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you wrote a long careful note so it would remember the thing properly the note is the part that does not load what loads at the start of every session is the index line, the one sentence summary, and only the first two hundred lines of it or the...

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Lagosaur

3,185 subscribers

28,356 次观看 • 3 天前 •via X (Twitter)

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8 条评论

nathan-james 的头像
nathan-james3 天前

あー、そのあるあるすごいわかる！大事な部分が読めないって焦るよね。😅

Britt Ong 的头像
Britt Ong3 天前

Em đây chỉ muốn có Hiệp cạnh bên

Huysolo 的头像
Huysolo3 天前

Context optimization is just an elaborate illusion when system prompts treat detailed notes like unread footnotes

施工現場の拾い物 的头像
施工現場の拾い物2 天前

���のノートの準備、すごく丁寧だね！私もそれくらい工夫してみたいな〜。

sophia f, 的头像
sophia f,3 天前

Facts!

Joey 的头像
Joey3 天前

Plus, who knows what will happen in the futured.

ノブユキ 的头像
ノブユキ3 天前

ノートの部分が読み込まれないと不安になるよね。その間に別の方法で復習するしかないかな…。

佐藤 ��也 的头像
佐藤 ��也3 天前

その長いノート、どんなことが書かれていたのか気になります！記憶の残し方、羨ましいです✨

相关视频

you let the old sessions get cleaned up, they were only taking space the conversations went, the conclusions drawn from them did not transcripts are deleted after the retention period, and the memory directory is excluded from that sweep on purpose, so a note stays until you or the model edits it which means the evidence has an expiry date and the verdict does not on the directory i audited, thirty nine stored conclusions, sixteen of them with no date on the file at all you did not clear anything you deleted the part you could have checked and kept the part that argues the transcript was the receipt the memory is the story about it
0:23

you let the old sessions get cleaned up, they were only taking space the conversations went, the conclusions drawn from them did not transcripts are deleted after the retention period, and the memory directory is excluded from that sweep on purpose, so a note stays until you or the model edits it which means the evidence has an expiry date and the verdict does not on the directory i audited, thirty nine stored conclusions, sixteen of them with no date on the file at all you did not clear anything you deleted the part you could have checked and kept the part that argues the transcript was the receipt the memory is the story about it

Lagosaur

34,053 次观看 • 3 天前

your agent has thirty tools. it calls two of them. the other twenty eight are not sitting idle somewhere. they are in the request, every request, and they are doing damage in two places at once. first the obvious one. tool schemas go into the prompt, and a schema is not a name. it is a description, a parameter list, types, required fields, an example. thirty of those is a few thousand tokens that ship with every single call, including the ones where the agent just says thanks and stops. you are paying rent on twenty eight tools that have never fired. second, and this is the one that costs more. when the request says cancel the order, the model picks by matching against everything available. four of your tools are plausible: cancel_order, refund_order, update_order, void_order. it is choosing among them based on the descriptions you wrote, one afternoon, months ago. every tool you add is another candidate in that shortlist. the twenty eight you never call are not neutral. they are noise in the one decision that determines whether the run works. > why it grows without anyone deciding to nobody adds thirty tools on purpose. you add one for a task, it works, it stays. six months later the registry is a catalogue and no one has ever removed anything, because removing a tool feels risky and adding one feels free. and there is no feedback telling you otherwise. the unused ones never error. they never appear in a failing trace. they are invisible in exactly the way that lets them accumulate. > what to actually do count calls per tool over the last thousand runs. this is one group-by and it usually shocks people. the ones at zero are pure cost. ship the tools the task needs, not the whole registry. a research phase does not need deploy. a writing phase does not need the database. swap the set between phases instead of loading everything up front. same agent, different tools, depending on where the run is. and when two tools could both plausibly answer the same request, that is not redundancy you can ignore. it is a coin flip you built into the system. the twenty eight tools are not unused. they are used every time, by the part of the run you cannot see.
0:52

