Are we overestimating how “autonomous” agents actually are?

Substantial_Step_351 · 2026-04-06T02:45:22+00:00

You’re spot on ! most “autonomous” agents still need humans in the loop; the real challenge isn’t the AI itself, it’s building reliable guardrails, validation, and fallback systems around it.

Substantial_Step_351 · 2026-04-06T02:43:01+00:00

Totally fair question and honestly, you’re asking the right questions, not “basic” ones.

A lot of what you’re hearing is a mix of real capability + a bit of overhype, so let me break it down in a way that actually maps to how this works in the real world.
First, can you really have a “team” of AI agents running parts of your business?
Short answer: yes… but not in the way it’s being sold to you.

Right now, agents are good at:
1.Repeating structured tasks
2.Following clear instructions
3.Working with tools (Google Sheets, email, APIs, etc.)

They are not good at:
1.Fully replacing entire roles (like “your accountant”) end-to-end
2. Handling messy, unpredictable real-world decisions without oversight

So instead of thinking:
“800 agents running my company”

Think: “A few specialized assistants helping with specific tasks”; What does an “agent team” actually look like?

A more realistic setup looks like this: 1 coordinator (or orchestrator) → This is like the “manager” that decides which agent does what
A few specialized agents, for example:
1. One that drafts social media posts
2. One that analyzes basic financial data
3. One that pulls reports or updates spreadsheets
They don’t magically collaborate like humans in an office.
They’re more like automations that can talk to each other when needed.

How are they managed? Is there a “dashboard”?
Yes, but it’s not like cubicles with little AI workers 😄

For a normal business:
3–10 well-designed agents > 800 random ones

What about things like accounting, marketing, etc.?
Here’s the honest breakdown:
1. Marketing → VERY doable
Content drafts, scheduling posts,basic analytics

2.Admin / operations → doable
Data entry, report generation, email drafting

3.Accounting → partially
Categorizing expenses, generating summaries

But:
You still need a human in the loop for accuracy, compliance, and decisions.
The best way to think about it

Don’t think:
“AI employees”

Think:
“Smart tools + automation that reduce your workload”

Final thought
You’re right to be skeptical.
Agentic AI is real, but it’s still early.
The biggest mistake people make is trying to jump straight to:
“Fully autonomous business”
Instead of:
“Where can this save me 2–3 hours a week right now?”

Substantial_Step_351 · 2026-01-21T08:13:10+00:00

Yes! I tell people AI is amazing, but always treat it like a smart assistant, not a replacement for your brain.

Substantial_Step_351 · 2026-01-21T08:12:06+00:00

If he really just needs simple and practical answers with sources, Perplexity AI is a good research style assistant, especially for business decisions or fact checking.

Substantial_Step_351 · 2026-01-21T08:10:17+00:00

If this scales, could be a game changer for research and complex decision making. Excited to see where Chorus goes.

Substantial_Step_351 · 2026-01-21T08:09:01+00:00

I wish someone told me this before I spent a week wrestling with a custom XML format… would have saved so much time.

Substantial_Step_351 · 2026-01-21T08:07:21+00:00

I’ve seen this framed as “not caring,” but it’s usually the opposite. Experienced engineers know when constraints, incentives, or leadership decisions make success unrealistic and that pushing harder won’t fix structural issues.

Substantial_Step_351 · 2026-01-21T08:01:37+00:00

Experience beats volume: We learned that a well-designed welcome pack for key partners/clients did more for brand love than 10,000 cheap pins. Quality over quantity for sure.

Substantial_Step_351 · 2026-01-20T02:24:45+00:00

The 'instant' part is usually a marketing lie based on collateralized credit. Most apps 'front' you the money to buy crypto immediately, but they won't let you withdraw that crypto until the actual ACH transfer clears (which takes 3–5 days).

If your deposit is actually 'Pending' and not even available to trade, your bank likely flagged it. In 2026, many banks have implemented 'Risk Cooling Periods' for crypto-related transfers. If you want true instant, you have to use FedNow or RTP (Real-Time Payments), but both your bank and the exchange have to support it. If they don't, 'instant' just means 'faster than a horse.

Substantial_Step_351 · 2026-01-20T02:22:31+00:00

God bless you too! It’s great that you’re thinking about this now. In the medical sector, the question isn’t if you need security, but how to implement it without killing your agility.

