# Session Analysis: rollout-2026-01-29T12-06-02-019c09a5-6f49-7d31-b40d-ee6379c9621c.jsonl

**Date**: 2026-01-29 | **Duration**: 0.4s | **Turns**: 5 | **Model**: gpt-5.2-codex
**Type**: bug-fix | **Outcome**: abandoned | **Specificity**: 4/5 | **Struggle**: 2/10

---

## Journey

The developer opened a new Codex CLI session and typed "hi" — then immediately interrupted before the assistant could respond. This appears to be a test or accidental session creation, coming just seconds after the end of the deep diagnostic session 10.

## Prompting Assessment (1/5)

**What worked:**
Nothing meaningful was attempted in this session.

> "hi"

**What was vague or could improve:**
The single-word greeting "hi" provides zero context for the assistant to work with. If the developer intended to continue the conversation from session 10, they should have referenced it explicitly.

> "hi"

## Outcome: abandoned

**Evidence:**
The session contains zero assistant messages and zero tool calls. Duration was 0.4 seconds. The developer interrupted immediately after sending "hi."

## Struggle Points

This session was efficient with no significant struggle points — it was simply too short to have any.

## Aha Insight

This session occurred immediately after the comprehensive diagnostic session 10, which ended with the assistant offering to implement three specific fixes. The developer may have intended to open a new session to request those implementations but then decided to continue in a different way. The pattern of rapid session cycling (sessions 3, 4, 8, 11 were all abandoned in under 1 second) suggests the developer might benefit from using a single long-running session rather than opening/closing sessions frequently.

**Evidence:**
> Session metadata shows `"duration_seconds": 0.4` with the prompt being just `"hi"` — coming only 18 seconds after the previous session ended at 12:05:58.

## Coach Tip

If you want to continue a conversation thread from a previous session, start the new session with a brief recap and a clear request: "In my last session, you identified false negatives in my sampler. Please implement the `sample_excluding` fix." This gives the assistant immediate context instead of requiring a full re-investigation of your codebase.