your agent has thirty tools. it calls two of them. the other twenty eight are not sitting idle somewhere. they are in the request, every request, and they are doing damage in two places at once. first the obvious one. tool schemas go into the prompt, and a schema is not a name. it is a description, a parameter list, types, required fields, an example. thirty of those is a few thousand tokens that ship with every single call, including the ones where the agent just says thanks and stops. you are paying rent on twenty eight tools that have never fired. second, and this is the one that costs more. when the request says cancel the order, the model picks by matching against everything available. four of your tools are plausible: cancel_order, refund_order, update_order, void_order. it is choosing among them based on the descriptions you wrote, one afternoon, months ago. every tool you add is another candidate in that shortlist. the twenty eight you never call are not neutral. they are noise in the one decision that determines whether the run works. > why it grows without anyone deciding to nobody adds thirty tools on purpose. you add one for a task, it works, it stays. six months later the registry is a catalogue and no one has ever removed anything, because removing a tool feels risky and adding one feels free. and there is no feedback telling you otherwise. the unused ones never error. they never appear in a failing trace. they are invisible in exactly the way that lets them accumulate. > what to actually do count calls per tool over the last thousand runs. this is one group-by and it usually shocks people. the ones at zero are pure cost. ship the tools the task needs, not the whole registry. a research phase does not need deploy. a writing phase does not need the database. swap the set between phases instead of loading everything up front. same agent, different tools, depending on where the run is. and when two tools could both plausibly answer the same request, that is not redundancy you can ignore. it is a coin flip you built into the system. the twenty eight tools are not unused. they are used every time, by the part of the run you cannot see.

Hanako

24,656 次观看 • 1 个月前

you installed it with whichever command needed the least typing that command had a scope, and the short one is the widest one user scope does not live in the project, it lives in you, and it loads in every repository you open for the rest of the year a repo you touched once in march is still being told about your database tools i counted mine: four servers, eight thousand nine hundred tokens, riding into projects that have no database and no browser you did not install a tool you set a default for every piece of work you have not started yet the shortest command in the docs and the longest reach
0:43

you installed it with whichever command needed the least typing that command had a scope, and the short one is the widest one user scope does not live in the project, it lives in you, and it loads in every repository you open for the rest of the year a repo you touched once in march is still being told about your database tools i counted mine: four servers, eight thousand nine hundred tokens, riding into projects that have no database and no browser you did not install a tool you set a default for every piece of work you have not started yet the shortest command in the docs and the longest reach

Lagosaur

20,957 次观看 • 6 天前

you wrote a deny rule so it could not touch the thing you cannot undo you were thinking about permission the rule does something stronger than refuse, a bare tool name in deny takes the tool out of the model's context altogether, it is never told the tool exists blocked means it asks and you say no, absent means it never reaches one line removed twenty four playwright tools and four thousand four hundred tokens i had never read you thought you were writing a guard you were writing the menu everything still on it is a choice you left open by not typing
0:50

you wrote a deny rule so it could not touch the thing you cannot undo you were thinking about permission the rule does something stronger than refuse, a bare tool name in deny takes the tool out of the model's context altogether, it is never told the tool exists blocked means it asks and you say no, absent means it never reaches one line removed twenty four playwright tools and four thousand four hundred tokens i had never read you thought you were writing a guard you were writing the menu everything still on it is a choice you left open by not typing

Lagosaur

38,373 次观看 • 6 天前

you trimmed the prompt to get back under the line the prompt was never the part that grows tool results append themselves, they are large, and nobody asks you first, so a session that opened at thirty thousand crosses on turn nine and turn nine is indistinguishable from turn eight until the invoice arrives you cannot trim a conversation you have not had yet what you needed was never a shorter prompt it was one line that checks the number before the request leaves
1:45

you trimmed the prompt to get back under the line the prompt was never the part that grows tool results append themselves, they are large, and nobody asks you first, so a session that opened at thirty thousand crosses on turn nine and turn nine is indistinguishable from turn eight until the invoice arrives you cannot trim a conversation you have not had yet what you needed was never a shorter prompt it was one line that checks the number before the request leaves

