Automation architecture · Python engineering · Agent reliability
I’m an automation consultant with over a decade of experience across web, mobile, APIs, and enterprise workflows. I design test architectures, diagnose difficult failures, and build tools that make engineering decisions easier to verify.
My current work brings that discipline to AI agents: capture what happened, check the outcome, and make failures understandable.
Portfolio & experience · The Automation Architect’s Playbook · LinkedIn
- Automation architecture: framework design, browser and API testing, mobile automation, and CI delivery.
- Failure diagnosis: UI stability signals, visual comparisons, test reports, and reproducible evidence.
- Agent reliability: controlled LLM tests, execution records, explicit agent contracts, and outcome verification.
A custom Grok bot I created for testers and development teams. It helps turn requirements into test plans, investigate flaky tests, review Playwright, Selenium and Appium code, draft bug reports, and discuss release risks.
I evaluated it across six real-world QA scenarios. Its recommendations and generated code still require engineering review and execution checks; it is not an autonomous release approval gate.
Local-first diagnostics, plugin health checks, safety signals, and incident
postmortems for Hermes Agent, listed in the official Hermes plugin catalog. It
correlates config, plugin state, and logs into redacted ok/warn/fail/unknown
findings with concrete recommendations. Missing evidence is reported as unknown,
and log keywords are treated as evidence, not root cause.
A reliability wrapper around SeleniumBase UC Mode for authorized browser testing on applications with modern bot defenses. It standardizes browser setup, bounded challenge recovery, fallback clicks, and screenshots, and raises explicit errors instead of silently continuing. It does not make automation undetectable.
pip install sb-stealth-wrapper
Reduce timing-related Selenium failures with configurable UI stability checks and diagnostics. Application-specific assertions still decide whether the outcome is correct.
pip install waitless · Technical walkthrough
Fixture-scoped mocks for supported LLM SDK calls, including typed responses, streaming scenarios, and repeatable failures. Active fixtures intercept supported calls; installing the plugin alone does not block network access.
pip install "pytest-mockllm[openai]" · Testing boundaries
HTML reports for pytest and unittest with test-phase results, step details, and screenshot evidence to help investigate failures.
pip install pytest-glow-report · Project walkthrough
Save and restore current-origin cookies and web storage, with optional encryption and explicit restore validation. Session reuse complements dedicated login tests.
pip install selenium-teleport · Session reuse guide
A general-purpose agent platform for turning goals into inspectable outcomes.
Starlight coordinates domain agents working with code, data, APIs, browsers, devices, or language models. It bounds mission execution and returns reports with agent identity, attempts, results, and evidence. Agents own their domain logic and outcome checks.
The current 5.x alpha includes a Node.js 22+ runtime, local CLI, and authenticated remote-agent protocol. A browser or model provider is not required. The earlier browser-specific implementation is legacy.
Repository · Demo & documentation · Start with the architecture
- pytest-why: a pytest plugin that classifies common failures with local, deterministic rules and writes concise explanations.
- Agent Safety Doctor: an early alpha, local-first scanner for AI coding-agent workspaces with redacted evidence reports.
- Agent Blackbox: a local-first flight recorder and CI diagnostic gate for AI-agent runs.
- Project Vandal: runtime UI mutation testing for Playwright to check whether tests catch regressions.
- Visual Guard: screenshot baselines, visual comparisons, region masking, and reviewable differences.
- Visual Sonar: computer-vision automation for WVD and Citrix environments without DOM access.
- The Automation Architect’s Playbook: a free guide to framework design, browser internals, failure analysis, and AI-assisted testing.
- My writing on Waitless was featured in PyCoder’s Weekly #714.
- My background includes published research in spatial clustering, which informs how I approach algorithms and automation design.
Working through an unreliable test suite, an automation architecture decision, or an AI-agent workflow that needs better evidence?