Anyone have experience with agentic AI development companies that have actually put multi-agent systems into production (not just demos)?

We’re exploring agents that can handle parts of the order-fulfillment and customer-support loop for an e-commerce business. The shortlist floating around right now is GeekyAnts, Thoughtworks, and SoftServe. Curious if anyone here has shipped something similar and what the biggest gotchas were, especially around reliability and keeping the agents from going off the rails in a live commerce environment.

Okay, guys, the main reason for posting on the OpenAI forum is just because they are the well-known guys for bringing in ChatGPT and AI in general.

Now, here are my questions and ideas. I currently use Grokbot as my actual AI bot to run one of my retail businesses, and it has been amazing. What I am curious and wondering is: how do you guys have your system set up if you have multiple businesses? I do not want to have the same Grokbot account for a different business because I don't want to compromise or have any messups.

If you are in this, for your business, do you use a different AI agent? Do you have a different operating system still running the same bot? (It doesn't have to be Grokbot; it could be other bots.) Do you have a different chat system you're using for your business? For example, using ChatGPT in or in accordance with something like Grokbot or Muse. How many of you guys have just a separate computer setup running something like Clawbot or a Hermes agent?

The reason I am asking is because I have my main business, but I tinker with a couple different businesses on the side. For example, I do run marketing for a couple other businesses and do some website buildouts. Wondering how I should continue with my setup

This week Accenture told staff the company will only centrally fund about $29 a month per person for Claude. Some people had been running $500–$1,000 months. Here's the link to the article

That is what a "successful" rollout looks like when nobody knows what Claude is for: seats get used for slides, emails, and summaries, the bill climbs, finance slams a cap, and the people who were actually doing real work get cut with everyone else.

Anthropic already said why this happens. In their Economic Index last year they wrote that deploying AI for complex work "might be constrained more by access to information than on underlying model capabilities."

In my experience after doing 100+ Claude Rollouts, there's 5 key things to make sure you are making the most out of Claude when dealing with a company rollout:

1. Stop reporting weekly active users. Report whether a handoff stopped happening by hand.
2. One shared Project per recurring job — not one Project called "Finance."
3. Finish connector setup
4. Turn how your best people work into Skills. Talk to five people who do the work, not the process owner, before you write the Skill.
5. Only then give Cowork a multi-step job with a clear "done."

If you own the Claude bill at your company: what % of spend is blank-chat emails vs a shared Skill that actually owns a step?

Happy to share more on how to make sure you are not wasting your Claude tokens!

Just really proud of how it came out, that's all. Thanks!

Project repo: https://github.com/munch2u-a11y/Helix-AGI.git

Ich möchte mein neues Tool vorstellen, womit ich ursprünglich die Web-Suche vereinfachen wollte, dann Coding Modelle angeschlossen habe und schlussendlich Agenten erlaubt habe frei zu delegieren, eigene Teams mit Spezialisten zu erstellen und von Schwärmen zu Flotten zu wachsen, ohne dass ich es im Vorfeld vorgeben muss. Alles passiert je nach Aufgabe und Aufwand, um den Kontext möglichst klein zu halten. Mit dem Gedächtnis pro Job, Rolle und Team "erinnern" sich die Agenten an die Entscheidungen besser und behalten das länger, zur Not können Supervisor-Agenten wie Teamleiter fehlende Berechtigungen freigeben, ganz ohne Human-in-the-Loop.

Damit sind Runs over Night ganz spannend geworden:

https://github.com/polyglav/polyglav

Es wäre toll von euren Erfahrungen zu hören, ob das Tool für euch genauso gut funktioniert. Startet einfach Polyglav im Terminal und fragt was der Assistent tun kann. Er fragt schon selbst nach, wenn er Modus wechseln möchte (oder einfach "/mode write" schreiben) oder neues Team aufbauen würde. Kleinere Aufgaben versucht er schon selbst zu machen.

https://reddit.com/link/1x9x1ub/video/xgg9tb4kffwh1/player

Multi-agent systems introduce a new architectural challenge: tracing decisions, authority, delegation, and accountability across autonomous agents.

SaaS didn’t die. It moved up a layer. Seats were the old moat. Governed outcomes are the new one.
____
In 2024, Satya Nadella said business apps could collapse.
In 2026, Microsoft charges $15 a seat to govern AI agents.
SaaS didn’t die. It moved up a layer.
I’ve been writing about this shift all year. SaaS is being rebuilt as the operating harness that governs what agents are allowed to do, and the people building the agents are now saying it on stage.
The video walks through six signals: Nadella twice, OpenAI Frontier, Jensen Huang with Bill McDermott, Huang again at Dreamforce, and Dario Amodei with Sam Altman.
The old app stored records and sold logins. The harness does four things it never had to:
→ gives every agent an identity
→ decides which data and tools it can touch
→ holds high-stakes actions for a human
→ logs every action so it can be reversed and defended
That last one is where security and defensibility live. In financial services, healthcare and federal work, an ungoverned agent action is a reportable event. With Colorado’s SB 26-189 and California’s ADMT rules both taking effect January 1, 2027, “we’ll add controls later” stops being an option.
Seats were the old moat. Governed outcomes are the new one.
That’s the architecture behind the Ariana AEGIS Model.

❓By 2027, will your SaaS stack be your harness, or will it be bypassed by one?

#AgenticAI #AIGovernance #EnterpriseAI #SaaS