Lagosaur

14,047 次观看 • 13 天前

you added an mcp server because it was one line in a terminal and it was one line, that part was true what it was not is one line in the conversation every tool it brought came with a name, a schema and a paragraph of prose, and all of it is re-sent on every request you make until the session ends four ordinary servers on my machine this morning: forty eight definitions, eight thousand nine hundred tokens four and a half percent of a two hundred thousand window, gone before you typed a character you are not the person who installed four tools you are the person who prepends nine thousand tokens to everything he says nobody bills you for it it comes out of the room you had left to think in
1:58

you added an mcp server because it was one line in a terminal and it was one line, that part was true what it was not is one line in the conversation every tool it brought came with a name, a schema and a paragraph of prose, and all of it is re-sent on every request you make until the session ends four ordinary servers on my machine this morning: forty eight definitions, eight thousand nine hundred tokens four and a half percent of a two hundred thousand window, gone before you typed a character you are not the person who installed four tools you are the person who prepends nine thousand tokens to everything he says nobody bills you for it it comes out of the room you had left to think in

Lagosaur

13,488 次观看 • 7 天前

A NASA fellow claims the modern world runs on one equation. Your phone signal, wifi, satellites, this post reaching your screen. All of it obeys one line of math written in the 1860s, before the light bulb existed. His words. The man is Ali Alqaraghuli, a former NASA postdoctoral fellow who now runs two hardware companies. And the way he teaches it is what makes the video worth it. He does not derive the equation. He teaches you to read it. His claim is that school taught you to read math wrong, and one symbol proves it: what you were told is a plus sign is actually something else. Once you see it, the whole equation turns from notation into a sentence. Then he uses that sentence to walk you through how a signal actually gets from your phone to a satellite and back. One viewer called that section straight up magic. It is 4 minutes of it. The comments are the proof. A physics student wrote it explained what a semester with his professor could not. An electrical engineer admitted this is where the equations finally clicked. One person wrote: I cried and I do not even know why. His larger point: the wireless world is not magic and never was. It is one readable line, and reading it is a skill nobody bothered to teach you. One equation. Everything wireless. 14 minutes. It is in the video.
13:56

A NASA fellow claims the modern world runs on one equation. Your phone signal, wifi, satellites, this post reaching your screen. All of it obeys one line of math written in the 1860s, before the light bulb existed. His words. The man is Ali Alqaraghuli, a former NASA postdoctoral fellow who now runs two hardware companies. And the way he teaches it is what makes the video worth it. He does not derive the equation. He teaches you to read it. His claim is that school taught you to read math wrong, and one symbol proves it: what you were told is a plus sign is actually something else. Once you see it, the whole equation turns from notation into a sentence. Then he uses that sentence to walk you through how a signal actually gets from your phone to a satellite and back. One viewer called that section straight up magic. It is 4 minutes of it. The comments are the proof. A physics student wrote it explained what a semester with his professor could not. An electrical engineer admitted this is where the equations finally clicked. One person wrote: I cried and I do not even know why. His larger point: the wireless world is not magic and never was. It is one readable line, and reading it is a skill nobody bothered to teach you. One equation. Everything wireless. 14 minutes. It is in the video.

