Agentic Pod StudioAgentic AI didn't stop at engineering. So we sat down next to everyone else.
The way we build is changing across the whole organization — not just in code. The proof came from engineering first. The real question was what happens when you take it everywhere else.
How do we bring agentic AI beyond engineering?
These functions run on workflows that are manual, deeply nuanced, and scattered across dozens of systems. You can't automate them from a process diagram. You have to understand how the work actually gets done — by watching it happen.
One engineer.
One expert.
Four weeks.
We handpick most AI-proficient engineers and pair each one with a domain expert from a business function.
The engineer brings the agents. The expert brings the ground truth of the job. Neither could do it alone — and that pairing is the whole point. You build with the person doing the work, not for them.
AI-proficient
does the work
Twenty days, start to shipped.
Every pod runs the same clock. It starts with watching, not building — because the opportunities you can't see from the outside are the ones worth chasing.
Shadow
Observe every step. Document the real workflow. Ask questions. Build intuition.
Prioritize
Rank opportunities by scale, repetition, business impact, and data availability.
Build
Ship a working agent alongside the person who does the job every day.
Validate
Test with others doing the same work. Does it generalize? Does it actually help?
Ship
Put it into the hands of the team and move it into their real workflow.
The speed is never the interesting part.
Hiding in plain sight
Engineers dropped into unfamiliar domains keep uncovering opportunities nobody has thought to name — the kind you only notice by sitting in the seat.
The workflow is the unit
The biggest wins rarely come from automating one task. They come from redesigning the whole workflow around AI — so the workflow, not the task, becomes what you automate.
Redesign removes the rest
Rebuild around AI and the extras fall away — handoffs vanish, approvals shrink, legacy tooling retires, vendor spend drops, decisions accelerate.
The best skills cut across
The most impactful agent skills don't sit inside one team. They run across functions, tools, and systems — which is exactly why they stay invisible from the outside.
Three ways to run a pod.
Same four-week sprint, same shadow-to-ship method. Choose how close the engineer sits to the work.
- Engineer embedded on-site for the full sprint
- Shadowing on the floor, side by side
- Deepest read on friction hiding in plain sight
- On-site for the shadow phase, remote to build and validate
- Balances depth of observation with cost
- Best fit for most functions
- Fully remote pairing across the sprint
- Screen-share shadowing and async validation
- Lightest footprint, fastest to start
Build with the people doing the work — not for them.
You find the real opportunities by sitting next to the work, feeling every friction point, and building alongside it. We're taking this deeper now: understanding work at its core, redesigning it from the ground up, and using AI to change how organizations actually operate.