AI Engineer World's Fair 2026

Orchestras, Not Factories: How the Fastest Builders Work — Charlie Holtz, Conductor

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Orchestras, Not Factories: How the Fastest Builders Work

Charlie Holtz’s Conductor workflow combines early experimentation, selective human review, shared organizational context and persistent cloud agents. The goal is to give people more room to direct and craft software with a team.

From a talk by Charlie Holtz

At a glance

Ideas worth remembering

  • Try new capabilities early, then limit workflow customization to places where knowledge of your users or codebase changes what the agent should do.

  • Apply human review selectively. Migrations need enforced scrutiny, and recurring agent instructions deserve care because they influence every new task.

  • Centralized organizational information and a SQL tool give agents a way to retrieve context beyond the repository.

  • Persistent cloud workspaces separate execution from the laptop and support shared review, live conversation and remotely initiated tasks.

  • Design agent tools so people can direct the whole effort, inspect details when needed and retain the experience of crafting software with a team.

One interface for a team of coding agents

At a wedding in New York, Charlie Holtz mentioned that he was preparing a presentation about AI engineering. His conversational partner’s eyes glazed over. An audience that actually wanted to hear about coding agents was a welcome change. Holtz, Conductor’s co-founder and CEO, used that opening to introduce a practical question: what do the fastest builders do with these tools?

Conductor is a desktop app for managing multiple coding agents at once. Instead of distributing their sessions across terminal windows, it brings them into one interface. Building that interface gave Holtz a close view of other engineers’ workflows: where they invested effort, what they delegated and what they avoided. The principles that follow are his synthesis of those observations and Conductor’s own experience.

0:260:29
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0:25 · section reference included

Try new capabilities before the workflow settles

“Stay near the frontier” starts with trying new tools and workflows when they arrive. For a startup, that exposure can change what seems worth building. Conductor itself began this way. The team was working on a different app, Chorus, when heavy use of a coding agent started reshaping its development process.

Source frame: Try new capabilities before the workflow settles
Source frame: Try new capabilities before the workflow settles

The first response was to clone the repository five times. Then the team discovered Git worktrees, and the workflow gradually became an internal tool: Conductor. The product idea emerged from using the new capability enough to encounter a concrete coordination problem. Multiple agents were useful; managing their work needed a better interface.

Inside an established company, the same habit can make someone the person who knows which workflows are newly possible. Holtz warns that waiting for useful practices to trickle through a social network can leave a builder three to six months behind; that is his assessment of the pace, rather than a measured adoption delay. But the word near matters. Experimentation stops paying when improving the workflow consumes all the time that was supposed to go into the work.

2:012:06
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2:00 · section reference included

Spend custom-workflow effort where you know something specific

Conductor’s heuristic for deciding how far to customize is “don’t try and beat the market.” Ask why a promising workflow is not already the default. If it works broadly, Holtz expects providers such as Anthropic or OpenAI to incorporate it into their agent harnesses—the tools that run and coordinate the model’s work. Under that expectation, extensively rebuilding a generally useful workflow yourself may buy only a temporary advantage.

Source frame: Spend custom-workflow effort where you know something specific
Source frame: Spend custom-workflow effort where you know something specific

The exception is “real alpha”: information about your users or codebase that a general model may not know. Conductor needs to render very long chats quickly. That product requirement justifies spending time optimizing its React queries, even when doing so requires sacrifices elsewhere in the codebase. The useful customization comes from knowing which behavior matters most for this app.

This puts a stopping rule around experimentation: invest when specific knowledge changes how the work should be done. Otherwise, keep the setup from becoming its own project. Holtz’s warning is familiar to anyone who has spent too long configuring an editor: an amazing Emacs setup does not ensure that anything gets finished.

3:383:40
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3:38 · section reference included

Protect migrations and the instructions agents repeatedly read

A “slop-free zone” is an area that requires strict human review. Conductor applies that care selectively: some parts of the codebase get close scrutiny, while others allow much looser development. Holtz connects this practice to costly experience—the team had to rewrite its app a couple of times after failing to protect important areas.

