Coding-agent practice for engineering teams.

Independent Practice · Team Training

Your engineers stop hand-writing the parts an agent already does better. The agents stay inside tests, reviews, and standards. Speed that survives code review is the bar. Taught with the same discipline used to operate infrastructure and distributed platforms under hard constraints.

Your team probably has the agents already. What is missing is the discipline around them, so two or three engineers get faster and the rest of the org inherits the risk.

I'm Boden, a Staff Platform/SRE engineer applying cross-layer reliability practice to coding-agent workflows.Book a conversation →

// why now

Agents are the next thing platform engineering and SRE are responsible for.

Like any production system, they need context, guardrails, observability, and a way to recover when they go wrong. Run them like production systems and the gains stack. Treat them as magic and you get random output and risk nobody's watching. That's the discipline I teach: the boring, repeatable practice that makes their output safe to merge.

// what your team gets

The four outcomes.

FASTER DELIVERY→Engineers move from typing code to directing it. They ship more and stop hand-writing the parts an agent does better.

BETTER CODE, FASTER→Agents that work inside your tests, reviews, and standards produce changes a human can actually review. The quality bar stays where it was; the typing load does not.

SAFE TO OPERATE→Clear rules for what an agent may touch, what needs a human in the loop, and how to stop, roll back, and recover when something looks wrong.

COMPOUNDS→Context, decisions, and patterns from each session get captured and reused, so the team gets faster instead of starting cold every prompt.

// the proof

Good agent operation is something you can measure and verify.

The case studies are on /work, and the method is at /method. One project is not a guarantee. The operation is repeatable, and the receipts live on /work.

// safe operation

Operating is the skill. That's what your team walks away knowing how to do:

What the agent is allowed to change, and what stays off limits across the repo, the pipeline, and production.
When it can act on its own, when it must propose, and when a human has to decide.
How to give it the context it needs so its output is right.
How to capture the work so it compounds instead of disappearing into a chat log.
How to stop, revert, and recover safely when a change goes sideways.

// how it's taught

Live-built, primitives-first, no slides where a terminal will do.

We work in your codebase, on your tasks, side by side. I pair with your engineers, set up the guardrails with you, and teach by doing. Every session produces a runnable artifact your team keeps. All the material derives from open-source work and public patterns, so you can read everything before we ever talk.

// the teaching bar

Complex, plain, honest about tradeoffs.

The standard comes from three years of daily technical briefings to flag officers: complex systems, plain words, a demanding non-specialist audience, every day. Your engineers get the same bar.

// who I work with

PRODUCTION AGENTS→Multi-agent systems you would put near production: written guardrails, visible traces, and a recovery path you can run when a run goes wrong.

ADOPTING TEAMS→You have the tools; you want the discipline that turns them into real throughput without dropping the quality or security bar.

LEVELING UP→Whether you want serious multi-agent workflows or sharper day-to-day delivery, the material is the same primitives, taught on real work.

// why me

Same operating discipline across infrastructure, platforms, and agent workflows. The tools and method are open. Full arc at /about.

All material derives from open-source work and publicly available patterns. Views are my own. This work is independent of and not endorsed by my employer. No classified, proprietary, or employer-specific information is used or discussed.

// independent practice

One secondary practice, with a path for teams and a path for individuals.

This page is the engineering-team path. If you want the same safety and validation principles translated into plain language for everyday use, continue to /ai-partner or try the self-guided /first-win.

Want your team faster and safer with coding agents?

We'll figure out where this pays off for your team, and where it won't.

Book a conversation →