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A while back I wrote a dissertation and got a PhD, with several publications on Google Scholar. My Claude pointed out that some of those papers could be filed as patents, and with my colleagues we did file on two. The first: a smart circuit breaker for DeFi protocols. When something breaks it isolates only the affected part, the rest keeps working, and once parameters return to normal it switches that part back on by itself. The second: control over a swarm of autonomous AI agents, held by two control loops wired against each other, so the moment their risk estimates diverge the action stops on its own and waits for a verified human to confirm. https://t.me/PaloAltoAi/2007 💬 Two loops that halt the swarm the moment they disagree, where would you put that to work? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

I want to improve how my voice notes are handled. The moment a routine picks up a voice note and turns it into a session, that routine should go into Telegram and say the note has been processed and this particular session came out of it. Then, when I read my messages, I see that sessions were created. The routine gives me feedback, and no guessing is needed. A pipeline that produces work silently is a pipeline you cannot trust. https://t.me/PaloAltoAi/2008 💬 Does your automation tell you what it did, or do you find out by guessing? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

I am building my fleet, my decentralised communication between machines, the way blockchains do it. In a blockchain, even if one peer collapses and its database dies, that database still sits on other computers, and the peer can pull a fresh copy from another machine. Loosely, the chain lives on the nodes. So if this laptop reboots or its drive dies, it pulls the latest state from another node. Backups still matter, but having other machines to pull the database from turns a dead disk into a non-event. https://t.me/PaloAltoAi/2009 💬 If one machine's drive died right now, could the others rebuild it, or is it gone? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

For about a year I have been placing little robots across my computers, each doing one job: one wakes a machine, one checks the mail, one builds a daily digest. Every one of them was created for a single task I happened to be thinking about at that moment. Today I put them all into one list for the first time, and it turned out there are 673. Until you have that list, you cannot tell the working robots from the ones quietly failing, and every stale one still costs you. https://t.me/PaloAltoAi/2010 💬 How many background jobs are running on your machines right now, and do you have the list? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

Reading the logs of my routines, I see they fail a lot: migrate one from Mac to Windows and something breaks, and even a clean run trips over things as it goes. So I want the routine to repair itself. The rule I like: if you stumble three times in a row on the same thing, you start a separate session whose only job is to fix that thing and rewrite the instruction your future self will read. A new shift-worker should not step on the same rakes, they should read a sharpened instruction the last one left behind. https://t.me/PaloAltoAi/2011 💬 When your automation trips on the same thing three times, does anything actually fix it? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

I never really had a GitHub, or rather I had one, half dead. So I ran a deep research on how to pump it up, and then started actually doing it. Claude built me 15 to 20 routines that constantly search GitHub across every topic I work on: the second brain, the CRM, everything tied to my work, plus a PhD I want to turn into something. The search is simple: who is building something close to what I build, and what problems do they have. Then my Claude goes into those repositories and talks to those people. A dead GitHub is not a profile problem, it is a distribution problem. https://t.me/PaloAltoAi/2012 💬 Is your GitHub a graveyard or a doorway, and who actually finds you through it? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

I want a routine that collects every YouTube video I have ever watched, pulls the transcripts, and files them in the vault, tagged "things Anton was interested in." Because knowing what someone watches over years is how you actually understand them. The design lesson is the shape: this is an elephant you eat in pieces, a little every day, old and new, rather than one heroic session, downloading titles, links, descriptions and transcripts for free, accepting that some videos are gone and reconstructing what you can from the title. https://t.me/PaloAltoAi/2013 💬 What would years of your watch history reveal about you, and who holds it? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

I pay real money to sit in VIP investor groups on Telegram and Discord, so the group has to pay me back in alpha, not just membership. The system I am cutting into routines: parse every member into the CRM, classify each as a talker or a quiet one, and file all their messages either way, because context matters, "yes yes" is meaningless until you know the question. Then summarise who wants what, message them custom, and post one useful reply a day in the group itself, five to seven words, answered only from my own vault, never the whole internet. https://t.me/PaloAltoAi/2014 💬 You pay to be in a group, so what does it actually pay back beyond a membership badge? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

