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I build software across AI tooling, APIs, full-stack applications, and native systems. My work spans shipping interfaces and backend services, integrating local language models, debugging production environments, and contributing fixes to other teams' open-source projects.
What I optimize for: reproducible setup, observable behavior, clear failure handling, tests that catch regressions, and code that another engineer can review and maintain.
LeaseLedger is an original, single-host durable job queue built with Python and SQLite WAL. It tackles real backend consistency problems: fencing stale workers, recovering crashed leases, idempotent producer requests, transactional audit events, bounded retries and dead-letter jobs. Four independent processes compete for work in its integration tests, and a killed worker's lease can be reclaimed safely. All 34 tests pass across Python 3.11–3.13 in CI. A one-command offline demo also proves stale-ACK rejection and backup recovery using a real SQLite database. Version 0.1.2 adds seeded fault-injection tests and fixes a verified queue-starvation bug where 100+ exhausted leases concealed runnable jobs. Version 0.1.1 introduced online WAL-safe backups and integrity verification.
Run the verified offline demo · View its machine-checked JSON output · Read the architecture · Why fencing tokens matter · See verified CI · v0.1.2 release · Reproduced claim starvation and fix · Online backup and recovery
Scope is explicit: at-least-once processing on a single host, not exactly-once external effects or a multi-region distributed queue.
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Local-first AI developer agent · Python · Git Takes a repository task through code inspection, change planning, edits in a separate local workspace, test execution, and reviewable Git diffs. Engineering focus: fail-closed Docker test isolation, fenced local workspaces, protected diagnostic logs, adversarial regression tests, and live isolation CI. |
Native audio integration · C++ · PipeWire · CoreAudio Unofficial community ports retaining the upstream DfxDsp processing engine while adapting audio transport to Linux and macOS. Engineering focus: platform boundaries, native builds, audio processing, installer workflows, and platform CI. Status: alpha software; see the README for platform-specific limitations. |
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Full-stack learning platform · TypeScript · Next.js Study materials, practice quizzes, mock exams, progress tracking, accounts, moderation, and an optional local-AI tutor. Engineering focus: end-to-end product architecture, health checks, and automated project validation. |
Local codebase exploration · Python · FastAPI · React · Ollama Clones or imports repositories, indexes source, exposes file trees and code search, and supplies relevant context to a local language model for questions about the code. Engineering focus: safe streaming imports, error handling, CodeQL security scanning, and frontend/backend CI. |
Alongside source code, I maintain engineering case studies showing the problems, design decisions, tests and trade-offs behind my work: lease fencing, agent isolation, ZIP/Git import boundaries, full-stack CI recovery, and native Linux/macOS portability. Each case links to verifiable PRs and CI results.
As of 13 October 2026, I have 20 merged pull requests across 9 repositories owned by other developers/organizations. These include bug fixes, tests, developer tooling, and documentation. Browse the merged PR history.
| Project | Accepted work |
|---|---|
| Hebbian-Robotics/hflow | 9 merged PRs involving data validation, artifact handling, tests, and examples |
| Internet Archive / Open Library | Corrected out-of-date developer documentation |
| ChurchCRM | Fixed floating controls overlapping modal dialogs |
| StaveIndustries / woo-pay | Improved WooCommerce error reporting and payment-failure persistence |
| pranjalparmar/fastdocparse | Simplified CLI errors and grounding logic |
PR acceptance and code review are more informative than a raw count of opened PRs. Current status and diffs are available via the links above.
Recent maintainer review follow-through: On ChurchCRM PR #10484, I corrected the translation-extraction configuration in response to maintainer feedback, verified that the requested string appeared in the generated catalog without committing it, and passed lint plus independent security checks. The PR is still open, so it is not included in the merged-contribution count.
Maintaining community contributions: WhatsApp bot PR #40 incorporated a correction from lucaslokchan's earlier PR #19, preserved verified co-author credit, and added privacy tests that prevent raw chat messages and provider exceptions from reaching logs. Both Node 20 and Node 22 CI checks passed. Historical unmerged credential-exposing PRs were closed with rotation notices; closing them does not erase the old public diffs.
My earlier Telegram/WhatsApp AI bot repositories have attracted developers and forks. They are legacy projects built around older APIs, not examples of my current production architecture.
| Repository | GitHub stars · forks (13 Oct 2026) |
|---|---|
| chatgpt-bot-telegram | 141 · 148 |
| ChatGPT-Telegram-Bot | 72 · 371 |
| whatsapp-chatgpt | 68 · 168 |
| Area | Technology |
|---|---|
| Backend & AI | Python, FastAPI, Node.js, APIs, local LLMs, Ollama, agent workflows |
| Frontend | TypeScript, React, Next.js, JavaScript |
| Systems | C++, Linux, macOS, SQLite WAL, fencing tokens, crash recovery, native audio |
| Delivery | Git, GitHub Actions, Docker, integration tests, VPS deployment, observability |
I publish reproducible engineering work, clear failure analyses, and maintenance-focused open source rather than maximizing commit counts. See the public portfolio quality roadmap and recent work on fenced leases and isolated AI-agent test execution.
ClonePeek is a dependency-free, offline preflight scanner for execution-capable repository config (editor auto-tasks, npm lifecycle scripts, devcontainer commands and MCP servers). In v0.2.1, I reproduced and fixed a Git filesystem-monitor execution risk in passive scans. The v0.2.2 release fixes a previously missed Windows PowerShell execution pattern and includes a 46-case synthetic evaluation with all 34 tests passing on Linux, macOS and Windows CI. The evaluation deliberately records false positives and false negatives; its scores do not estimate real-world malware detection.
I enjoy tackling concrete bugs, building useful developer tools, and working through edge cases with maintainers. For engineering opportunities, architecture discussions, or collaborations:
harshitethic.com · LinkedIn · contact@harshitethic.com
Evidence first: source code, reproducible examples, tests, PR discussions, and the trade-offs behind implementation.