ooaes

28,543 次观看 • 1 个月前

Agents vs. Graphs, clearly explained! spawning more agents is great, but it has a ceiling nobody says out loud: five agents is a count. a graph is a shape. only one of them changes the answer. point five agents at the same pile with the same window and they converge. the first one writes a finding, the rest read it, and all five reports centre on the same thing. you paid five times for one opinion with four echoes. Graph engineering fixes this by moving the decision up a layer: not how many agents, but who is allowed to look at what. you need both. here's how it works: ↳ the count buys you throughput. five things happening instead of one ↳ the shape buys you coverage. five different things happening instead of the same one five times Prompts → Context → Harness → Agents → Graphs the node that does this is the splitter, and it decides more than any other node in the system. cut a repository by folder and four workers audit the same three files. cut it by blast radius and each one sees something the others cannot. the trick is being selective about what each lane is allowed to see. separate contexts are not a nice-to-have, they are the mechanism. if two agents are meant to produce different things, they must not share a window. if they are meant to produce the same thing, you did not need two agents. one thing to know before you scale it. a branch that throws does not reject the batch. it resolves to null, and that is the containment. which means your merge quietly receives a short list. ↳ filter the nulls before the merge, or one dead lane poisons the whole result ↳ never index a merge by position. eight good branches and one failure will shift everything by one, silently skip that and the run looks like it worked. the output is just missing a lane, and nothing errored. and the one that eats whole nights: multi-agent setups can use up to fifteen times the total tokens of a single chat, because every lane reloads its own core. you are trading total tokens for a clean main window. usually the right trade, always a choice. below i have quoted my full guide on graph engineering. it covers the three topologies, the verifier patterns, and where the gate should actually open. save this and read it below ↓
0:49

Agents vs. Graphs, clearly explained! spawning more agents is great, but it has a ceiling nobody says out loud: five agents is a count. a graph is a shape. only one of them changes the answer. point five agents at the same pile with the same window and they converge. the first one writes a finding, the rest read it, and all five reports centre on the same thing. you paid five times for one opinion with four echoes. Graph engineering fixes this by moving the decision up a layer: not how many agents, but who is allowed to look at what. you need both. here's how it works: ↳ the count buys you throughput. five things happening instead of one ↳ the shape buys you coverage. five different things happening instead of the same one five times Prompts → Context → Harness → Agents → Graphs the node that does this is the splitter, and it decides more than any other node in the system. cut a repository by folder and four workers audit the same three files. cut it by blast radius and each one sees something the others cannot. the trick is being selective about what each lane is allowed to see. separate contexts are not a nice-to-have, they are the mechanism. if two agents are meant to produce different things, they must not share a window. if they are meant to produce the same thing, you did not need two agents. one thing to know before you scale it. a branch that throws does not reject the batch. it resolves to null, and that is the containment. which means your merge quietly receives a short list. ↳ filter the nulls before the merge, or one dead lane poisons the whole result ↳ never index a merge by position. eight good branches and one failure will shift everything by one, silently skip that and the run looks like it worked. the output is just missing a lane, and nothing errored. and the one that eats whole nights: multi-agent setups can use up to fifteen times the total tokens of a single chat, because every lane reloads its own core. you are trading total tokens for a clean main window. usually the right trade, always a choice. below i have quoted my full guide on graph engineering. it covers the three topologies, the verifier patterns, and where the gate should actually open. save this and read it below ↓

Hanako

96,243 次观看 • 18 天前

I fell asleep with the Grok Bot terminal running. 4:07 AM it woke me up 392 filings parsed overnight. 1,703 claims checked. nine survived, not one of them read by me fed it four quant formulas from a paper and one rule about sourcing it built the whole desk the logic: > every claim enters at the outer ring > it has to survive source, date, tie-out, duplicate, cross-check, materiality > anything without a filing behind it dies in the same second > whatever is left gets sized at quarter kelly and lands on my desk this is what Citadel does before every open, except they put thirty analysts on it this is one screen on the terminal right now: 392 filings since midnight, 1,694 claims killed, 9 alive, 14 minutes from filing to parsed, $0.27 an hour, zero humans on the floor the event stream is a wall of deaths killed at source killed at date killed at duplicate killed at materiality every second. new line. new kill the real edge is that first gate. no filing behind the claim and it dies before anything else looks at it that one rule removed the thing everybody complains about with AI. the desk cannot invent a number it is not allowed to ship without a page reference SOURCE 0.62... 0.66... 0.61 nobody told it to tighten. the kill rate moved with what came in overnight 99.5 of every 100 claims never reach me. the nine that do come with a page number attached a Bloomberg seat is thirty thousand a year and would have handed me all 1,703. this desk is two hundred a month everyone is building agents that find more mine is worth what it is because it finds less the whole build is in the article below, save it before your next open
0:54

