Agentic Coding & Automation

From Assistance to Agency

Traditional AI coding tools wait for you to type. They suggest completions, maybe a function or two, then stop. Agentic systems are different—they can take a goal, break it into steps, execute those steps, verify the results, and course-correct when something doesn't work.

This changes the development dynamic. Instead of writing code line by line, you can describe an objective and supervise the AI as it works toward that goal. Your role shifts from typist to architect, reviewer, and quality gatekeeper.

• Describe a feature; watch it get implemented across multiple files
• Request a refactor; review the changes before committing
• Ask for tests; get coverage for complex edge cases
• Point at a bug; let the AI propose and verify a fix

Agentic Workflows in Practice

I integrate agentic coding into development workflows using tools like Claude Code, Cursor, and custom automation. Here's what these workflows typically look like:

Code Generation

You provide requirements—a spec, a ticket, a conversation. The agent reads relevant existing code, plans the implementation, writes the code, and runs tests. You review the output, provide feedback, and the agent iterates. The final code is yours to approve and commit.

Code Review & Refactoring

Point the agent at code that needs attention. It analyzes the structure, identifies issues, and proposes improvements. Security vulnerabilities, performance problems, code smell—the agent can spot them and suggest fixes. You stay in control of what actually changes.

Test Generation

Testing is often the first thing to slip when deadlines press. Agents can generate comprehensive test suites, including edge cases human developers might overlook. They read the code, understand the intent, and create tests that actually verify behavior.

Integration with Your Toolchain

Agentic coding works best when it's woven into your existing development environment, not bolted on as a separate system. I help teams integrate these capabilities with:

• Git workflows: Agents that understand branching, can create PRs, and respect your commit conventions
• CI/CD pipelines: Automated checks that give agents feedback on whether their changes work
• IDEs: Cursor, VS Code, and other editors with agentic capabilities built in
• Project management: Connections to Jira, Linear, or GitHub Issues so agents understand context
• Documentation: Agents that can read and update docs as code changes

The goal is invisible integration. Agentic capabilities should feel like a natural extension of how your team already works.

For complex orchestration needs, I work with frameworks like LangChain and LangGraph to build multi-agent systems where specialized agents collaborate on larger tasks. One agent might analyze code structure, another generates implementation, and a third runs tests and validates—all coordinated through an orchestration layer that keeps humans informed and in control.

Humans Stay in the Loop

I'm not interested in fully autonomous code generation that runs unsupervised. That's a recipe for subtle bugs and technical debt. The agentic systems I implement keep humans in meaningful control:

• Review gates: Code changes require human approval before merging
• Scope limits: Agents operate within defined boundaries, not free-roaming through the codebase
• Audit trails: Every agent action is logged for accountability
• Confidence signals: Agents communicate when they're uncertain
• Easy rollback: If something goes wrong, reverting is straightforward

The developer's judgment remains central. The agent handles the tedious execution; the human provides direction, context, and quality assurance.

Bringing Agentic Coding to Your Team

Adopting agentic workflows is a process, not a switch. I typically recommend starting small:

• Pick a specific use case—test generation, documentation, boilerplate code
• Integrate with one team or project first
• Establish review patterns and feedback loops
• Measure impact: velocity, quality, developer satisfaction
• Expand gradually based on what works

I work with teams to identify the right starting point, set up the tooling, and build the practices that make agentic coding successful and sustainable.