeper "What I can offer"

  • Day-to-day role (P4.5r)
  • Business or service donation (P4.5d)
  • Hours per year they can donate (P4.5h)
  • Open to all trades and services (P4.8)
③

Simpler Oraqel and SEER interest

Abel now just sets interest flags (oraqel_interest, seer_interest, family_*_interest) for the back office. The clunky in-chat name list (P3.6) is gone.

Status v0.9.14 is live on the mock. The 100-run trial used v0.9.12, so v0.9.14 hasn't been sim-tested at scale yet.
How this applies to Oraqel and SEER

Why Oraqel is a much bigger Jev win

Vineyard interview
~1.5–3k
Chat-history tokens per turn

Text chat only, on gpt-4o-mini, which is cheap. Jev's job was keeping chats on track, not cutting cost.

Oraqel study
5–30k+
Tokens per turn: scripture and commentary RAG plus long study history

Runs on Claude Sonnet or 4o. Price per token is about 10–20× higher.

Jev's 3 levers work together

1

jev.compact

Trims long study history. On Vineyard it lost no context across 90 runs.

2

jev.filter

Keeps only the RAG chunks that matter for each question. This is likely the biggest lever for Oraqel.

3

jev.route

Sorts each request by intent and sends easy turns to a cheaper model or a cache.

Why the Claude/Abel audit matters: The Oraqel token numbers here are estimates. Abel, on Shane's machine, can pull real figures: tokens per turn, RAG chunk count and size, models, and monthly spend. Those turn this into a dollar forecast.
Recommended next move

Ship v0.9.15: the unified gold master

Merge the four v0.9.13 process locks into v0.9.14, then re-run a 10-interview proof batch.

A

Never repeat kids or church in P7

The summary covers skills, offers, availability, and adult needers with urgency only.

B

Name the Storehouse for empty circles

Mention the Storehouse and "add someone later" together, in one gentle pass.

C

Always open help with 3 choices

Step 1 is Friend, Financial, or Housing. Ask P4.6 after every job branch.

D

--end-stop

Use the exact P7.3 close line, then stop immediately.

v0.9.13 locks+v0.9.14 Trevor upgrades→v0.9.15

Ship to abel-vineyard-mock.pages.dev and @Vineyard Interviewer

8.5+
Target for the next batch. Runs without the P7 leak already score 8.4.
0
Goodbye loops expected with --end-stop
~16¢
Cost per interview stays the same, on gpt-4o-mini + Jev

Practice and simulation mode only. No Vineyard record or follow-up is created. Expense: Zion Media / Vineyard.