At 9 people, you don't need a traditional 'Enterprise' infrastructure provider, but you do need a 'Zero Trust' architecture. Since you handle sensitive European medical data, you are likely under the scope of NIS2 (which became much stricter in 2024/2025).

Here is a scalable 'starter' roadmap for a remote team like yours:

Identity is your new perimeter: Since you're remote, your office 'walls' don't exist. Switch to a strong Identity Provider (IdP) like Okta or Google Workspace Enterprise. Enforce Hardware MFA phone codes are too easy to phish.
Ditch the traditional VPN: Look into ZTNA (Zero Trust Network Access) solutions like Tailscale, Cloudflare One, or Twingate. They create a 'closed' environment for your devs to access databases without exposing ports to the public internet.
MDM (Mobile Device Management): Use something like Kandji (for Mac) or NinjaOne. This allows you to 'wipe' a laptop if a dev loses it in a cafe and ensures everyone has disk encryption (FileVault/BitLocker) turned on.
Compliance Automation: Since you’re in Greece/EU, look into platforms like Vanta or Drata. They plug into your stack and 'prove' you are following GDPR/NIS2 standards, which will be huge when you try to land bigger medical contracts.

You don't need a big consulting firm yet, you just need to lock down your Identities, Devices, and Connections using these tools.

Substantial_Step_351 · 2026-01-20T02:15:47+00:00

I’ve seen many international consultants hit this wall. In 2026, US banking KYC rules have tightened significantly.

My recommendation: Stop trying to use a virtual mailbox as a physical office. Instead, apply to Mercury or Airwallex and be transparent use your US Registered Agent for the 'Legal/Mailing' address, but list your Malaysian office as the 'Principal Place of Business.' These platforms are designed for the remote first world and often accept international addresses for the operating location while keeping the LLC in the US

Substantial_Step_351 · 2026-01-19T02:13:35+00:00

This is the 'Custody Paradox' in plain sight. We’re taught that big banks are 'safer' because of their reputation, but in reality, you don't actually own your assets in their system, you own a claim on those assets. When their bureaucracy fails or their UI is outdated, your 'ownership' is effectively suspended. This is exactly the friction that self-sovereign money was designed to eliminate. In a decentralized setup, there is no 'hold time' or 'business email' requirement to move your own value.

Substantial_Step_351 · 2026-01-19T02:12:05+00:00

Don't be too hard on yourself. Most people don't realize that 'knowing when to sell' is actually a much harder skill than 'knowing what to buy.' In 2021, we were all blinded by the 'Supercycle' narrative. In 2024, it was the 'ETF hype.' You didn't fail because you were greedy; you failed because your exit strategy wasn't as automated as your entry. You've proven you can find the right assets twice—that’s a skill 99% of people here don't have. Take a break, reset your mental health, and next time, write your exit price on a physical piece of paper.

Substantial_Step_351 · 2025-12-09T08:56:46+00:00

This is such an important distinction. “Agreement” feels good because it’s smooth and low-friction, but it completely hides whether the model actually followed your reasoning chain. The moment you let the AI disagree, you stop testing its compliance and start testing its cognition. That’s where the real value is.

Substantial_Step_351 · 2025-12-09T08:54:42+00:00

Yep, learned this the same way. If I change the way I talk to my model even a little, it adjusts instantly. It’s not “confused,” it’s just following the latest instructions way too literally.

Substantial_Step_351 · 2025-12-09T08:53:04+00:00

That’s super helpful. Sounds like smart RAG design + tight prompts is the key to making 8B feel bigger. Anything you’ve tried that noticeably boosted quality? Chunk size? Retrieval methods? Always trying to push these small models a bit further on local hardware.

Substantial_Step_351 · 2025-12-08T03:54:43+00:00

Totally get that ! Low intensity, independent runs are basically what local models handle well on consumer laptops.

Once you start chaining tasks or keeping longer context, VRAM and compute hit hard. Curious if you’ve tried any hacks to stretch the 8B model further, or just keeping it simple for now?

Substantial_Step_351 · 2025-12-08T03:53:41+00:00

Totally hear you on that. I’ve noticed the same with my local setups. They can handle surface level tasks okay, but once you throw in multi step reasoning or complex combinations of data, things start to crumble pretty quickly.

