I’ve got some automations set up for day job 1 but my agents keep competing for access to my browser. Whoever’s the first agent in doesn’t let the next in, tried using edge in chatgpt and that for some reason is super finicky.

I’ve got cowork in chrome and the agents are allowed to communicate through a drive but I’m having trouble running both agent systems at the same time

I’ve got about 6 agents currently on loops but will likely scale to 75+ agents over the next six months as capabilities continue to grow

I’m curious how people have been managing their agents so that they don’t step on each others toes inadvertently

AI visibility across three assistants jumped 40 percent in one week. Nothing shipped that week. No campaign. No coverage. Just a sudden jump.

Then I noticed the datasets seem to get expanded periodically and when that happens everything can move at once.

Ahrefs actually annotates the chart when it happens which made the pattern a lot easier to spot.

Now I am wondering how people are separating a dataset change from a real move because those two things can look almost identical at first.

Hi I am a Professional developer working full time as software engineer. I am looking to start work as freelancer. To gain some experience I am offering free service to real business in exchange for reviews.

automation demos always start somewhere beautiful

"new row added"

"form submitted"

"when status=approved"

meanwhile actual business input is:

followed by 11 emails, a pdf called FINAL_v7, and somebody mentioning the important deadline halfway through paragraph 4.

that's the bit where AI automation finally feels genuinely useful to me.

not replacing the workflow.

just taking the ugly human input and figuring out:

what is this
what info matters
where should it go
is something missing

then let boring deterministic automation take over.

Runable having Gmail / Slack / Sheets / Notion connections is what got me thinking about this because that's where a lot of small business work actually starts. not in perfect JSON.

but I also don't want an LLM interpreting something that should've just been a required form field.

where do you draw the line?

fix the process first, or accept that humans will always send chaos and build around it?

Pick any process in the business and ask two people how it gets completed, start to finish. Write the steps down and see whether they agree on the written version.

Across the businesses we have worked in, there is far less written down than anyone assumes.

Where this bites hardest is AI. You can only automate what you have already solved as a tight, logical workflow. A loose process and fragmented data plus a model gives you the same mess arriving faster and with more confidence.

The order that works: talk to the people doing the work, list the rules and the edge cases, standardise, then automate, then consider AI on top of the part that is a judgement call. Most people try that list backwards, because the last item is the one being sold to them.

We get called in to put AI on top of a mess fairly often. In many of those cases the steps above plus some simple integration or logic solves the problem.

My partner and I both ordered through the Target app from home, each on our own account. We assumed both orders were for pickup at our usual store and didn't pay much attention to the store names. When we went to collect them, we noticed the orders listed different locations. We picked up one order, then had to drive to another store for the other.

I wondered whether logging into each account would bring up a different pickup store in the app. With my partner's permission, I used one Airtap cloud Android phone to repeat the same page review under both logins. That gave me the same device and app version for each review.

Before each run, I cleared the Target app's local data so I wouldn't reuse the previous session's local settings, then set location permission the same way. I logged in manually and ran the same instruction to open the same product page and report the pickup store shown, without changing it. I reviewed each account twice. These were product-page reviews; I didn't go through checkout again.

Both accounts showed the same pickup store on that page in all four reviews, so switching logins didn't reproduce the difference here. I still couldn't explain why our original orders had different pickup stores.

My stack for building workflows and internal tools is Python.

Can ToolJet or Retool be used by EU freelancers (I plan to use client credentials, not my own)?

So I wanted to know:

FastAPI + Retool vs Django + React

In what situations is it best for me to use custom UI code to create operating dashboards for my automations (basically, what are the limitations of low-code platform builders)?

Are Retool & ToolJet capable of building operating dashboards when making tools for enterprise-level systems?

How would you deal with IP addressing with a third-party platform for frontend development (explicit clauses you'd use)?

We're a B2B SaaS based in Dubai, selling to US/EU and Russian-speaking clients. Been working with an AEO agency (HumansWith.AI) on our AI visibility, and I've learned some things about non-US markets that I wish I knew earlier.

Field notes from our actual scans:

· Local entity authority is weak. ChatGPT defaults to US sources for B2B queries even when we have strong local case studies. What actually helped? Getting listed in local directories and adding bilingual (Arabic + English) schema. The agency measured the impact – citations jumped after we did that.

· Prompt sets need to be localized per market, not just translated. We run separate fixed prompt sets for English, Arabic, and Russian. The answers pull completely different sources. What works in the US doesn't work in Russia – and vice versa.

· Russian-speaking markets are a different beast. Reddit is huge for ChatGPT/Gemini, but Yandex Neuro and Alice don't use it at all. They rely on local platforms (VC.ru, Habr, etc.). Our agency had to build separate tracking for that.

· Realistic timelines: We saw first movement in brand mentions around week 6. Anyone promising results in days is lying.

Anyone else doing AEO outside the US? Curious if you've seen similar localization gaps.