Coding Agent Log to Blog Post

Using chat history to create richer blog drafts

I built a working promo video draft in 30 minutes. I also got a complete transcript of the AI conversation that produced it.

The code tells you what I built. The conversation tells you why and how: false starts, creative corrections, decisions, and dead ends.

This is how I turn that raw log into a polished blog post.

(Tip: I use the SpecStory extension to automatically capture every chat.)

From Raw Log to Insights

A raw transcript is a data dump. It contains more detail than I need. I use Gemini's large context window to upload the full history and ground the first draft in what happened.

1. Pinpointing Critical Feedback

Human expertise is critical. The chat log provided the exact prompts I used, making the examples real and concrete.

For example, syncing an animation to a musical cue is a matter of taste. The transcript gave me the exact quote, which is stronger than paraphrasing or forgetting it.

From the AI Chat Log:

User

I want "Simple Air Application" to come in right at 35 seconds to match the major phrase change in the song.

How it appeared in the blog post:

This is a level of creative direction AI can't do on its own. It can't "feel" the music. It needs a human to provide the keyframe.

2. Showing the Process

Developers want real details. The history log shows the steps I took. When explaining how I gave the AI context for the video, I could show the exact tool call from the transcript.

From the AI Chat Log:

Tool use: mcp__air__fetch_air_documentation

3. Building a Narrative from Key Decisions

The chat log became the outline. I used Gemini to pull out and organize key steps like:

• Aesthetics: When AI-generated text was hard to read

• Fact-Checking: Removing incorrect air.test module hallucination

• Creativity: Syncing animation to musical cue

• Value: Asking for more code and annotations

These moments became the topics.

My Workflow

The transcript makes me more efficient. Here's what I do:

1. Do the work. I use AI to build while SpecStory logs the session.

2. Upload the transcript to Gemini. The log is a primary source.

3. Add my opinions. I add them as additional context.

4. Edit and refine. I do passes with AI and by hand to tighten the language and fit my voice.

The transcript is a chronological record I can rely on. Records beat memory.