Flagship
Production-oriented public products. These receive the shared quality baseline, release discipline, and primary portfolio attention.
Portfolio operating model · July 2026
One role for every repository
Twenty-two owned repositories, deliberately split between three public flagships, two portfolio surfaces, one candidate, three private products, seven labs, and six archived projects.
Active portfolio
Maintenance and promotion concentrate on the flagships. Labs remain intentionally lightweight; private products keep operational data and workflows out of the public portfolio.
Portfolio surface
The GitHub profile and personal website that explain the work and keep public status, source, and deployment links accurate.
Flagship candidate
Podcast Enhancer is the next promotion candidate after the initial flagships meet the quality threshold.
Private product
Trading, portfolio, broker, and job-search products remain private. No private data or operational output is published here.
Lab
Focused experiments used to learn or prove a pattern. Labs may be incomplete and do not claim the flagship engineering baseline.
Archive
Read-only history, superseded experiments, and duplicated collections. Archiving preserves learning without competing for maintenance attention.
Canonical classification
This list is the public source of truth for repository roles. Private products are named for completeness but intentionally have no public links.
| Classification | Repository | Operating decision |
|---|---|---|
| Flagship | BA Assistant | Baseline v0.1.2 · Maintain the shared flagship baseline. |
| Flagship | BA Jira Agent | Baseline v0.1.0 · Maintain the shared flagship baseline. |
| Flagship | Stock Research Assistant | Baseline v0.1.0 · Maintain the shared flagship baseline. |
| Portfolio surface | Touseef1949 profile | Keep the public portfolio index concise and current. |
| Portfolio surface | touseefshaik.com | Maintain public status, case studies, and this map. |
| Flagship candidate | Podcast Enhancer | Reassess after the three flagships reach the baseline. |
| Private product | Momentum Scanner | Keep code, trading data, and generated reports private. |
| Private product | Stock Agent Platform | Keep code, broker details, and portfolio data private. |
| Private product | LinkedIn Job Copilot | Keep code and job-search information private. |
| Lab | Whiteboard to Requirements | Retain as a focused vision-to-requirements experiment. |
| Lab | Cast Relationship Graph | Retain as a knowledge-graph visualization experiment. |
| Lab | India Streaming Finder | Retain as a search and aggregation experiment. |
| Lab | Sarvam TTS | Retain as an Indian-language speech experiment. |
| Lab | Sarvam Voice AI | Retain as a voice-AI experiment. |
| Lab | Writing Tools | Retain as a focused writing experiment. |
| Lab | Evals | Retain as an AI-evaluation learning lab. |
| Archive | Agentic RAG | Preserve privately as superseded RAG exploration. |
| Archive | Agentic RAG Firecrawl CrewAI | Preserve privately as duplicated RAG exploration. |
| Archive | Agno CrewAI | Preserve as early agent-framework exploration. |
| Archive | Moodsetter | Preserve as an unmaintained experiment. |
| Archive | News Agent | Preserve as an unmaintained experiment. |
| Archive | AImpactForge | Archive the duplicated collection; retain standalone labs as the clearer sources. |
Promotion rule
Depth before breadth
A lab or candidate is promoted only after it has a clear user and value proposition, reproducible setup, change-safety checks, security and operational boundaries, and active stewardship.
Explore the active products →