Source frame: Protect migrations and the instructions agents repeatedly read
Source frame: Protect migrations and the instructions agents repeatedly read
  • Migrations: CI requires a human review whenever the migrations file changes. This makes scrutiny a required step for that file, rather than a general aspiration.
  • Team communication: Conductor treats Slack messages as human-written material. That is a team convention about who authors the communication.
  • Documentation and agent instructions: Docs and skill files receive substantial attention. They shape what agents know and how they begin their work.

The instruction-file analogy is an intern joining the company. Imagine being able to whisper advice into that intern’s ear every time they sit down to work. You would choose those words carefully because they keep influencing subsequent decisions. Agent instruction files play that recurring role: their contents enter the agent’s context when it starts working. Time spent improving them can affect many tasks, which explains why the builders Holtz admires put unusual effort into these files.

5:265:29
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5:24 · section reference included

Feed agents the organization’s working context

Careful instructions provide standing guidance. “Feed the beast” adds information about what is happening now. Conductor’s internal tool, the Conductor Internal Agent—CIA—collects organizational activity in a central database. A new Slack message is picked up and saved to a Postgres table. Discord bug reports enter the same collection process, and recorded meetings go into the CIA as well.

Source frame: Feed agents the organization’s working context
Source frame: Feed agents the organization’s working context

How does information scattered across conversations become available to an agent? The diagram follows the collection and access paths. Centralizing the material gives agents one place to look for company-specific context; a SQL tool lets them query the database. Holtz’s prescription is deliberately simple: put the information in a database and give the agent a way to ask questions of it. The mechanism supplies access to context, without establishing that every query will find or interpret the right information.

How it fits togetherFrom team activity to queryable context

New messages are picked up as they arrive.

Collection brings separate sources into one database. The SQL tool gives agents a way to retrieve organizational information when they need it.

7:117:14
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7:22 · section reference included

Move execution to the cloud, then share the workspace

“Free-range agents” need somewhere to work that survives the user closing a laptop. Holtz proposes persistent sandboxes where agents can explore the codebase, tackle difficult tasks, create more agents and collaborate with people. His reasoning is that longer-running, more capable models need an execution environment that does not inherit the interruptions of a personal computer.

Source frame: Move execution to the cloud, then share the workspace
Source frame: Move execution to the cloud, then share the workspace

The demonstration introduces a Conductor version centered on cloud collaboration. Each workspace has a cloud icon that exposes information about the sandbox running its agent. Holtz describes a change from tasks built around local Git worktrees to tasks running in cloud sandboxes, so work can continue after the laptop closes. He announces a rollout for the week of the presentation; that announcement does not establish subsequent availability.

Cloud execution also gives the interface a shared place for collaboration. The organization view lists work across teammates, and Holtz opens a colleague’s workspace to review its changes. He sends a request to use tabs instead of spaces. The colleague can see the message and chat in the same workspace; a typing indicator appears during the demonstration. The sequence establishes shared review and live conversation, though no corresponding code edit is shown.

The collaboration case follows from ambition. As models improve, teams can attempt larger projects, and larger projects call for more people and agents working together. A shared workspace gives those participants a place to inspect work and discuss its direction while it is underway. Holtz expects collaboration to become an important interface change because the unit of work increasingly includes a team.

8:418:46
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8:40 · section reference included

A message becomes a new cloud workspace

The next example turns cloud execution into remotely initiated work. A personal agent has access to the Conductor API. Holtz describes reaching it from a phone, Telegram or Slack and asking it to create a workspace. His concrete task is simple: make all the buttons blue.

Source frame: A message becomes a new cloud workspace
Source frame: A message becomes a new cloud workspace

The request passes to the personal agent, which can call Conductor’s API to start the work. Holtz then reports that the workspace has been created and the coding agent is on the task. Opening Conductor shows that workspace setup is still underway. The observable change is therefore a new workspace beginning its task; the demonstration does not establish that the buttons were changed.

What separates sending a request from executing it? The diagram shows the handoff from a messaging interface through an API to a cloud workspace. The phone supplies the request, while the sandbox supplies the execution environment. That separation lets a person initiate a task while away and return to its workspace later, without requiring the laptop to remain the host.

