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Sprint Retrospective

What Went Well

  1. Prototype demonstration was clear and functional – The customer understood the current behaviour and was able to give actionable feedback.
  2. Valuable technical guidance from the customer – The customer provided concrete next steps (diff-first workflow, context packaging, token size limits, backlog grooming).
  3. Team alignment improved – The meeting clarified responsibilities and the logical order of development steps (diff → context → LLM experiments).

Problems Encountered & Root Causes

1. Unclear approach to handling diffs vs full files

  • Root cause: Assumptions were made without experimentation; team hadn’t validated LLM behaviour on diffs vs full-file context.
  • Impact: Development stalled because it was unclear how to design prompts and context packaging.

2. Backlog lacked grooming and coherent prioritisation

  • Root cause: Story points were assigned intuitively without relative sizing; the backlog wasn’t sorted by complexity or readiness.
  • Impact: Harder to select appropriate tasks for the sprint; long-term tasks were mixed with near-term ones.

Changes for Next Sprint (Prioritised)

High Impact

  1. Perform hands-on experiments with diffs and full files using LLMs
  2. Compare outputs on 2–3 test cases.
  3. Establish what “good summary” means using real examples.

Medium Impact

  1. Define the initial CLI command structure

  2. Draft commands such as cli changes-since, cli ask, cli diff.

  3. Set an internal token usage limit and warning system

  4. Apply a temporary personal token or free-tier LLM with mindful usage.
  5. Add a limit (e.g., 10k–20k tokens).

Low Impact

  1. Introduce backlog grooming sessions before sprint planning
  2. Sort tasks by clarity and size (small → medium → large).
  3. Apply relative story points only after grouping.