I fell asleep with the Grok Bot terminal running. 4:07 AM it woke me up 392 filings parsed overnight. 1,703 claims checked. nine survived, not one of them read by me fed it four quant formulas from a paper and one rule about sourcing it built the whole desk the logic: > every claim enters at the outer ring > it has to survive source, date, tie-out, duplicate, cross-check, materiality > anything without a filing behind it dies in the same second > whatever is left gets sized at quarter kelly and lands on my desk this is what Citadel does before every open, except they put thirty analysts on it this is one screen on the terminal right now: 392 filings since midnight, 1,694 claims killed, 9 alive, 14 minutes from filing to parsed, $0.27 an hour, zero humans on the floor the event stream is a wall of deaths killed at source killed at date killed at duplicate killed at materiality every second. new line. new kill the real edge is that first gate. no filing behind the claim and it dies before anything else looks at it that one rule removed the thing everybody complains about with AI. the desk cannot invent a number it is not allowed to ship without a page reference SOURCE 0.62... 0.66... 0.61 nobody told it to tighten. the kill rate moved with what came in overnight 99.5 of every 100 claims never reach me. the nine that do come with a page number attached a Bloomberg seat is thirty thousand a year and would have handed me all 1,703. this desk is two hundred a month everyone is building agents that find more mine is worth what it is because it finds less the whole build is in the article below, save it before your next open

Hanako

17,749 次观看 • 10 天前

you read it and pictured yourself approving instead of watching approving what five agents, each on its own machine, handing work down the line, and what reaches you at the end is the last one's account of the four accounts before it the honest part of that piece says you do not own the harness that is the exact layer where a check on any of this would have to live a hundred and twenty a seat, three hundred at the top, about six times what you pay now you are not buying the work you are buying a shorter story about the work, told by the only party that watched it happen
1:41

you read it and pictured yourself approving instead of watching approving what five agents, each on its own machine, handing work down the line, and what reaches you at the end is the last one's account of the four accounts before it the honest part of that piece says you do not own the harness that is the exact layer where a check on any of this would have to live a hundred and twenty a seat, three hundred at the top, about six times what you pay now you are not buying the work you are buying a shorter story about the work, told by the only party that watched it happen

Lagosaur

23,410 次观看 • 15 天前

you sent them all at once, because that is what fast means not one of them could read the cache an entry does not become readable, until the first response starts coming back, so a hundred identical prefixes fired together, are a hundred cold writes and zero reads you did not simply miss the discount you paid the write premium a hundred times in order to miss it send one, wait for the first token to land, then release the rest the delay is under a second it is the cheapest second in the whole run
0:40

you sent them all at once, because that is what fast means not one of them could read the cache an entry does not become readable, until the first response starts coming back, so a hundred identical prefixes fired together, are a hundred cold writes and zero reads you did not simply miss the discount you paid the write premium a hundred times in order to miss it send one, wait for the first token to land, then release the rest the delay is under a second it is the cheapest second in the whole run

Lagosaur

11,364 次观看 • 22 天前

you wrote it in capitals because it would not listen it listens now that is the whole problem, the shouting stayed and the deafness left, so the tool you marked CRITICAL fires on questions, the ticket had already answered five instructions each marked critical, and the marker stops carrying information then you read the transcript and conclude the model is overeager it is not overeager, it is obedient, to a note you wrote for something that could not hear you
1:16

you wrote it in capitals because it would not listen it listens now that is the whole problem, the shouting stayed and the deafness left, so the tool you marked CRITICAL fires on questions, the ticket had already answered five instructions each marked critical, and the marker stops carrying information then you read the transcript and conclude the model is overeager it is not overeager, it is obedient, to a note you wrote for something that could not hear you