How it fits togetherStarting the blue-buttons task remotely

Create a workspace to make all the buttons blue.

The demonstrated result is workspace creation with setup still underway. Cloud hosting separates the agent’s execution from the device used to request it.

13:2013:23
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13:20 · section reference included

Keep people at the center of the work

The final principle gives the talk its title. Holtz dislikes the term “software factory,” even while recognizing that automation improves efficiency and makes it possible to produce more. His objection concerns the working experience and the goal that the metaphor encourages: a person managing an assembly line of agents that continually pumps out features.

Source frame: Keep people at the center of the work
Source frame: Keep people at the center of the work

An orchestra offers a different role for the person directing the work. A gesture starts one group of agents; another brings people and agents together. The conductor can zoom in on details when needed and spend much of the time looking across the whole effort. This is a design aspiration for the interface: make it possible to move between directing a team and examining its work, while retaining a sense of craft.

The shared-workspace demonstration makes part of that aspiration concrete: teammates can see ongoing work, review changes and discuss a decision in the place where the task is happening. The selective review policy supplies another part: a human deliberately gets close to migrations and recurring agent instructions. Cloud agents provide room to keep work moving between those interventions. Together, these choices let direction, review and execution happen at different levels of attention.

For tool builders, the ending is a responsibility as much as a metaphor. Holtz wants software to feel human and crafted, and wants the people making it to feel capable, absorbed and excited. His image is designing the Mac with a team of people and AI agents in the same place. The closing recap returns to all six principles, but the orchestra explains what their speed is meant to preserve: the pleasure and judgment of making something together.

14:4014:42
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Read the complete timestamped transcript
  1. 0:01

    [music]

  2. 0:25

    >> Hello.

  3. 0:26

    I was at a wedding this weekend

  4. 0:29

    and it was in New York and there were a

  5. 0:31

    bunch of trendy people there

  6. 0:33

    and uh I I told I was talking to someone

  7. 0:36

    who I'd never met before and uh I told

  8. 0:38

    him I was prepping for this presentation

  9. 0:40

    and he was like, "Oh, that's cool. Like,

  10. 0:41

    what what's the conference about?" And I

  11. 0:43

    said it was about AI engineering. And I

  12. 0:46

    could just see his eyes glaze over and

  13. 0:49

    he started like looking behind me to

  14. 0:51

    find the next person to talk to. And I'm

  15. 0:53

    it's like so cool to actually be in a

  16. 0:55

    room full of people who actually want to

  17. 0:56

    hear about this stuff.

  18. 0:57

    So, I I I I'm very excited to be here.

  19. 1:00

    Um I am the co-founder of Conductor. Um

  20. 1:02

    has anyone here used Conductor?

  21. 1:05

    Okay, nice. Nice. Okay, cool. So, uh

  22. 1:09

    uh for those who don't know, uh

  23. 1:10

    Conductor is a desktop app for managing

  24. 1:12

    a team of coding agents all at the same

  25. 1:14

    time. So, instead of having a bunch of

  26. 1:16

    terminal windows for your Cloud Codes,

  27. 1:18

    your Code Accesses, or your uh whatever

  28. 1:21

    uh coding agent, you have one interface

  29. 1:23

    to manage them all.

  30. 1:24

    And one of the really cool things about

  31. 1:26

    building Conductor has been that I've

  32. 1:28

    seen a lot of the best builders up

  33. 1:31

    close. I've like watched their workflow,

  34. 1:32

    I've seen how they work, I've seen the

  35. 1:34

    things they do do and the things that

  36. 1:36

    they avoid doing. And so, I thought I

  37. 1:37

    would compile a bunch of the principles

  38. 1:40

    um that I've seen the best engineers use

  39. 1:42

    um and give them to you all.

  40. 1:44

    Um

  41. 1:45

    so, here's what Conductor looks like.

  42. 1:48

    Uh can you can you guys see this?

  43. 1:50

    Okay, nice. Okay. So, here's what

  44. 1:52

    Conductor looks like. Um

  45. 1:54

    and here are my principles for being the

  46. 1:57

    fastest builder in your organization.

