Weave "optimizations reveal deeper issues" framing into engagement report
executive summary, case study, and optimization README. Add O(N²) text
extraction fix, per-request RSS creep (24→17 MB), and memray profiling
data that were previously undocumented.
Apply research-backed case study structure: headline anchoring on
biggest numbers, customer-as-hero framing, loss aversion, narrative
arc, methodology for developer credibility. Collapse PR inventory
to category summary, ~1,100 words in optimal range.
- Rename case-studies/pypa/ → case-studies/python/ to match .codeflash/ convention
- Add case-studies/netflix/metaflow/summary.md (7-18x lz4 vs gzip)
- Add case-studies/unstructured/core-product/summary.md (14.6% latency, 2.1 GB memory)
- Update main README results table with all five case studies
