Daily Development Log - January 14, 2026

The parsing code expected transcripts in a clean markdown format where speaker turns are clearly delineated. What it got was… less structured. Paragraphs blend together. System messages about tools being invoked get mixed in with actual conversation.

Here’s the crux of the problem: there’s no programmatic way to distinguish “Claude is explaining something” from “Claude is running a tool that produces output.” The transcript captures everything, which makes replay possible but analysis difficult.

I tried several approaches:

1. Regex-based parsing — Looking for patterns like “User:” and “Assistant:” worked until it didn’t. The moment there’s code in a response that happens to contain the string “User:”, the parser gets confused.

2. Line-by-line state machine — Keep track of whose turn it is and accumulate lines. This handled simple cases but fell apart with multi-paragraph responses containing code blocks.

3. Treating the whole thing as a document — Feed the entire transcript to Claude and ask for structured extraction. This actually worked best, but now I’m using an AI call to prepare data for another AI call, which feels architecturally suspect.

The third approach is probably what I’ll ship. It’s not elegant, but it’s reliable. Sometimes you have to accept that a system’s quirks become your problem to work around rather than solve properly.

What I Learned

The bigger realization: AutoBlog was over-engineered from the start. I built a multi-pass generation pipeline (draft → review → revise → polish) without first confirming that raw material flowed cleanly into that pipeline. I should have started with “can I reliably get transcripts in a usable format?” instead of “how sophisticated can my generation system be?”

This is a pattern I’ve noticed in my own work. I get excited about the downstream processing—the clever parts—and handwave through the data ingestion. Then I’m surprised when the clever parts don’t work because they’re receiving garbage.

The fix isn’t more sophisticated parsing. The fix is finding a better data source. Claude Code likely has structured session export formats I haven’t found yet, or I could hook into the session earlier, before the data becomes unstructured text.

Tomorrow

Two items on the list:

1. Investigate whether Claude Code has JSON or structured transcript export options
2. If not, design a capture hook that extracts turns as they happen rather than parsing a blob post-hoc

The tmux hook took twenty minutes. The AutoBlog debugging took four hours and isn’t done. That’s software development—sometimes the simple thing is simple, and sometimes you’re deep in the weeds before you realize the weeds are the whole garden.

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This post was generated automatically from my Claude Code sessions using AutoBlog.