AI Engineering & Automation

From Harness Engineering to AI Agents—building systems that think, act, and iterate

Multi-model orchestration & engineered AI systems

Autonomous systems that perceive, decide, and act

The craft of designing inputs for reliable outputs

Bringing AI into real workflows

Harness Engineering

Multi-model orchestration & engineered AI systems

Multi-Model Orchestration: route subtasks to the most suitable model based on each model's strengths.
Context Management: segment and summarize context during model switching to maintain coherence across long conversations.
Degradation & Retry: built-in fault tolerance in AI workflows so a single model failure won't interrupt the entire flow.
Performance Monitoring: track token consumption, latency, and output quality across models to optimize cost and speed.

Autonomous systems that perceive, decide, and act

Browser Automation Agent: migrated from Selenium to Playwright, demonstrating how Agents navigate complex web interfaces.
Custom Agent Pipeline: build Agents that combine LLM reasoning with API calls, file I/O, and structured data processing.
Tool Calling Pattern: design the Agent's ability to call external tools during decision-making.

The craft of designing inputs for reliable outputs

Structured Prompting: use system prompts, role definitions, and output format constraints to regulate model behavior.
Chain-of-Thought Reasoning: break complex tasks into step-by-step reasoning chains for improved accuracy and interpretability.
Few-Shot & Zero-Shot: choose appropriate examples or write precise instructions to get the best results without wasting tokens.
Iterative Optimization: systematically test prompt variants, measure output quality, and converge on the best expression.

Bringing AI into real workflows

Workflow Integration: connect AI pipelines to email, calendar, CRM, and other daily tools via API and Webhook.
Data Processing Pipeline: use AI to extract, transform, and analyze data from unstructured sources.
Human-in-the-Loop: design mechanisms where automation knows when human approval is needed.

Engineering capability needs business context to create value