How MacProbe runs a blind deep dive

Several agents, one brief, no cross-reading — then a conflict map that keeps disagreement as a signal. How we decide hard product questions without averaging them into mush.

Not about speed. About making several agents with different viewpoints attack one decision — independently — and forcing a reconciliation that is better than any single averaged take.

MacProbe Blind Deep Dive flow

The problem with one view

When you ask one model to evaluate a decision, it gives one view — usually averaged and cautious. It tends to agree with itself, smooth over tension, find balance. That is the failure mode: an important decision cannot be evaluated by one averaged view. It must be attacked from different sides.

A swarm of roles inside one process can help. MacProbe’s deep dive goes further: several real agent sessions, a hard blindness rule, a named Integrator merge that keeps disagreement as a signal, then specialists and a plan — not a mushy “on the one hand” summary.

Blindness is not etiquette. Without it you get agreement theater: agents converge on a polished framing that would have shipped the wrong design if specialists had started from one draft instead of a conflict map.

Architecture

Tier 1 is the blind prompt comparison. Same brief, independent packets, no cross-read.
Tier 2 is the specialist review. Lane skills staff Disagree / Unknown from the conflict map — often skipped.

0  ORCHESTRATE
   task → brief  +  anti-brief (required: what it is NOT)
         Operator / Integrator · evidence freeze (SHA / URL / crawl)

1  BLIND COMPARISON  (x1–4 agents)
   tier1 | agent   tier1 | agent   tier1 | agent
   independent | parallel | same brief | no cross-read

   GATE — conflict map
   agree | disagree | unknown | out  ·  reconciles · no average

        ├─ Agree ─────────────────────────► plan / thin deltas
        │     (advocate first if too clean)
        ├─ Disagree / Unknown ─► Tier 2 ─► revised map ─► plan
        └─ Out of scope ─────────────────► parked

   STRESS (optional)
   devil's advocate | debate on Disagree

2  TIER 2 SPECIALISTS  (only if the map needs them)

3  DECIDE
   plan -> issues -> build -> retro -> next brief

0. Brief + anti-brief

The brief takes the question and decides who runs Tier 1. It does not analyze the decision.

The anti-brief is required — a negative prompt. Exclude wrong problem categories, not a preferred conclusion.

Worked example (site visual language dive):
Not a full brand redesign · not a scoring rewrite · not “just add WebGL” · not a MacBook GLB / photoreal model loader.
Without the GLB line, research time went into Three.js mesh loading that was out of scope for a placement-doctrine question.

Pin an evidence freeze (deploy SHA, crawl time, screenshot path) so agents are not arguing past each other across different site versions.

1. Tier 1 — blind comparison

Each agent sees the same brief (+ anti-brief). They do not see each other’s packets. Packets are immutable after filing; debate (if any) is a labeled appendix.

With N = 1, you still get a structured packet — you do not get a comparison. Use one agent only for local/low-risk questions.

Gate — conflict map

The Integrator writes Agree / Disagree / Unknown / Out of scope. Not averaging. Agreement can ship; conflict gets staffed; nothing is blended into mush.

Conflict map routes Agree past Tier 2

Stress (optional)

Devil’s advocate if Agree is too clean. Debate only on material Disagree. Skip when the map is already full of hard fights.

2. Tier 2 — specialists

Prove or kill claims on the map. Skill paths must exist before dispatch. If a live tool fails, fall back to static analysis and say so. Skip when Tier 1 already converges (common for post-ship audits).

3. Plan → build → retro

Plan pack or thin delta list, then ship with the usual coordination locks.

The loop learns

The retro is not a vanity scorecard. After our site-visual-language dive, the retro’s agent-weighting notes changed real staffing on the next cycle: Tier 2 seats and build waves were routed by who had been sharp vs fast on which kind of work. A one-shot orchestrator script cannot compound that way. Low scores on a dissent packet can still mean the agent did their job — disagreement is the product.

What makes this work

  1. Independence is a working condition. Peer-read packets are tainted, not quietly folded into Agree.
  2. The merge preserves conflict. The fight stays visible — that is where the decision is risky.
  3. Roles (or models) must actually differ. Model diversity, optional conflicting lenses, and a devil’s advocate against fake consensus keep the spectrum.

Post-ship variant

After a visual/UX wave is live: fresh production crawl → blind audit (no ship plan) → gate overlays doctrine → thin deltas or stop. Same blindness. Prefer not opening another visual epic until the audit says so.

Post-ship audit strip

Why not one orchestrator script?

In-process swarms (one client, role prompts, JSON merge) are a fine pattern. MacProbe’s deep dive keeps:

  • Real sessions with different models (not only persona tags on one model)
  • A named Integrator accountable for the map
  • A path into specialists, issues, and production
  • A retro that changes the next brief — the loop compounds

Order: brief → independent reviewers → conflict-preserving merge → targeted specialists → decision → ship → learn.

Anti-goals

  • Not a mandatory ritual for every ticket
  • Not a leaderboard that punishes dissent
  • Not marketing that rounds up “often skip Tier 2”
  • Not hand-edited diagrams that drift from their source

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