Working together
I’m the Engineering Manager at Delphos Labs by day, where I run a fleet of agents alongside my team and ship more in a week than I used to in a month. Alongside that, I help a small number of teams get the same kind of leverage: the agent workflows, the review pipelines, and the management practices that make AI-native work actually stick.
Three ways to work together
Start with the audit. It’s an hour of your time, and you leave with a plan you can act on whether or not we work together after. If there’s a fit, we build from there.
AI productivity audit
1 hour of your time
Where is AI already helping your team, where is it quietly a distraction, and what's the highest-leverage workflow you're not yet running? I map how your team actually works and hand you a prioritized plan.
- Where AI fits and where it's just noise
- Three quick wins you can ship this week
- The one workflow worth building next
- A prioritized action plan you keep
Best when: you know AI should help but don't know where to start.
Most common
AI-native workflow build
Hands-on engagement
We build your team's agent workflow together: task design, parallel worktrees, review pipelines, and the documentation that turns one good run into a repeatable system.
- An agent workflow codified in your repo
- Parallel task execution your team can run
- Specialized review agents for your standards
- A written playbook your team keeps
Best when: your team is dabbling with AI but not yet compounding.
Engineering velocity
Ongoing, embedded
I join as a hands-on engineering leader and stay. I install the AI-native workflow, raise the team's throughput, and keep improving the system as your needs grow. Architecture, hiring, and strategy come with it.
- A leader in the work, not just advising it
- Throughput that climbs as the system matures
- Architecture, hiring, and technical strategy
- A process that gets sharper every cycle
Best when: you need senior leadership before you can hire it full-time.
Not just engineering teams
The biggest leverage I've found isn't in code; it's in the system around it. Agents work the same way on any knowledge work that synthesizes sources and has to stay consistent: design docs, proposals, research, reports, and the operations behind them. If your team writes for a living, the audit and the workflow build apply to you too. I wrote about why in The Knowledge Stack.
What I won’t do
- Code-for-hire that doesn’t compound into a relationship. I’m not a contractor.
- “Strategic” work without enough technical depth to be useful. I’m not a generalist advisor.
- Anything that conflicts with my work at Delphos Labs. I treat that boundary carefully.
I'd love to hear from you
Tell me what you're working on and what's actually hard about it. I'll tell you whether the audit fits, what you'd walk away with, and where it could lead. If it's not a fit, I'll try to point you at someone better suited.
Send me a note