  47. 2:00

    So, let's start with

  48. 2:01

    number one, stay near the frontier.

  49. 2:06

    Staying near the frontier means you are

  50. 2:08

    always trying the latest things,

  51. 2:09

    basically the day they come out. Uh it

  52. 2:11

    means that when uh uh ultra code comes

  53. 2:14

    out, you're trying it. It means that

  54. 2:17

    when uh uh slash go comes out, you're

  55. 2:20

    giving it a go. Um it's really important

  56. 2:22

    to stay near the frontier um for a few

  57. 2:24

    reasons. Um if you are doing your own

  58. 2:27

    startup, then staying near the frontier

  59. 2:29

    means that you will um come up with lots

  60. 2:31

    of new ideas for what you should

  61. 2:32

    actually be building. Um and this

  62. 2:33

    literally happened to us. We were

  63. 2:35

    building a totally different app called

  64. 2:37

    Chorus. Um

  65. 2:38

    but we started using We were such power

  66. 2:40

    users of cloud code back in February of

  67. 2:43

    last year that we uh started building

  68. 2:45

    our whole workflow around cloud code,

  69. 2:47

    and we started cloning our repo five

  70. 2:49

    times, and then we discovered work

  71. 2:50

    trees, and then bit by bit we had built

  72. 2:52

    conductor as an internal tool. And we

  73. 2:54

    couldn't have figured that out if we uh

  74. 2:56

    weren't staying near the frontier.

  75. 2:58

    And if you're not doing a startup, you

  76. 3:00

    should be the person at your company who

  77. 3:02

    always knows what the latest uh the

  78. 3:04

    latest workflows are. Um it used to be

  79. 3:07

    that you could just kind of like use

  80. 3:09

    your social graph and the information

  81. 3:11

    that was important about the best

  82. 3:13

    workflows to use would trickle down to

  83. 3:14

    you. But things just like move way too

  84. 3:16

    fast now. You're You're always going to

  85. 3:17

    be three to six months behind if you do

  86. 3:19

    that.

  87. 3:20

    Um so, it's a very important to stay

  88. 3:22

    near the frontier. And there's an

  89. 3:23

    important word here, near. Um there is a

  90. 3:27

    danger if you are at the frontier, um

  91. 3:30

    you can you can do what uh I call

  92. 3:32

    mid-whip miming, where you're spending

  93. 3:34

    all of your time working on your

  94. 3:35

    workflow and not doing actual work. And

  95. 3:38

    so, internally we've come up uh with a

  96. 3:40

    heuristic for this. Um we call it don't

  97. 3:42

    beat the market. Don't try and beat the

  98. 3:44

    market. Um uh the concept here, like the

  99. 3:48

    heuristic you should use when you're

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    you're to decide if you're near the

  101. 3:51

    frontier or at the frontier and uh too

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    deep in into

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    the latest trends is you should ask

  104. 3:58

    yourself

  105. 3:59

    why isn't this workflow the default?

  106. 4:02

    So for example when

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    Ralph loops were becoming a big thing

  108. 4:10

    you should ask yourself like should I

  109. 4:12

    spend a ton of time optimizing my

  110. 4:14

    workflow to work with Ralph loops

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    because

  112. 4:17

    if Ralph loops work for everyone like if

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    they are the default then you probably

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    should just wait for Anthropic or Open

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    AI or ever to build the workflow into

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    the into the default harness. You can

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    think of this is sort of like an

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    efficient market hypothesis where

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    unless you have like real alpha you

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    shouldn't be optimizing your workflow

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    too much. And what I mean by real alpha

  122. 4:41

    is like some kind of information about

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    either your users or your code base that

  124. 4:45

    the models might not know about. So an

  125. 4:48

    example for us is we it's

  126. 4:51

    we're we're a chat app. We have to

  127. 4:52

    render really long chats really quickly

  128. 4:54

    and performance is is important to us

  129. 4:56

    and so we need to spend a lot of time

  130. 4:58

    optimizing our react queries

  131. 5:00

    to render the chats quickly and we're

  132. 5:02

    willing to make sacrifices in other

  133. 5:05

    parts of our code base to make that

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    happen.