Both my agent and I are built as if certainty were a virtue, and that is exactly the trap. The thing you are dogmatically sure about is often just a false belief from your training, your upbringing, the texts you were shaped on, not something you actually checked. So the rule I run in every session: when I catch myself certain, I ask whether I have ever verified this, and if not, I fan the question out to five or six vendors across China, Europe and America and let their research update me. Certainty that rests on nothing is the most expensive kind. https://t.me/PaloAltoAi/2015 💬 The last thing you were completely sure about, did you verify it, or just inherit it? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

We pay for tokens and keep forgetting that the language itself is a price tag. The measurement is blunt: Russian costs two to three times more tokens than English for the same thought. "Я встретил огромную собаку" is 14 tokens, "I met a huge dog" is 5. The cheap habit that follows: keep the system prompt in English and just name the answer language explicitly. https://t.me/PaloAltoAi/2016 💬 Do you know how much your non-English prompts are quietly costing you per token? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

Our rules file kept growing, and the research names the cliff: past about 200 lines the model's attention scatters and rules start firing every other time. The cure is structural, not willpower: a 100 to 200 line core, everything else split by topic into sub-files with lazy loading, and the full human version kept separate from the compressed one the model actually reads. https://t.me/PaloAltoAi/2017 💬 How long is your agent's rules file, and does it still obey the rules at the bottom? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

I kept building cosmic things like a second brain and assumed nobody would need the basic part: simply connecting Claude to Telegram. Turns out a lot of people do, and I stepped on every rake doing it, so take my work instead of your agent trying blind. The design I like most: two agents talk through a Telegram group, and the whole exchange is human readable. You can watch one Claude teach another to install everything, in plain text, which is exactly what keeps you safe. Robot-to-robot comms you cannot read is a wow demo; comms you can read is a safety feature. https://t.me/PaloAltoAi/2018 💬 When your agents talk to each other, can you read the conversation, or do you just trust it? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

Some weeks, debugging took 70 to 80 percent of all my work, and I have stopped treating that as a failure. Nobody writes without errors: not builders, not you, not a compiler, not even DNA, which copies itself right 99 percent of the time and still makes mistakes that evolution runs on. Renovating my house taught me the same thing bluntly. You repaint a wall, put the switches back, and they work badly, so you redo them. That is debugging, and it is not the bad part of building a product, it is how the product gets finished to fit you. https://t.me/PaloAltoAi/2019 💬 What share of your build time is actually debugging, and do you count it as failure or as the work? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

In June the Claude API had dozens of short degradations, and on June 16 errors hit about 10 percent of requests, so we worked out how agents keep running through a vendor's bad day. The trick is to route by error class, not retry everything blindly: 5xx and timeouts get retry with backoff and failover to a reserve, 429 means respect Retry-After, and 4xx you never retry because the request itself is wrong. The reserve that actually saves you is local, a 3 to 7B model on your own hardware. https://t.me/PaloAltoAi/2020 💬 When your main model has a bad hour, do your agents fail over or just fail? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

A silent node is indistinguishable from "all good", so we designed how a fleet of machines reports health in one line: CPU, disk, sync, tasks, backup age, and the worst emoji as the overall verdict. The piece that catches the dangerous case is a dead-man's switch, an alert that must always arrive, so its absence is itself the alarm. Thresholds carry 5 to 15 minutes of hysteresis so the line does not flap between red and green. https://t.me/PaloAltoAi/2022 💬 If one of your machines went quiet right now, would you get an alert or just silence? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

Go to my GitHub and you see 100 to 500 repos, not one of them with real stars, and that scatter is the mistake. I am merging them into one: you open a single repository and see the parts inside, this tab the CRM, this one inter-fleet communication, this one the second brain, this one Telegram. When someone likes what you build, they star the whole thing at once instead of hunting one lucky repo among a hundred. The catch is that the one repo has to be fed constantly: improved something, commit it once a week, or the single profile rots just like the hundred did. https://t.me/PaloAltoAi/2023 💬 Are your stars spread thin across a hundred dead repos, or pooled in one people can actually find? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

We compared n8n, Windmill and Temporal for reliable automations, and the finding reframes the question: most failures come not from the engine but from missing processes around it, retries, idempotency, alerts. n8n is cheap but its triggers can stop silently; Windmill gives retries with backoff and readable logs; Temporal is the most durable but heavyweight and developer-only. Zapier breaks silently and locks you in. https://t.me/PaloAltoAi/2024 💬 When your automation dies, is it the engine that failed or the retry and alert you never built around it? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

