Summarizer

You're not going crazy. That is what I see as well. But, I do think there is value in: - driving the LLM instead of doing it yourself. - sometimes I just can't get the activation energy and the LLM is always ready to go so it gives me a kickstart - doing things you normally don't know. I learned a lot of command like tools and trucks by seeing what Claude does. Doing short scripts for stuff is super useful. Of course, the catch here is if you don't know stuff you can't drive it very well. So you need to use the things in isolation. - exploring alternative solutions. Stuff that by definition you don't know. Of course, some will not work, but it widens your horizon - exploring unfamiliar codebases. It can ingest huge amounts of data so exploration will be faster. (But less comprehensive than if you do it yourself fully) - maintaining change consistency. This I think it's just better than humans. If you have stuff you need to change at 2 or 3 places, you will probably forget. LLM's are better at keeping consistency at details (but not at big picture stuff, interestingly.)

For me the biggest benefit from using LLMs is that I feel way more motivated to try new tools because I don't have to worry about the initial setup. I'd previously encountered tools that seemed interesting, but as soon as I tried getting it to run I found myself going down an infinite debugging hole. With an LLM I can usually explain my system's constraints and the best models will give me a working setup from which I can begin iterating. The funny part is that most of these tools are usually AI related in some way, but getting a functional environment often felt impossible unless you had really modern hardware.

Same. This weekend, I built a Flutter app and a Wails app just to compare the two. Would have never done either on my own due to the up front boilerplate— and not knowing (nor really wishing to know) Dart.

I did the same thing but with react and supabase. I wouldn’t have done this on my own because of the react drudgery.

I tend to be surprised in the variance of reported experiences with agentic flows like Claude Code and Codex CLI. It's possible some of it is due to codebase size or tech stack, but I really think there might be more of a human learning curve going on here than a lot of people want to admit. I think I am firmly in the average of people who are getting decent use out of these tools. I'm not writing specialized tools to create agents of agents with incredibly detailed instructions on how each should act. I haven't even gotten around to installing a Playwright mcp (probably my next step). But I've: - created project directories with soft links to several of my employer's repos, and been able to answer several cross-project and cross-team questions within minutes, that normally would have required "Spike/Disco" Jira tickets for teams to investigate - interviewed codebases along with product requirements to come up with very detailed Jira AC, and then,.. just for the heck of it, had the agent then use that AC to implement the actual PR. My team still code-reviewed it but agreed it saved time - in side projects, have shipped several really valuable (to me) features that would have been too hard to consider otherwise, like... generating pdf book manuscripts for my branching-fiction creating writing club, and launching a whole new website that has been mired in a half-done state for years Really my only tricks are the basics: AGENTS.md, brainstorm with the agent, continually ask it to write markdown specs for any cohesive idea, and then pick one at a time to implement in commit-sized or PR-sized chunks. GPT-5.2 xhigh is a marvel at this stuff. My codebases are scala, pekko, typescript/react, and lilypond - yeah, the best models even understand lilypond now so I can give it a leadsheet and have it arrange for me two-hand jazz piano exercises. I generally think that if people can't reach the above level of success at this point in time, they need to think more about how to communicate better with the models. There's a real "you get out of it what you put into it" aspect to using these tools.

I can’t speak for anyone else, but Claude Code has been transformative for me. I can’t say it’s led to shipping “high quality projects”, but it has let me accomplish things I just wouldn’t have had time for previously. I’ve been wanting to develop a plastic -> silicone -> plaster -> clay mold making process for years, but it’s complex and mold making is both art and science. It would have been hundreds of hours before, with maybe 12 hours of Claude code I’m almost there (some nagging issues… maybe another hour). And I had written some home automation stuff back with Python 2.x a decade ago; it was never worth the time to refamiliarize myself with in order to update, which led to periodic annoyances. 20 minutes, and it’s updated to all the latest Python 3.x and modern modules. For me at least, the difference between weeks and days, days and hours, and hours and minutes has allowed me to do things I just couldn’t justify investing time in before. Which makes me happy! So maybe some folks are “pretending”, or maybe the benefits just aren’t where you’re expecting to see them?

That’s where it really shines. I have a backlog of small projects (-1-2kLOC type state machines , sensors, loggers) and instead of spending 2-3 days I can usually knock them out in half a day. So they get done. On these projects, it is an infinity improvement because I simply wouldn’t have done them, unable to justify the cost. But on bigger stuff, it bogs down and sometimes I feel like I’m going nowhere. But it gets done eventually, and I have better structured, better documented code. Not because it would be better structured and documented if I left it to its ow devices, but rather it is the best way to get performance out of LLM assistance in code. The difference now is twofold: First, things like documentation are now -effortless-. Second, the good advice you learned about meticulously writing maintainable code no longer slows you down, now it speeds you up.