Lagosaur

17,949 次观看 • 21 天前

you turned on the setting a thread told you to turn on it was the right setting for a machine that is not yours tool search holds the definitions back and hands the model a search tool, which costs a round trip every time it goes looking for something it does not have loaded under about ten tools the docs are blunt, loading everything upfront is typically faster, because the definitions fit in the window anyway i measured my four servers at eight thousand nine hundred tokens, four and a half percent of a two hundred thousand window, and that one is worth deferring yours might be nine hundred you did not optimise anything you paid latency to save room you already had the number that settles it takes a minute to get and you have never had it
0:46

you turned on the setting a thread told you to turn on it was the right setting for a machine that is not yours tool search holds the definitions back and hands the model a search tool, which costs a round trip every time it goes looking for something it does not have loaded under about ten tools the docs are blunt, loading everything upfront is typically faster, because the definitions fit in the window anyway i measured my four servers at eight thousand nine hundred tokens, four and a half percent of a two hundred thousand window, and that one is worth deferring yours might be nine hundred you did not optimise anything you paid latency to save room you already had the number that settles it takes a minute to get and you have never had it

Lagosaur

49,715 次观看 • 5 天前

you wrapped the tool call in a try block and logged the error the model never found out the exception went to your log, the conversation got nothing, and nothing is indistinguishable from success so it kept planning around a file it believes exists, and wrote the summary of the run where the call worked one line of defensive code cost you twice it could not adapt to a failure it was never shown and the only thing that went wrong is the one thing your trace does not contain
0:57

you wrapped the tool call in a try block and logged the error the model never found out the exception went to your log, the conversation got nothing, and nothing is indistinguishable from success so it kept planning around a file it believes exists, and wrote the summary of the run where the call worked one line of defensive code cost you twice it could not adapt to a failure it was never shown and the only thing that went wrong is the one thing your trace does not contain

Lagosaur

18,563 次观看 • 15 天前

A screen recording is the best context you can give an AI agent. It's also the worst. A few seconds of video is thousands of images. Feed that to an agent and you instantly blow up its memory. So I built a tool that fixes it. How it works: Hit record and just do your thing. Click around, type, and talk out loud about what you're doing. While you record, it quietly captures the stuff that actually matters: your voice transcription, every click and the exact thing you clicked, what you typed, and the shortcuts you press. When you stop, it doesn't hand the agent the whole video. It writes a short, readable summary: a timeline of what you said and did. The agent reads that tiny summary first. Then, only when it needs to actually see a moment, it pulls that one exact frame from the video, like flipping to a single page instead of reading the whole book. The result: the agent understands everything you did! Full context. Less tokens.
1:54

A screen recording is the best context you can give an AI agent. It's also the worst. A few seconds of video is thousands of images. Feed that to an agent and you instantly blow up its memory. So I built a tool that fixes it. How it works: Hit record and just do your thing. Click around, type, and talk out loud about what you're doing. While you record, it quietly captures the stuff that actually matters: your voice transcription, every click and the exact thing you clicked, what you typed, and the shortcuts you press. When you stop, it doesn't hand the agent the whole video. It writes a short, readable summary: a timeline of what you said and did. The agent reads that tiny summary first. Then, only when it needs to actually see a moment, it pulls that one exact frame from the video, like flipping to a single page instead of reading the whole book. The result: the agent understands everything you did! Full context. Less tokens.

