Short answer: we are running more than twenty AI agents across our own business and our clients’ businesses, and each one owns a narrow, checkable job. Website builds. Supply chain and inventory. Marketing execution. Lead generation. Reporting. Documentation. The newest addition to that fleet is Grok-based agents working alongside our Viktor AI deployment.
Why more agents instead of one big one?
Because narrow beats general when the work is real. An agent with one job, one definition of done and one place to report is easy to supervise. An agent asked to “handle marketing” is not.
Every agent we deploy has three things: a scope it will not step outside of, an acceptance test it must pass, and a rollback path if it gets something wrong. That last one is the part most teams skip, and it is the reason their AI pilot quietly died.
What do the agents actually run?
- Website and storefront builds — theme work, templates, product detail pages, accessibility fixes, performance work, with before-and-after evidence on every change.
- Supply chain and inventory — purchase order workflows, inbound tracking, stock position monitoring, and the chasing that normally lands on a human.
- Marketing execution — content production, metadata, feeds, campaign setup and the unglamorous catalogue hygiene that decides whether ads work at all.
- Lead generation and qualification — research, enrichment, first-pass qualification and routing, so humans only touch conversations worth having.
- Reporting — recurring pulls from the systems of record, assembled into something a decision can be made from.
- Documentation and SOPs — the written process behind all of the above, kept current instead of rotting in a folder.
What changed when we added Grok agents?
Throughput on deep technical work. On a live Shopify build, a Grok agent worked through storefront defects with a discipline we would expect from a senior engineer: identify the actual root cause, name the exact file and setting changed, state the acceptance criteria it verified, and record the rollback.
One example from a build in progress: a hero heading that looked like a headline but contained no real h1 element at all — a genuine SEO and accessibility defect that a visual review would never catch. Another: a brand carousel rendering 180 images where 12 would do, which is a page-speed problem disguised as a design choice.
That is the difference between an agent that writes plausible text and an agent that measures the page and tells you what is wrong.
How do you keep twenty agents from causing chaos?
Four rules, learned the hard way:
- Evidence, not activity. “Done” means measured and shown, not reported.
- Remove, do not hide. Suppressing something with CSS is not fixing it.
- One owner per surface. Two agents writing to the same thing will fight, and the winner will be decided by timing rather than intent.
- A human approves anything irreversible. Money, contracts, client communication, production deletes.
Frequently asked questions
Do AI agents replace staff?
They replace the queue, not the judgement. In practice teams stop deferring work they know they should do, because the cost of doing it collapsed.
What kinds of businesses can use this?
Any business with repeatable process. We deploy agents for ecommerce brands, but also for service businesses, distributors and operators whose work lives in documents, spreadsheets and inboxes.
How long does a deployment take?
The first useful agent is usually running in days. The value comes from the process design around it, which is the part we are actually selling.
Curious what your first three agents should be? Name your stuck point on Work With Us and we will tell you where we would start.

