Two Ryan Fleury talks about the rad debugger / radare2 codebase,
extracted via scripts/video_analysis/extract_transcript.py:
rcJwvx2CTZY_ryan_fleury_raddbg_codebase_intro.json
YouTube ID rcJwvx2CTZY; ~50 min; raddbg codebase intro.
Relevant quote (v1@2237s): 'a view type view is just saying, If you
have this type, just do that automatically for me.'
_9_bK_WjuYY_ryan_fleury_raddbg_walkthrough.json
YouTube ID _9_bK_WjuYY; ~2 hr; raddbg deep walkthrough.
Relevant quote (v2@7697s): 'lenses in the code but to the users
theyre just called views... the type view is just saying... if
you have this type, just do that automatically for me.'
Naming follows the existing docs/transcripts/ convention
({video_id}_{speaker}_{topic}.{ext}) used for i-h95QIGchY_...,
Ddme7DwMQBI_..., wo84LFzx5nI_... .
Referenced from: conductor/tracks/default_layout_install_20260629/spec.md
(Eventual Normalization Target section) and metadata.json as context
for the deferred 'panel_defs_fleury_migration' track. The current
default_layout_install_20260629 track sets up layouts/ + src/layouts.py
as the home for the eventual Fleury-style PANELS: tuple[PanelDef, ...]
migration; this commit makes the source material available in-tree.
This one was important to keep is it was the first attempt at an autonomous run.
Essentially worked except for a turn exhaustion on ai side (need to tweak some config maybe).
Foundation research track. Produces a single markdown report at
docs/ideation/2026-06-12-intent-based-scripting-languages.md surveying
intent-based scripting languages and proposing a 4-tier vocab (~40
verbs) for a Meta-Tooling-facing intent DSL.
The report's 7 sections:
1. The 'intent-based' design philosophy (O'Donnell immediate-mode,
Onat/Lottes hardware, CoSy open-vocab, Jofito intent-mapping)
2. Prior art across 8 clusters (0: IMGUI, 1: Concatenative,
2: Array, 3: Intent-mapping, 4: Meta-Tooling, 5: SSDL shapes,
6: Command Palette, 7: Result error handling)
3. The grammar (14 primitives formalized from user's pseudocode)
4. The 4-tier vocab (math, data pipeline, shell, AI-fuzzing tolerance)
5. Hardware mapping (4 anchor claims to Onat/Lottes/O'Donnell/APL-K)
6. AI-agent properties (10 claims tying to existing project
architecture: Meta-Tooling domain, 3-layer security, 4 memory
dimensions, stable-to-volatile cache, Result envelope,
Command Palette 33 commands, Hook API, IEventTarget/sandbox,
'reads are free')
7. Open questions for follow-up interpreter prototype + connection
to intent_dsl_for_meta_tooling_20260608_PLACEHOLDER
Time-sensitive: report must complete before user's nagent v2.2.
No new src/ code, no new tests, no pyproject.toml changes.
Pure research deliverable.
ed