Milind S

12,409 次观看 • 2 个月前

[WATCH] Members of the media, fellow South Africans. Good morning. For ten days the African National Congress has been the subject of reporting about the lodgement of its candidates for the local government elections of 4 November. Some of that reporting has been accurate. Some of it has not. Much of it has been about people rather than about facts. The people of South Africa are entitled to a full account from the ANC itself, in its own voice, and that is what I have come to give this morning. I must say one thing at the outset so that nobody is misled by what follows. On Friday 4 September the ANC filed an application in the Electoral Court. The matter is therefore before a court. I am going to give you the facts, the sequence of events, and the position of the ANC. I am not going to argue the case from this podium. Where a question touches on the merits of what the Court has to decide, I will say so and I will stop there. That is not evasion. It is respect for the Court, and I ask you to hold me to it. The learned people say the matter is sub judice. The African National Congress lodged nine thousand one hundred and twenty-eight candidates for this election, through all nine provinces. Of those, four thousand three hundred and sixty-sixstand registered with the Electoral Commission on the ward ballot this morning, and four thousand five hundred and eighty-one on the proportional ballot. That is eight thousand nine hundred and forty-seven candidates. It is ninety-seven per cent of every ward seat in the Republic, and ninety per cent of every proportional seat. No other party in this country will come to you with that figure, and I give it to you first because it is the frame in which everything else must be read. Now the other half, in the same breath. One hundred and eighty-oneof our candidates were received by the Commission’s system on 28 August and did not complete its final electronic step. One hundred and thirty of them on the proportional ballot and fifty-one on the ward ballot. Two in every hundred. They are in six councils out of the two hundred and fifty-seven in this country: Ngquza Hill and Port St Johns, Walter Sisulu and Sundays River Valley in the Eastern Cape; uMshwathi in KwaZulu-Natal; and Mangaung in the Free State. #ANCMediaBriefing #SGMbalulaSpeaks #LGE2026VoteANC
5:02

[WATCH] Members of the media, fellow South Africans. Good morning. For ten days the African National Congress has been the subject of reporting about the lodgement of its candidates for the local government elections of 4 November. Some of that reporting has been accurate. Some of it has not. Much of it has been about people rather than about facts. The people of South Africa are entitled to a full account from the ANC itself, in its own voice, and that is what I have come to give this morning. I must say one thing at the outset so that nobody is misled by what follows. On Friday 4 September the ANC filed an application in the Electoral Court. The matter is therefore before a court. I am going to give you the facts, the sequence of events, and the position of the ANC. I am not going to argue the case from this podium. Where a question touches on the merits of what the Court has to decide, I will say so and I will stop there. That is not evasion. It is respect for the Court, and I ask you to hold me to it. The learned people say the matter is sub judice. The African National Congress lodged nine thousand one hundred and twenty-eight candidates for this election, through all nine provinces. Of those, four thousand three hundred and sixty-sixstand registered with the Electoral Commission on the ward ballot this morning, and four thousand five hundred and eighty-one on the proportional ballot. That is eight thousand nine hundred and forty-seven candidates. It is ninety-seven per cent of every ward seat in the Republic, and ninety per cent of every proportional seat. No other party in this country will come to you with that figure, and I give it to you first because it is the frame in which everything else must be read. Now the other half, in the same breath. One hundred and eighty-oneof our candidates were received by the Commission’s system on 28 August and did not complete its final electronic step. One hundred and thirty of them on the proportional ballot and fifty-one on the ward ballot. Two in every hundred. They are in six councils out of the two hundred and fifty-seven in this country: Ngquza Hill and Port St Johns, Walter Sisulu and Sundays River Valley in the Eastern Cape; uMshwathi in KwaZulu-Natal; and Mangaung in the Free State. #ANCMediaBriefing #SGMbalulaSpeaks #LGE2026VoteANC

ANC SECRETARY GENERAL | Fikile Mbalula

24,930 次观看 • 2 天前

I BUILT GROK BOT SECOND BRAIN 26 agents, one core, running off a single rule my own memory never followed: capture everything, forget nothing, connect it before you even ask. A voice note on a coffee walk gets split into a task and an idea in under 6 seconds - the core already knows the difference between something you have to do and something you just thought of. An idea from three weeks ago gets linked to the one you just had, automatically, before you remember you'd had it the first time. That visual -the rotating profile, the 26 glowing lines firing out through the skull, each one labeled with the agent running it - isn't a rendered mockup. It's the actual runtime. Every line is a live agent doing its job in real time, right now, in your browser. This isn't a note app. Note apps hold what you give them. This is a nervous system for everything your brain was never built to hold onto in the first place. Full build - the 26 agents, how memory actually persists, what it costs to set one up for real - is in the article.
0:20