You may just be more knowledgeable than me. For me, even getting to algorithmic creation of 4-6 part molds, plus alternating negatives / positives in the different mediums, was insurmountable. I’m willing to believe that I’m just especially clueless and this is not a meaningful project to an expert. But hey, I’m printing plastic negatives to make silicone positives to make plaster negatives to slip cast, which is what I actually do care about.

It might be role-specific. I'm a solutions engineer. A large portion of my time is spent making demos for customers. LLMs have been a game-changer for me, because not only can I spit out _more_ demos, but I can handle more edge cases in demos that people run into. E.g. for example, someone wrote in asking how to use our REST API with Python. I KNOW a common issue people run into is they forget to handle rate limits, but I also know more JavaScript than Python and have limited time, so before I'd write: ``` # NOTE: Make sure to handle the rate limit! This is just an example. See example.com/docs/javascript/rate-limit-example for a js example doing this. ``` Unsurprisingly, more than half of customers would just ignore the comment, forget to handle the rate limit, and then write in a few months later. With Claude, I just write "Create a customer demo in Python that handles rate limits. Use example.com/docs/javascript/rate-limit-example as a reference," and it gets me 95% of the way there. There are probably 100 other small examples like this where I had the "vibe" to know where the customer might trip over, but not the time to plug up all the little documentation example holes myself. Ideally, yes, hiring a full-time person to handle plugging up these holes would be great, but if you're resource constrained paying Anthropic for tokens is a much faster/cheaper solution in the short term.

I find these agents incredibly useful for eliminating time spent on writing utility scripts for data analysis or data transformation. But... I like coding, getting relegated to being a manager 100%? Sounds like a prison to me not freedom. That they are so good at the things I like to do the least and still terrible at the things at which I excel. That's just gravy. But I guess this is in line with how most engineers transition to management sometime in their 30s.

I'm curious what types of tasks you were delegating to the coding agents?

Completely agree. However I do get some productivity boost by using ChatGPT as an improved Google search able to customize the answer to what I need.

The crazy pills you are taking is that thinking people have anything to prove to you. The C compiler that Anthropic created or whatever verb your want to use should prove that Claude is capable of doing reasonably complex level of making software. The problem is people have egos, myself included. Not in the inflated sense, but in the "I built a thing a now the Internet is shitting on me and I feel bad" sense. There's fundcli and nitpick on my GitHub that I created using Claude. fundcli looks at your shell history and suggests places to donate to, to support open source software you actually use. Nitpick is a TUI HN client. I've shipped others. The obvious retort is that those two things aren't "real" software; they're not complex, they're not making me any money. In fact, fundcli is costing me piles of money! As much as I can give it! I don't need anyone to tell me that or shit on the stuff I'm building. The "open secret" is that shipping stuff is hard. Who hasn't bought a domain name for a side project that didn't go anywhere. If there's anybody out there, raise your hand! So there's another filtering effect. The crazy pills are thinking that HN is in any way representative of anything about what's going on in our broader society. Those projects are out there, why do you assume you'll be told about it? That someone's going to write an exposé/blog post on themselves about how they had AI build a thing and now they're raking in the dollars and oh, buy my course on learning how to vibecode? The people selling those courses aren't the ones shipping software!

If people make extraordinary claims, I expect extraordinary proofs… Also, there is nothing complex in a C compiler. As students we built these things as toy projects at uni, without any knowledge of software development practices. Yet, to bring an example for something that's more than a toy project: 1 person coded this video editor with AI help: https://github.com/Sportinger/MasterSelects

> My guess is that the drive is toward power Not really for me. Programming is an effort type job. The more effort you put in the more you get out. True in other professions sure but multiplied with dev work. When became a dad everything changed. Solve hard problem or spend time with kid. I couldn't juggle the two. So i made a choice and fortunately had an opportunity to move into management. Anyway full circle now I'm back to being a dev and this go around couldn't be easier with our ai agents. Point is I went into management because I was forced, not at all for power.

Some people want the thing done more than they want to do the thing. That gets to extremes of exploitative parasitic behavior, but it's true at much less obnoxious scales: ever used a programming language's standard library instead of inventing your own _whatever_? Probably a yes. That can extend to arbitrary absurdity. You are probably not growing your own food, mining your own ore, forging your own tools, etc etc etc. It's all just a matter of where you rely on external tools/abstractions to do parts of the work you don't want to do yourself.

