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WHITTL v2.4 RELEASE NOTES

Latest patch + the v2.4.0 major release

Jump to: v2.4.1 (May 2026) · v2.4.0 (April 2026)


v2.4.1 — Auto-fix Stale Rule Patch

May 2026 · Patch release on top of v2.4.0

v2.4.1 is a fast follow-up patching a specific failure mode that surfaced in the first hours of post-release usage: an auto-fix rule based on outdated PySide6 5.x knowledge was reverting AI-generated imports on every Run, creating infinite fix-and-revert spirals on any project using PySide6.QtWebEngineCore classes. Plus a defensive improvement to the file-state merge logic that hardens against a class of similar bugs.


STALE WEBENGINE CLASS-LOCATION AUTOFIX RULE (fixed)

Field repro on a browser project running on PySide6 6.11.0: every press of the Run button produced this log signature, regardless of which model generated the project:

[AUTO-FIX] Moved QWebEnginePage from PySide6.QtWebEngineCore to PySide6.QtWebEngineWidgets
[RUN] Live error detected: cannot import name 'QWebEnginePage' from 'PySide6.QtWebEngineWidgets'
    Did you mean: 'QtWebEngineCore'?

The AI correctly imported QWebEnginePage from PySide6.QtWebEngineCore — its real location in PySide6 6.0 and later. Whittl's add_missing_imports autofix looked up QWebEnginePage in its internal class-to-module mapping, found it pointing at QtWebEngineWidgets (the PySide6 5.x location), and "moved" the import — silently breaking it. The AI's next auto-fix round restored the correct import; Whittl's autofix reverted it again on the next Run. The user could not break out of the loop without manually editing the file outside of Whittl.

Root cause: core/autofix_rules.py had four WebEngine classes hardcoded to QtWebEngineWidgets. In PySide6 6.0+ only QWebEngineView stayed in QtWebEngineWidgets — everything else (Page, Profile, Settings, History, CookieStore, Script, DownloadRequest, plus 16 more) moved to QtWebEngineCore. The rule was written against PySide6 5.x and never updated when the library reshuffled its module layout. Fix: corrected the mapping for the four affected classes and added 19 more QWebEngine* classes to QtWebEngineCore. Pinned by the 321 existing autofix tests.

Broader pattern worth flagging: frontier models often know newer APIs than Whittl's static rules do. The usual assumption that "Whittl's deterministic rules know better than the probabilistic AI" inverts in cases like this. A v2.5 candidate is being tracked for stale-rule detection.


PREVIEW PANEL MERGE-BACK COULD CLOBBER AI EDITS (defensive fix)

Discovered during investigation of the WebEngine spiral above. The merge-back logic in preview_panel.get_all_files() unconditionally trusted the editor's get_code() output over the in-memory file dictionary on every read. Under tight timing (AI tool edit → signal dispatch → set_code() → Qt deferred layout pending → user clicks Run), the editor's get_code() could return a previous-frame value that overwrote the AI's fresh content before Run wrote files to disk.

Fix: set_code() now calls document().setModified(False) after each programmatic write. get_all_files() only merges editor content back into the file dict when document().isModified() is true (the user typed since the last set_code()). Otherwise it trusts the file dict, which already holds the latest AI / autofix output. User typing still wins; programmatic writes no longer get clobbered by stale display state.

This wasn't the cause of the WebEngine spiral — that was the autofix rule above — but it's a real defensive improvement.


UPGRADING FROM v2.4.0


v2.4.0 — The Whittl Layer + In-App Updates

April 2026 · Major release


HEADLINE: IN-APP AUTO-UPDATER

v2.3 and earlier dumped users at a browser download URL and expected them to find the installer, run it, click past SmartScreen, and restart manually. v2.4 replaces that with a proper in-app "Download → Restart to install" flow with SHA-256 verification and silent install handoff.

What changed

This is the first Whittl release that genuinely auto-updates itself. Subsequent versions ship through the same flow.


THE WHITTL LAYER

Every other AI coding tool is a chat window over someone else's model. v2.4 formalizes what Whittl actually is: the knowledge layer that sits between you and the AI — 75+ auto-fix rules, a curated skills library, oscillation guards, hard round caps, tool executors, and validators. The model writes the code; Whittl makes the model better at building Python desktop apps.

This is positioning more than code — the components all existed in v2.3 — but v2.4 ships a versioned whittl_layer.json manifest pinning the layer's components and their versions. Foundation for v2.5's Whittl Commons: a download channel for community-sourced rule bundles that update independently of the binary.


REWRITTEN HELP TAB + FULL DOCS SITE

The v2.3 Help tab was a plain-text QTextEdit skeleton with 5 sparse sections nobody read. v2.4 rewrites it as a proper QTextBrowser with:

Plus a brand-new full documentation site at lyndeneftoda.com/docs/ — from zero pages at v2.3 ship to 45 pages totalling ~62K words. Covers Getting Started (3 pages), Features (15), Backends (6), Workflows (9), Reference (8), and Troubleshooting (3). Built with MkDocs + Material, custom-styled to match the retro brand palette (VT323 + Press Start 2P, navy/cream/tan/copper).


MID-GENERATION QUESTION TOOL

The AI can now ask you structured design questions mid-generation when it has to guess at a decision — SQLite vs JSON, bottom tabs vs nav drawer, local vs cloud. Better than guessing wrong and regenerating.


CONTENT-AWARE SKILL INJECTION + LAZY LOADING

Skills can now declare YAML frontmatter that gates injection on the active project's actual imports and framework target. Skills without frontmatter keep today's always-inject behavior — no migration needed for existing libraries.


CLAUDE-COMPATIBLE SKILL PATHS

SkillManager now discovers skills from three paths in priority order:

Whittl-wins dedupe protects vetted defaults — a random ~/.claude/skills/flet-mobile.md can't silently override Whittl's shipped guidance. Source-aware log line: [SKILLS] Injected 4200 chars (2800 whittl, 1400 claude-user) makes it visible when foreign skills are inflating the prompt. New Preferences toggle to disable Claude paths entirely if you want token cost bounded.


edit_function — PER-FUNCTION SURGICAL EDITING

For projects with 500+ line files, full regen costs $0.05+ per turn and burns 30-60 seconds. v2.4 adds a third edit tier between surgical-diff and full-regen: per-function rewriter. The AI specifies {function_name, replacement_body}; Whittl uses AST to locate the function, replace the body, and preserve indentation across the file.


BUG FIXES & POLISH

Field-driven fixes from real stress-test sessions:


UPGRADING FROM v2.3


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