How much do you trust AI agents?
With the advent of clawdbots, it's as if we've all lost our inhibitions and "put our lives completely in their hands."
I'm all for delegating work, but not giving them too much personal/sensitive stuff to handle.
I certainly wouldn't trust something to the extent of providing:
access to personal finances and operations (maybe just setting aside an amount I'm willing to lose)
sensitive health and biometric information (can be easily misused)
confidential communication with key people (secret is secret)
Are there any tasks you wouldn't give AI agents or data you wouldn't allow them to access? What would that be?
Re. finances – Yesterday I read this news: Sapiom raises $15M to help AI agents buy their own tech tools – so this may be a new era when funds will go rather to Agents than to founders.
Replies
lead gen. mostly. and automatic replies. can't fully trust with money tho... there's a news here that some Claude bot users bought an entire course just to serve it's master useful information regarding what he's looking for.
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@kilopolki Damn, I would go crazy if it used my money like that. 😂
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@kilopolki This? :D https://www.instagram.com/p/DUL0RCLFEvv/
Isn't Clawd just like Cowork? I've only been mildly impressed with agents. One goal of any founder is to find people to trust their reputation to and let those people grow and make mistakes with your name on the door. Finding the right people is make or break.
Finding an AI agent is kinda the same thing. You're trusting it with your name/brand and resources. So far I can't say I've been impressed beyond entry level. I'd rather find someone who can truly reason and knows how to get AI to do some grunt work.
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@tinyorgtech Yes, but let's say that AI Agent is capable dof oing anything to deliver what you want. And can be like a very proactive idiot who doesn't mind getting it by any means (and that way it is getting related to something you don't like). Here's the example: https://www.instagram.com/p/DUL0RCLFEvv/
@busmark_w_nika I would want to fire that agent. $3000 in training classes. I mean its next predictive response must have sent it there and with payment processing available it goes nuts. Appreciate that user taking a hit for science!
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@tinyorgtech TBH, when it comes to payments, I would require an AI agent to confirm it with me first.
The trust question is really about boundaries and observability. I think about it in tiers:
Tier 1 (full trust): Research, drafting, data analysis, coding assistance - tasks where I can verify outputs before acting on them.
Tier 2 (supervised): Content publishing, email responses, social interactions - tasks where there's a review step or low blast radius if something goes wrong.
Tier 3 (manual only): Financial transactions, legal commitments, anything with compliance implications, direct customer communication without review.
The key is having clear handoffs between autonomous work and human decision points. If you can't articulate exactly what an agent is allowed to do and where it stops, that's a sign you need stronger guardrails.
Has anyone built explicit "stop and ask" checkpoints into their agent workflows? Curious what triggers you've found useful.
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@taylorbrooksops But how you would traing the agent the way that it will not mess up the Tier 3? :)
I couldn’t agree more. AI agents are great for boosting productivity, but I’d never let them handle my finances, sensitive health data, or confidential conversations—trust needs clear boundaries.
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@vivianzheng There is nobody to rely on :D
TinyCommand
AI agents are very strong at analysis-heavy work like forecasting, scenario modeling, and competitive analysis because they can process large datasets faster than humans. The boundary for me is not insight generation but autonomous execution. I am comfortable letting agents crunch data and propose decisions, but a human should own the final call when accountability or second-order effects are involved.
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@priyanka_gosai1 work-related stuff to filtering, analysing – okay, but rather nothing else, right? :)
TinyCommand
@busmark_w_nika mostly work-related stuff. sometimes also personal stuff like expenses.
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@priyanka_gosai1 aaaa, that would be too personal for me :D (no, I am not hiding anything, but such info can also be misused) :D
Building on what others have mentioned, one area I’m still cautious about is confidential human communication. Conversations involving private intent, negotiation, or emotional context—like founder discussions, legal strategy, or sensitive relationship dynamics—feel different from other tasks we delegate. These exchanges aren’t just about transferring information; they’re shaped by timing, framing, subtext, and mutual trust.
On sensitive health and biometric data, I tend to share the hesitation others have expressed. This kind of data is deeply personal and hard to separate from identity itself. Even if current systems are secure and well-intentioned, the long-term risks feel harder to reason about—future re-identification, secondary use, or new forms of inference as models and datasets evolve. Unlike credentials or accounts, this isn’t something you can easily change or revoke once it’s exposed.
So for me, it’s less about never trusting AI in these areas and more about being aware that the downside risks could be asymmetric.
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@joannachris Regarding the first paragraph – did you refer to "access of human behaviour"/Psychology? Or whad did you mean by that?
I wouldn’t grant agents access to irreversible domains: personal finances beyond capped loss, raw biometric data, or confidential human relationships. These aren’t automation problems; they’re alignment and accountability problems.
The Sapiom news is interesting, but also telling: we’re starting to fund agents as economic actors before we’ve solved auditability, intent drift, or liability. Capital flows faster than safety guarantees.
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@akshat_sharma31 and imagine some countries restricting this while others are adapting, evolving... we shouldn't be reactive to this, but proactive :)
I use AI daily for work, but I draw the line at anything that requires actual accountability. If an agent messes up my schedule, it's annoying; if it messes up a bank transfer or a government application, it's a disaster. Until AI can be legally held responsible for its mistakes, my wallet and my ID stay offline.
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@ibrahim_khalil25 True. I wouldn't give access to things that can harm my personal data or time + finances.
I work on agent tooling and the thing nobody talks about is that trust is a spectrum, not a binary. Right now most people either let the agent do whatever or don't use it at all.
What changed my mind was building replay/trace infrastructure — when you can go back and see exactly what an agent did step by step, you stop worrying about whether to trust it. You just check. Same way you'd review a junior dev's PR, not because you don't trust them, but because that's how you build confidence over time.
The actually scary failure mode isn't "agent accesses my bank account." It's 50 small reasonable-looking decisions that compound into something you didn't want.
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@manuel_del_verme But that's usually how it starts. You want one innocent thing, and it can result in a catastrophe. :D I think that first you should know / predict what bad can happen and then say: don't do this... this... this...
Great thread, Nika—trust in increasingly autonomous AI agents is one of the defining questions of the next few years.
My personal boundaries are quite similar to yours:
Hard no-go zones (no access, no exceptions):
Full control over personal banking, crypto wallets, or payment methods (only ever a capped “burner” amount I’m willing to lose)
Direct access to health records, genetic data, continuous biometrics, or medical history
Any end-to-end encrypted or highly confidential communication (family, legal, therapy, C-level business secrets)
Actions with real-world legal, financial, or physical consequences (signing contracts, posting publicly on my behalf, controlling smart home/security devices)
What I do delegate today (with monitoring):
Read-only analysis of finances (categorization, forecasting, anomaly detection)
Email triage, drafting low-stakes replies, meeting prep & follow-ups
Research, summarization, task triaging, calendar suggestions
Code generation/review in isolated environments
The Sapiom news is a fascinating (and slightly dystopian) signal—if agents start managing their own budgets and tooling autonomously, we’re moving toward agent-to-agent economies where human oversight becomes even more critical. That could unlock insane productivity… or create entirely new classes of misalignment risk.
Where do you personally draw the line between “helpful proactive assistant” and “too autonomous to feel safe”? Curious about your take as a minimalist-tool builder. 💭
Upvoted—excellent conversation starter. 🚀
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@64185008aaa We are on the same page when it comes to delegating ;)