I used to be so deeply annoyed with leadership decisions as an IC. When I got into management my attitude completely shifted. Leadership only cares about shipping code. Thinking they care about anything else and you're fooling yourself. So whatever your team cares about your decisions doesn't matter. Are they shipping code? All good. Team dynamics will work itself out as long as you're pushing to main. Now I'm back to being an IC and I just do the job. Want me to change this variable name so its more readable, in your opinion? No problem. I shall change const foo to const bar.

>the joy of problem solving It's frontier exploration that brings me joy. If a clanker can do something, then it's a solved problem. I use all the tools at my disposal to push the frontier of problems solved. Wasting my time re-inventing the wheel brings me the opposite of joy.

i like the aspect of engineering that's building useful or interesting or fun things for people, and i'll always experiment with new tech that facilitates that

For many people, code is just a means to an end to solve problems and build. The joy from solving problems doesn't disappear. Would you use traditional (not WebAssembly) assembly to build a web application? Probably not. LLMs make a lot more sense if you think of it as a tool to translate requirements into solutions.

You just have another agent/session/context refactor as you go. I built a skribbl.io clone to use at work. We like to play eod on Friday as a happy hour and when we would play skribbl.io we would try to get screencaps of the stupid images we were drawing but sometimes we would forget. So I said I'd use claude to build our own skribbl.io that would save the images. I was definitely surprised that claude threaded the needle on the task pretty easily, pretty much single shot. Then I continued adding features until I had near parity. Then I added the replay feature. After all that I looked at the codebase... pretty much a single big file. It worked though, so we played it for the time being. I wanted to fix some bugs and add more features, so I checked out a branch and had an agent refactor first. I'd have a couple context/sessions open and I'd one just review, the other refactored, and sometimes I'd throw a third context/session in there that would just write and run tests. The LLM will build things poorly if you let it, but it's easy to prompt it another way and even if you fail that and back yourself into a corner, it's easy to get the agents to refactor. It's just like writing tests, the llms are great at writing shitty useless tests, but you can be specific with your prompt and in addition use another agent/context/session to review and find shitty tests and tell you why they're shitty or look for missing tests, basically keep doing a review, then feed the review into the agent writing the tests.

Here’s mine https://apps.apple.com/us/app/snortfolio/id6755617457 30kloc client and server combined. I built this as an experiment in building an app without reading any of the code. Even ops is done by claude code. It has some minor bugs but I’ve been using it for months and it gets the job done. It would not have existed at all if I had to write it by hand.

I am an old school c++ programmer and actually I have learned modern c++ just by using LLMs.

AI is great, harness don't matter (I just use codex). Use state of the art models. GPT-5.2 fixed my hanging WiFi driver: https://gist.github.com/lostmsu/a0cdd213676223fc7669726b3a24...

It is if it's something they couldn't do on their own before. It's a magical moment when someone is able to AI code a solution to a problem that they couldn't fix on their own before. It doesn't matter whether there are other people who could have fixed this without AI tools, what matters is they were able to get it fixed, and they didn't have to just accept it was broken until someone else fixed it.

Right!? It's like me all the sudden being able to fix my car's engine. I mean, sure, there are mechanics, and it surely isn't rocket science, but I couldn't do it before and now I can!!! A miracle! Cue the folks saying "well you could DIE!!!" Not if I don't fix brakes, etc ...

It was an easy fix for someone who already knows how WiFi drivers work and functions provided to them by Linux kernel. I am not one of these people though. I could have fixed it myself, but it would take a week just to get accustomed to the necessary tools.

That was very vague, but I kinda get where they're coming from. I'm now using pi (the thing openclaw is built on) and within a few days i build a tmux plugin and semaphore plugin^1, and it has automated the way _I_ used to use Claude. The things I disagree with OP is: The usefulness of persistent memory beyond a single line in AGENTS.md "If the user says 'next time' update your AGENTS.md", the use of long-running loops, or the idea that everything can be resolved via chat - might be true for simple projects, but any original work needs me to design the 'right' approach ~5% of the time. That's not a lot, but AI lets you create load-bearing tech-debt within hours, at which point you're stuck with a lot of shit and you dont know how far it got smeared. [1]: https://github.com/offline-ant

My openclaw built skills (python scripts) to interact with the Notion API which allows it to make work items for me and evenly distribute them, setting due dates on my calendar.

