Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
1Unique collaborators
1/1OpenAlex citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Openalex:
A5148028421
ORCID evidence
No valid ORCID is stored.
Observed aliases (2)
- Jayanthi M (openalex, provider refresh)
- Jayanthi M (openalex, source metadata)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
- Human Ai Collab: 1 paper
- Labor Markets: 1 paper
- Org Design: 1 paper
- Productivity: 1 paper
- Skills Training: 1 paper
Claim outcomes
- Developer Productivity: 1 paper
- Employment: 1 paper
- Error Rate: 1 paper
- Task Completion Time: 1 paper
- Hiring: 1 paper
- Output Quality: 1 paper
- Skill Obsolescence: 1 paper
Papers in the OpenAlex view
Latest stored OpenAlex author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| AI coding assistants are reshaping software engineering rather than replacing it: firms are substituting automation for routine junior work—cutting entry-level hiring—while value and risk move toward architecture, verification and governance; unreviewed AI-generated code raises measurable security and technical-debt concerns.openalex | Jayanthi M provider id |
2026-08-24 | 0 |
Citation observation summary
OpenAlex supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 0 cumulative citations. This is a coverage summary, not an author score or h-index.