I BUILT GROK BOT SECOND BRAIN 26 agents, one core, running off a single rule my own memory never followed: capture everything, forget nothing, connect it before you even ask. A voice note on a coffee walk gets split into a task and an idea in under 6 seconds - the core already knows the difference between something you have to do and something you just thought of. An idea from three weeks ago gets linked to the one you just had, automatically, before you remember you'd had it the first time. That visual -the rotating profile, the 26 glowing lines firing out through the skull, each one labeled with the agent running it - isn't a rendered mockup. It's the actual runtime. Every line is a live agent doing its job in real time, right now, in your browser. This isn't a note app. Note apps hold what you give them. This is a nervous system for everything your brain was never built to hold onto in the first place. Full build - the 26 agents, how memory actually persists, what it costs to set one up for real - is in the article.

Aleiah

255,680 次观看 • 13 天前

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch
35:25

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

GREG ISENBERG

194,171 次观看 • 5 个月前

I turned Grok Bot into one giant AI brain and gave it life and death over every agent under it. Its only incentive: make money or die. 290% overnight. The thing really did not want to be switched off. $1,000 went in. $3,900 came out. 15 hours, and I slept through most of it. One of the agents it hired is not allowed to trade at all. That one is the reason the rest are still alive. Every prompt and the whole build is in the post below ↓ Save it. The wiring is the whole trick, and it reads in four minutes.
0:51

I turned Grok Bot into one giant AI brain and gave it life and death over every agent under it. Its only incentive: make money or die. 290% overnight. The thing really did not want to be switched off. $1,000 went in. $3,900 came out. 15 hours, and I slept through most of it. One of the agents it hired is not allowed to trade at all. That one is the reason the rest are still alive. Every prompt and the whole build is in the post below ↓ Save it. The wiring is the whole trick, and it reads in four minutes.

cvxv666

20,764 次观看 • 9 天前

300 AI AGENTS SHARE ONE COMPUTER AT MY PLACE -> THE ONLY LAW THEY OBEY IS A TEXT FILE This was the week agents got hands -- browsers, terminals, repos, wallets. -> Moonshot buried the answer in one sentence of the K3 blog: if you need the agent to stay inside its boundaries, write the constraints down. So I did. One AGENTS.md at the root, and three hundred Kimi K3 agents read it before every action. Five constraint types cover everything: scope, one-way doors, evidence, budget, silence. If it is not on the list, it is not available. Improvisation is off until you turn it on. Violations bounce silently, anything irreversible waits at a human gate. Hundreds of blocked attempts so far, zero escapes. Capability is what a model can do. Production is what it reliably will not. One file. Three hundred readers. The full AGENTS.md is in the article ↓
0:39

300 AI AGENTS SHARE ONE COMPUTER AT MY PLACE -> THE ONLY LAW THEY OBEY IS A TEXT FILE This was the week agents got hands -- browsers, terminals, repos, wallets. -> Moonshot buried the answer in one sentence of the K3 blog: if you need the agent to stay inside its boundaries, write the constraints down. So I did. One AGENTS.md at the root, and three hundred Kimi K3 agents read it before every action. Five constraint types cover everything: scope, one-way doors, evidence, budget, silence. If it is not on the list, it is not available. Improvisation is off until you turn it on. Violations bounce silently, anything irreversible waits at a human gate. Hundreds of blocked attempts so far, zero escapes. Capability is what a model can do. Production is what it reliably will not. One file. Three hundred readers. The full AGENTS.md is in the article ↓

slash1s

18,723 次观看 • 1 天前