My pet peeve with AI is that it just accelerates whatever has already been automated or can be automated easily, but could not touch the bastions of government service, financial service, schools and health services that are way less automated. They keep eating ourselves’ lunch without touching the real problems. For me the pain point has always been with non-IT people/companies. They are way more accustomed with phone or even in person appointments. They in general have way more of a say than me, the customer. Can Openclaw make and take phone calls for me to make appointments? Can Openclaw do chores for me? Can Openclaw meet with contractors for me? None of them it can do. It can make notes for me (useless as most notes are useless). It can scrap websites for me (not very interesting as why would I want to collect so much knowledge?). It can probably automate anything that already has an endpoint or whatever, but I don’t mind write code for my own projects. I always failed to understand why anyone would want to let AI write most of the code of their PERSONAL project — unless they want to sell them quickly. I’m just a frustrated old man I guess.

It can make/take phone calls[0], but they need to be prompted on the nature of the call, the data they need, and how to collect it. They can also output the results of the call via API. An AI agent from Masterworks recently called me using this technology. [0] https://vapi.ai/

> My pet peeve with AI is that it just accelerates whatever has already been automated or can be automated easily .... > I’m just a frustrated old man I guess. I think this is a great summary of the failure of vision that a lot of tech people are having right now. > automate anything that already has an endpoint or whatever Facebook used to have API's, Reddit used to have API's, amazon used to have API's They are gone. Enshitification and dark patterns have taken over. "Hey open claw, cancel service xxx" where XXX is something that is 17 steps and purposely hard to cancel so they keep your money. What's going to happen when your AI tool can go to a website and strip the ad's off and return you just the text? What happens when it can build a customized news feed that looks less like Facebook and more like HN? Aren't we just gaining back function we lost with the death of RSS? Consumers are mad about the hype of AI but the moment that it can cut through the bullshit we keep putting in their way it's going to wreck business MODELS, and the choice will be adapt or die. Start asking your "AI" tools to do all the basic, tedious bullshit tasks that are low risk (you have a ton of them) and if it gets 1/4 of them done your going to free up a ton of your own time.

> You could send it a voice message over discord and say "hey remember that conversation about birds? Send an email to Steve and ask him what he thinks about it" if one of my friends sent me an obviously AI-written email, I think that I would cease to be friends with them...

> “hey remember that conversation about birds? Send an email to Steve and ask him what he thinks about it” Isn’t the “what he thinks about it” part the hardest? Like, that’s what I want to phrase myself - the part of the conversation I’d like to get their opinion on and what exactly my actual request is. Or are people really doing the meme of sending AI text back and forth to each other with none the wiser?

I think in the context of business communication; yeah a lot of people are doing that. Which, to be honest, I don't think it the worst thing ever. Most corporate communication is some basic information padded out with feigned personal interest and rehearsed politeness, so it's hardly a huge loss. For personal communication between friends it would be horrible. Authenticity has to be one of the things I value most about the people I know. Didn't mean to imply from that example that I did or would communicate that way.

You can just hook up Claude Code to a Telegram bot and get basically the same result in 50 lines of code. https://github.com/a-n-d-a-i/ULTRON Well, it's a work in progress, but I have self-upgrading and self-restarting working, and it's already more reliable than Claw ;) I used the Claude Code SDK (Agents SDK) originally, but then realized I can get the same result by just calling `claude -p the_telegram_message` The magic sauce being the --continue flag, of course. Bit less useful otherwise. I haven't figured out how to interrupt it or see what it's doing yet though.

The value of openclaw as I understand it is separate context management per venue (per dm, per channel, per platform, etc) and clever tricks around managing shared memories and state. Well, that and skills to download more skills. It’s a lot faster and easier to extend OC than CC via prompts . It also has cron and other take-initiative features. I had it hack up a poller for new Gitea notifications (for @ mentions and the like) that wakes up the main bot when something happens, so I have it interacting with a self hosted Gitea. There wasn’t even a Gitea skill for it, it just constructs API requests “manually” each time it needs to do something on it. I guess it knows the Gitea API already. It knew how to make a launchd plist and keep the poller running, without me asking it to do that. It’s a little more oriented toward getting things going and running than CC, which mostly just wants to make commits.

I want an OpenClaw that can find and call a carpenter, a plumber when I need him; take appointment for all the medical stuff (I do most of that online), pays the bills and make me a nice alarm when there's something wrong, order train tickets and book hotel when I need to. That would be really helpful.

