Session Planning: Phases 2F–2H (200K Context Window Adaptation)#

Generated 2026-03-22 by Claude Opus 4.6 at /effort max during a planning session with LLoL.

This llog documents the conversation in which the original prompts prompt_2f_ready.rst and prompt_2g_ready.rst (designed for a 1M-token context window) were redesigned for a 200K-token window and enhanced with a multi-angle stress-test methodology.

This file is for debugging/audit purposes only. It is NOT listed as a required read in any of the Phase 2F–2H session prompts.

Gap Found: Round 3 Not Integrated#

During analysis of the project state, a gap was discovered:

  • Round 3 (C3.1–C3.7) has NOT been integrated into quest.rst. All 7 Round 3 objections (all targeting ResearchCity feasibility) remain unprocessed. The inventory table (quest-cons-table.rst) has them catalogued with severity, targets, and dispositions, but zero Con/Pro entries exist in quest.rst.

  • Phase 2e status note is stale. The note in quest.rst (line 42) says “Phase 2e in progress” but Phase 2e is complete — all C2.7–C2.12 entries are present, and the Round 2 Summary is written through line 2619.

  • Root cause: The inventory table recommended merging 2f into 2g (since no Round 3 objections are Se1), and the prompts prompt_2f_ready.rst / prompt_2g_ready.rst were written but never executed. Neither prompt works in a 200K window because both attempt to load all files simultaneously (~270–360K tokens of source material).

Token Budget Analysis#

File sizes of all referenced material:

File Group

Lines

Est. Tokens

A: Methodology/planning

1,957

~30–40K

B: All 6 critique/reply files

7,403

~110–150K

C: Phase 2a–2e session llogs

2,804

~42–56K

D: Canonical content files

4,548

~68–91K

Debug file

1,370

~20–27K

TOTAL

~18,100

~270–360K

At 200K tokens, usable file-read budget is ~120–150K (after system prompt, the prompt itself, and output space). The material must be split across sessions.

Strategy Comparison#

Two strategies were evaluated:

Strategy 1: “Minimum Splits” (4 sessions total)

Each analytical session loads primary source material + uses the Round Summaries already in quest.rst for cross-round awareness. Trade-off: narrative paragraphs work from summaries rather than original critique/reply text. This matters because the prompts explicitly say “draw on specific details — not just the summaries in quest.rst.”

Strategy 2: “Maximum Fidelity” (more sessions, always uses originals)

Each analytical/reasoning step has original source material in context. The narrative synthesis gets its own dedicated session loading original reply files. Trade-off: more sessions to execute.

Decision: Strategy 2 chosen for maximum mathematical and scientific accuracy. LLoL stated: “I’d happily run 10 sessions if that improves the quality.”

Design Enhancement: Multi-Angle Stress-Test#

LLoL requested that the synthesis phase (originally a single session 2g producing flat summary statistics) be redesigned as a multi-angle stress-test:

“do all 3 and then tell me what remains as the strongest critique after considering all my best replies”

This led to the 3-angle stress-test design:

  1. 2G-1 (Mathematical Rigor): Re-examine all Se1 resolutions. Grade each as Proven / Semi-formal / Plausible / Asserted. Trace the core logical chain (th8_T8 -> ax24_A24 -> ax25_A25 -> ResearchCity). Identify the weakest mathematical link.

  2. 2G-2 (Institutional Feasibility): Re-examine all Se2/Se3/Se4/Se6 resolutions. Grade ResearchCity solution credibility. Evaluate the 7-stage scaling plan. Identify the most heroic assumptions.

  3. 2G-3 (Disposition Audit): Independently reassess all 33 dispositions. Check for motivated reasoning (the replies and dispositions were produced by the same Claude model). Downgrade inflated resolutions; upgrade over-conceded items.

Session 2G-4 then triangulates the three analyses, producing a convergence matrix and definitive “strongest remaining critique” ranking.

Renumbering Convention#

To distinguish from the original (never-executed) prompts prompt_2f_ready.rst and prompt_2g_ready.rst, the new sessions use uppercase phase letters:

Session

Purpose

Approx. Tokens (reads)

2F-1

Round 3 integration (C3.1–C3.7)