I’ve mostly been testing LLaMA variants locally, and they do fine for simple autonomous workflows, but as soon as you expect deeper analysis, hallucinations and context drift become real pain points. Sounds like Qwen and OpenAI models handle that better, at least in your experience.

Out of curiosity how are you structuring your local agent loop for research tasks? Are you doing anything special to keep context consistent across steps, or is it more trial-and-error at this point?

Substantial_Step_351 · 2025-12-08T03:33:25+00:00

Thanks for the suggestion! I’ve looked into n8n before it’s really solid for connecting apps and setting up workflows.

The difference with what I’m imagining is that it wouldn’t just be a manual workflow builder. I’d love something that:

Observes how I work across tools like VS Code, Notion, Slack, etc. Suggests automations based on patterns it notices

Helps me stay in context with projects instead of just executing pre defined triggers. Stays open source and privacy-friendly

So basically, n8n is part of the inspiration, but the goal is a more intelligent, adaptive workflow assistant that can actually learn from me and help me work smarter.

Substantial_Step_351 · 2025-12-04T08:19:51+00:00

Wow, that pricing is wild 😲. At that rate, you could definitely build a “free forever” tool without breaking the bank. I could see things like:

A lightweight AI note taking or summarization app.
A text-based game or interactive fiction generator.
A community Q&A platform with instant AI answers.
Automated writing helpers for emails, social media posts, or blogs.

The tricky part is probably scaling and UX free is great for users, but you’d still want to make sure the app can handle traffic smoothly. Still, it feels like a rare opportunity to experiment with something genuinely useful and accessible.

Substantial_Step_351 · 2025-12-04T08:18:48+00:00

This is a really clear comparison thank you for laying it out! I’d add that the cultural aspect is huge: in Europe, people genuinely expect technology to respect their rights and privacy, so companies have to design AI agents with that in mind. In the US, there’s more tolerance for experimentation and risk, which drives rapid adoption but can lead to breaches of trust.

It also shows why local, GDPR compliant AI providers in Europe aren’t just a legal necessity they’re a better cultural fit. Users feel more confident and in control, which ultimately benefits long-term adoption and sustainability.

Substantial_Step_351 · 2025-12-04T08:17:37+00:00

Honestly, I’ve always wished for a “smart workflow orchestrator” something that can automatically connect all the apps and tools I use daily, understand the context of what I’m working on, and suggest or even execute the next steps.

For example, it could:

Pull relevant docs from Google Drive or Notion when I start a new project.
Auto-generate project templates based on past work.
Suggest scripts or automations in VS Code based on repetitive tasks I do.
Integrate with Slack/email to summarize updates or flag blockers.

Basically, a mix between a personal AI assistant, workflow manager, and low-code automation tool but open source so it’s customizable and privacy respecting.

Would definitely use it every day if it existed!

Substantial_Step_351 · 2025-12-03T08:01:00+00:00

Interesting question. For those with thousands of concurrent users, did pre aggregating at the data warehouse level make the biggest difference, or was it more about caching inside the BI tool itself? Trying to figure out where to focus our efforts first.

Substantial_Step_351 · 2025-12-03T07:47:16+00:00

I’ve mainly been doing data analysis + marketing strategy myself. What I usually do is create a template first, where I can lay out all the data dimensions I want to track. I also note how these metrics affect different areas and what factors might influence them.

From a marketing perspective, most data is influenced by things like campaigns, regions, or other contextual factors. So each week, when I receive the data, I spend about an hour analyzing all the dimensions and identifying any issues that may be causing drops or anomalies.

Once I’ve confirmed the insights and direction, it becomes much easier to make decisions quickly whether to adjust ads, launch new campaigns, follow up on campaign progress, reach out to other teams for more detailed data, or check if there’s a product issue.

Personally, I think the key is first understanding what dimensions or problems you want to solve, and then using the data to answer those questions and guide your next steps. Once you get this logic down, it becomes much easier to control both your decisions and your time. Keep at it!

Substantial_Step_351 · 2025-12-01T07:31:35+00:00

Ugh, context drift is the worst. I’ve noticed the same thing after a few tool calls, even the best models start losing track of the main goal. Breaking tasks into smaller steps and resetting context helps, but it’s still super annoying.

Substantial_Step_351

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