> find and call a carpenter, a plumber when I need him Good luck hoping that none from the big money would try to stand between you and someone giving you a service (uber, airbnb, etsy, etc) and get rent from that.

I hate receiving competitive quotes so I take what the 1st guy offers or dont engage at all. AI agents could definitely be useful gathering bids where prices are hidden behind "talk to our sales specialist" gates.

I haven't tried OpenClaw, but I gave Claude Code an account on my Forgejo instance. I found issues and PRs to be a very good level of abstraction for interfacing with the new agent teams feature, as well as bringing the "anytime, anywhere, low activation energy" benefits this article talks about. I let it run in a VM on my desktop and I can check on its progress and provide feedback any time. Only took a few iterations of telling it to tweak its workflow to land on something very productive. Doesn't work for everything but it covers a lot of my work.

I am currently in the process of setting up a local development environment to automate all my programming tasks (dev, test, qa, deploy, debug, etc; for android, ios, mac, windows, linux). It's a serious amount of effort, and a lot of complexity! I could probably move faster if I used AI to set it all up for me rather than setting it up myself. But there's significant danger there in letting an AI "do whatever it wants" on my machine that I'm not willing to accept yet, so the cost of safety is slowness in getting my environment finished. I feel like there's this "secret" hiding behind all these AI tools, that actually it's all very complicated and takes a lot of effort to make work, but the tools we're given hides it all. It's nice that we benefit from its simplicity of use. But hiding complexity leads to unexpected problems, and I'm not sure we've seen any of those yet - other than the massive, gaping security hole.

The post mentions discussing projects with Claude via voice, but it isn't clear exactly how. Do they just mean sending voice memos via Whatsapp, the basic integration that you can get with OpenClaw? (That isn't really "discussing".) Or is this a full blown Eleven Labs conversational setup (or Parakeet, Voxtral, or whatever people are using?) I'm not running OpenClaw, but I've given Claude its own email address and built a polling loop to check email & wake Claude up when I've sent it something. I'm finding a huge improvement from that. Working via email seems to change the Claude dynamic, it feels more like collaborating with a co-worker or freelancer. I can email Claude when I'm out of the house and away from my computer, and it has locked down access to use various tools so it can build some things in reply to my emails. I've been looking into building out voice memos or an Eleven Labs setup as well, so I can talk to Claude while I'm out exercising, washing dishes etc. Voice memos will be relatively easy but I haven't yet got my head around how to integrate Eleven Labs and work with my local data & tools (I don't want a Claude that's running on Eleven Labs servers).

Openclaw is just that, it wakes on send and as cronjobs and get to work. What made it so popular I think is that it made it easy to attach it to whatever "channel" you're comfortable with. The mac app comes with dictation, but unsure the amount of setup to get tts back.

>I used to have way too many ideas but no way to build them all on my own—they just kept piling up. But now, everything is different. This has been a significant aspect of ai use as well. As a result a feel a little less friction with myself, less that I am letting things slip by because, well, because I still want a nice balance to work, life, leisure, etc. I don’t want to overstate things, it’s not a cure all for any of these things, but it helps a lot.

everything I see people do with openclaw is less like LLM work and more like 'Yahoo! Pipes' work. I haven't been able to find a good use for myself yet. Almost everything I use an LLM for has some kind of hard human-in-the-loop factor that is as of yet inescapable -- but I also don't really use LLMs for things like "sort my email.". mostly entirely coding.

Hah, I read that as well and made a big "hmmmmmmmmm" sound... The last time I talked to someone about OpenClaw and how it is helping them, they told me it tells them what their calendar has for them today or auto-tweets for them (i.e., non-human spam). The first is as simple as checking your calendar, and the second is blatant spam. Anyone found some good use cases beyond a better interface for AI code assistance?

A dev on my team was trying to get us to setup OpenClaw, harping on about how it would make our lives easier etc, etc. (even though most of the team was against the idea due to the security issues and just not thinking it would be worth it). Their example use case was for it to read and summarize our Slack alerts channel to let us know if we had any issues by tagging people directly... the Slack channel is populated by our monitoring tools that also page the on-call dev for the week. The kicker... this guy was the on-call dev that week and had just been ignoring the Slack channel, emails and notifications he was getting!

> how it is helping them This should be the opening for every post about the various "innovations" in the space. Preferably with a subsequent line about the manual process that was worth putting the extra effort into prior to the shiny new thing . I really can imagine a better UX then opening my calendar in one-click and manual scanning. Another frequent theme is "tell me the weather." One again, Google home (alexa or whatever) handles it while I'm still in bed and let's me go longer without staring at a screen. The spam use-case is probably the best use-case I've seen, as in it truly saves time for an equal or better result, but that means being cool with being a spammer.