~115–150K

2F-2

Documentation for Phase 2F

~30–50K

2G-1

Stress-test: Mathematical Rigor

~100–136K

2G-2

Stress-test: Institutional Feasibility

~117–156K

2G-3

Stress-test: Disposition Audit

~111–148K

2G-4

Convergence: triangulate + Final Summary

~80–120K

2H-1

OOv2 Freeze + Build

~80–120K

2H-2

Final Documentation

~80–120K

Files Produced#

All prompt files written to: source/matheology/vv/jub/oov2/prompts/

File

Purpose

prompt_2F-1.rst

Round 3 integration (core analytical work)

prompt_2F-2.rst

Phase 2F documentation (llog, debug, plan additions)

prompt_2G-1.rst

Stress-test: Mathematical Rigor angle

prompt_2G-2.rst

Stress-test: Institutional Feasibility angle

prompt_2G-3.rst

Stress-test: Disposition Audit angle

prompt_2G-4.rst

Convergence: synthesize 3 stress-tests, Final Summary

prompt_2H-1.rst

OOv2 freeze, open-items consolidation, build

prompt_2H-2.rst

Final documentation (llog, debug, plan additions)

Verbatim Prompts#

The following captures the key exchanges from this planning session. The full conversation is preserved in the Claude Code session history.

— Verbatim AI prompt by LLoL start —

These two prompt files were written by Claude-Opus Max for a 1M context window. I want you to revise them, so that they work for a 200k token window without loss of quality (i.e. break the work down in a sequence of smaller steps). Tell me what the differences are if there are different strategies for doing that. Help me to choose the most reliable strategy for doing the mathematically and scientifically most accurate work in reasoning through the problem. Here are the files: Users/llol/LLoL-Repos/SethGitHubSetup/balospe-com/source/matheology/vv/jub/oov2/llog/prompt_2f_ready.rst /Users/llol/LLoL-Repos/SethGitHubSetup/balospe-com/source/matheology/vv/jub/oov2/llog/prompt_2g_ready.rst I need new prompts for the smaller context window. What do you recommend?

— AI prompt by LLoL end —

— Verbatim AI reply by Claude Opus 4.6, working at /effort max, start —

[Claude performed token budget analysis of all referenced files, identified ~270–360K tokens of total material, and proposed two strategies. Strategy 1 (Minimum Splits): 4 sessions, uses quest.rst summaries for cross-round depth. Strategy 2 (Maximum Fidelity): 5–6 sessions, always uses original source material. Recommended Strategy 2 for mathematical accuracy. Provided concrete session breakdown with token estimates for each session. See the full analysis in the conversation above.]

— AI reply end —

— Verbatim AI prompt by LLoL start —

Let’s choose strategy 2 for maximum fidelity. I’d happily run 10 sessions if that improves the quality. Before you write out sessions, some questions. I’m not sure if you actually have the full picture. Maybe I made some mistake in directing earlier prompt-writing that led you to overlook the processing of some critiques, especially about ResearchCity in Round 3 (or late Round 2). Can you check if that is the case? — Then about what about session 2g from diverse angles: do all 3 and then tell me what remains as the strongest critique after considering all my best replies? If that takes 3-4 sessions that’s OK for me. Then conclude with session 2g-3. Please map out your best session plan in light of all this — and lets redo the nunmbering starting from Phase 2F 2G 2H… (to distinguish it form the earlier 2f 2g….). So, was there a gap in the overal planning?

— AI prompt by LLoL end —

— Verbatim AI reply by Claude Opus 4.6, working at /effort max, start —

[Claude investigated the project state: read quest-cons-table.rst, searched quest.rst for all Con/Pro entries, read the tail of quest.rst, and read the opening sections of the Round 3 critique and reply files. Found the gap: all 7 Round 3 objections (C3.1–C3.7) are unprocessed. Status note is stale. Proposed the 8-session plan with 3-angle stress-testing (2G-1 math rigor, 2G-2 feasibility, 2G-3 dispositions) converging in 2G-4. See the full analysis in the conversation above.]

— AI reply end —

— Verbatim AI prompt by LLoL start —

yes and then put them into a new oov2 folder called prompts. write a llog entry about this discussion here to document what we did for debugging purposes (but not for re-reading during sessions). Does that make sense?

— AI prompt by LLoL end —

This llog documents session planning only. It does not contain analytical output. The 8 session prompts in source/matheology/vv/jub/oov2/prompts/ are the actionable output of this planning session.

TELES migration report (2026m04d04)

Mechanical identifier migration applied to this file. All axiom/theorem text references were migrated from short form (e.g., A15) to compound form (e.g., ax15_A15) as part of the matheology compound naming operation. Both forms refer to the same formal object. The old form survives as the suffix to ensure consistency with the oldest records; the new form adds a temporary-status prefix. Forward-facing pages use brief form (ax15) only. See TELES Axiom/Theorem Compound Naming — Execution Prompt for the complete mapping table and DD b12 — Legacy Naming for PET/JUB Axioms and Theorems for the permanent reference.