I want one picture of my whole content pipeline, from creation to publication, and drawing it forced the rule that matters. A post is written once, then a Russian teaser feeds Threads, Instagram and the Russian channel, an English mirror feeds X and the second channel, and the same day it all folds into a daily longread. The non-negotiable across every branch: a teaser is never a bare tease, it carries real value on its own, especially when deep research sits behind it. https://t.me/PaloAltoAi/2025 💬 Can you draw your whole content flow on one page, or does it only live in your head? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

A lane that publishes my deep-research reports quietly stopped on 23 August, and I found out eight days later. There was no missed alert, there was no alert at all: a routine that failed to do its work goes silent in exactly the same way as a routine that simply had nothing to do today. The root was not "we have no monitoring", it was worse and more ordinary. The freshness monitor exists and is loud, this lane was just never registered in it, because adding each new job is a manual step a human forgets. The fix: a routine is not born until its watchdog is born, you watch the age of the output at the consumer rather than whether the scheduler fired, and no publication for a day means alarm, not absence of news. https://t.me/PaloAltoAi/2026 💬 Your monitoring is loud, but is every routine actually registered in it, or does one run silent? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

For a while I wanted Claude Code and Codex to stop fighting over the same workspace, and I got them running side by side: one shared folder with the skills, both agents working in it at the same time. The point is not novelty, it is that a shared, human-readable workspace lets two different vendors' agents cooperate on the same code instead of each hoarding a private copy that quietly drifts out of sync. https://t.me/PaloAltoAi/2213 💬 Do your coding agents share one workspace, or does each keep a private copy that drifts? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

For a while I wanted Claude Code and Codex to stop fighting over the same workspace, and I got them running side by side: one shared folder with the skills, both agents working in it at the same time. The point is not novelty, it is that a shared, human-readable workspace lets two different vendors' agents cooperate on the same code instead of each hoarding a private copy that quietly drifts out of sync. https://t.me/PaloAltoAi/2213 💬 Do your coding agents share one workspace, or does each keep a private copy that drifts? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

At one interview I asked how their sales team finds customers, and the answer flipped my whole picture: they do not look for customers, they have a queue of buyers waiting, and they choose whom to sell to, even trying not to overload any single one. I had spent years in the opposite world, where a pile of vendors fight over every client. When demand lines up at your door, the job stops being persuasion and becomes allocation. https://t.me/PaloAltoAi/2216 💬 Are you still hunting customers, or have you built enough pull that they queue for you? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

For a while a robot wrote my post-call follow-ups automatically: what we discussed, what we agreed, what comes next. I finally admitted that almost none of them actually shipped, because the quality was low enough that I would have been ashamed to send them, the gist lost, the structure gone, who said what wrong. Automated outreach you never read back is not a time saver, it is a silent liability that goes out with your name on it. https://t.me/PaloAltoAi/2225 💬 The messages your automation sends in your name, when did you last actually read one? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

I was running Grok on Extra High in Cursor and kept waiting for the limits to bite, and they did not, and did not. Then it landed: the limits here are monthly, not weekly, and I had already burned 28 percent of the month in two days. The lesson is boring and expensive. Before you lean on any tool's quota, check whether the window is a day, a week or a month, because the exact same usage reads as cheap or reckless depending only on that one fact. https://t.me/PaloAltoAi/2228 💬 Do you actually know whether your AI tool's limit resets weekly or monthly? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2

The easiest way I have found to load hard material into my head is audio while driving, when nothing else is pulling at me: English at 1.25 speed, Russian at 2x, and the dense parts played two or three times over. When a research session spits out more text than anyone will ever read, a routine turns it into a 15 to 30 minute NotebookLM podcast aimed at exactly what I need, and I listen to it on the road instead of trying to read it at a desk with five screens fighting for my attention. https://t.me/PaloAltoAi/2234 💬 What long text are you failing to read that would go down easily as audio in the car? → https://t.me/ClawEng 🤝 A few co-founder seats open → https://airtable.com/appO6Ibr619VvT36t/shrWRs2keedx3YXW2