This is a pretty simple thing to boil the ocean over but it was fun nonetheless. I've been applying for jobs but I don't want Gmail notifications on my phone because of all the spam, I'm really picky about push notifications. I told my openclaw adjacent ai bot to keep an eye and let me know if any of the companies I applied to send me an email. Worked great. CEO LARPing at its finest. Also a big fan of giving it access to my entire obsidian vault so if I'm on the go instead of trying to use obsidian on the phone I just tell it what I need to read or update. I'm not running openclaw itself. I am building a simpler version that I trust and understand a lot more but ostensibly it's just another always on Claude code wrapper.

Not via OpenClaw, but I automate breakdowns of my analytics and I recently started getting digests of social media conversations relevant to my interests. It's also good for monitoring services and doing first line triage on issues.

Everybody here probably already has an opinion about the utility of coding agents, and having it manage your calendar isn't terribly inspired, but there is a lot more you can do. To be specific, for the past year I've been having numerous long conversations about all the books I've read. I talk about what I liked, didn't like, the ideas and and plots I found compelling or lame, talks about the characters, the writing styles of authors, the contemporary social context the authors might have been addressing, etc. Every aspect of the books I can think off. Then I ask it for recommendations, I tell it given my interests and preferences, suggest new books with literary merit. ChatGPT just knocks this out of the park, amazing suggestions every time, I've never had so much fun reading than in the past year. It's like having the world's best read and most patient librarian at your personal disposal.

> Anyone found some good use cases beyond a better interface for AI code assistance Well... no. But I do really like it. It's just an always-on Claude you can chat with in Telegram, that tries to keep context, that has access to a ton of stuff, and it can schedule wakeup times for itself.

> Anyone found some good use cases beyond a better interface for AI code assistance? Yesterday, I saw a demo of a product similar to OpenClaw. It can organize your files and directories and works really great (until it doesn't, of course). But don't worry, you surely have a backup and need to test the restore function anyway. /s Edit: So far, I haven’t found a practical use case for this. To become truly useful, it would need access to certain resources or data that I’m not comfortable sharing with it.

No, he seemed pretty certain about how they demoed it. We're allowed to have opinions about promises that turn out not to be true. If the rabbit had been what it claimed it would be, it would have been an obvious upgrade for me, at least. I just want a voice-first interface.

Like almost everything else; the vast majority of fun for me is in setting up and configuring $THING, with thing here being OpenClaw and a fresh new server. After that I realize I have nothing to do with it and destroy the instance only to create a new one to try out some other self-hosted $THING

This is for people that talk to ChatGPT at length in voice mode. You are not the audience.

been writing code for 15 years now , agree with the author about this one , open-claw like agents are going to be the future. Already automated away a bunch of routine stuff like checkin FB marketplace if l’m looking to but something , daily stock position brief , calendar management , grocery planning and buying , workout and calorie tracking . Stopped using a bunch of app directly overnight . The “mid-wits” are the one with their head still stuck under that sand

Yes claude + scripts without any big corp restrictions / bloat , if i want to connect to a website or api i can just do it. If you expose it to me as a human it is fair game for my assistant to read data the same way i do. Its like the old days of internet . I build harnesses for a living these days , i see why enterprises are slow to even to see what is possible

Since many posts mention lack of substance, providing a link to the All-In Podcast from last week in which they discuss Clawdbot (prior to re-brand). https://www.youtube.com/watch?v=gXY1kx7zlkk&t=2754s For the impatient, here's a transcript summary (from Gemini): The speaker describes creating a "virtual employee" (dubbed a "replicant") running on a local server with unrestricted, authenticated access to a real productivity stack—including Gmail, Notion, Slack, and WhatsApp. Tasked with podcast production, the agent autonomously researched guests, "vibe coded" its own custom CRM to manage data, sent email invitations, and maintained a work log on a shared calendar. The experiment highlights the agent's ability to build its own internal tools to solve problems and interact with humans via email and LinkedIn without being detected as AI. He ultimately concludes that for some roles, OpenClaw can do 90%+ of the work autonomously. Jason controversially mentions buying Macs to run Kimi 2.5 locally so they can save on costs. Others argue that hosting an open model on inference optimized hardware in the cloud is a better option, but doing so requires sharing potentially sensitive data.