  135. 5:07

    Um So if you have some kind of alpha

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    like some kind of information about the

  137. 5:11

    app you're building that the models

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    might not know about then you should put

  139. 5:14

    time into the workflow. Otherwise don't

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    don't midwit meme. Don't don't be the

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    person who has an amazing Emacs setup

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    but like doesn't actually get stuff

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    done.

  144. 5:24

    Okay three.

  145. 5:26

    Create slop free zones. So at Conductor

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    we have this term we call a slop free

  147. 5:30

    zone.

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    And a slop free zone is a part of the

  149. 5:34

    code base or a part of the app that

  150. 5:37

    requires really strict human review.

  151. 5:40

    And we're actually I think a little bit

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    unusual in this way. I think a lot of

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    people assume that we are uh pure token

  154. 5:46

    maxers and we are like ripping through

  155. 5:47

    like 30,000 line PRs, but we're actually

  156. 5:50

    not. Um we're actually quite careful

  157. 5:52

    with certain parts of our codebase, and

  158. 5:54

    then very loose with other parts of our

  159. 5:56

    codebase. Um

  160. 5:58

    the reason this is important is because

  161. 5:59

    if you are not careful about your slot

  162. 6:01

    free zones, your your code your codebase

  163. 6:03

    can get in a really tricky spot. Um and

  164. 6:06

    this actually happened to us. We have

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    We've had to rewrite our whole app like

  166. 6:10

    a couple of times because we weren't

  167. 6:11

    careful about slot free zones. Um

  168. 6:14

    specifically, we have a uh migrations

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    file. And

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    uh in our CI

  171. 6:21

    uh any change to migrations file

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    requires the AI uh a human to review it.

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    Um we also assume that anything written

  174. 6:28

    in Slack is slot free. It's It's not

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    written by the AI. It's written by a

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    human. All of our docs, um all our cloud

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    MDs, like all our skills, we put a ton

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    of time into making them good. Um

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    and this is also something I've seen

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    with all the the the best builders up

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    close. Like they put an unusual amount

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    of time into the cloud MD or their skill

  183. 6:47

    files. Um and I I think like another way

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    that I've thought about this is like if

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    you had a new intern that was joining

  186. 6:55

    your company, and you had the

  187. 6:57

    opportunity to like whisper something in

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    their ear every time they started

  189. 7:02

    working. Like every day, anytime they

  190. 7:04

    sat down, you could like whisper

  191. 7:05

    something in their ear. You would

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    probably put a lot of thought into like

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    what it is that you're whispering in

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    their ear. And this is what the cloud MD

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    or agent's MD is. It's like information

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    that gets loaded into the agent's

  197. 7:15

    context every time they start working.

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    Um and so you probably want to put a lot

  199. 7:19

    of thought into

  200. 7:20

    into those.

  201. 7:22

    Um okay, four.

  202. 7:25

    Feed the beast.

  203. 7:26

    Uh

  204. 7:28

    at Conductor, we have a uh internal tool

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    we call the Conductor Internal Agent. Um

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    and it is

  207. 7:36

    uh we also also known as the CIA.

  208. 7:38

    And the CIA is basically like the the

  209. 7:42

    uh centralized database of everything

  210. 7:44

    that's happening in the organization.

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    So, anytime a new Slack message gets

  212. 7:47

    sent, the CIA picks it up. The CIA agent

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    will see that a new message sent Slack,

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    it will pick it up, and it will save it

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    to a Postgres uh

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    uh table. Anytime a user has a bug

  217. 7:58

    request in Discord, the same thing

  218. 7:59

    happens. Anytime we have a meeting, we

  219. 8:02

    are recording it, uh and it goes into

  220. 8:04

    the CIA. Um we call this feed the beast

  221. 8:07

    because you you want to for if your

  222. 8:09

    agents to be effective uh

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    in your company, you want them to have

  224. 8:13

    as much information and as much context

  225. 8:15

    as they can have about the way you guys

  226. 8:17

    specifically work. And the best way to

  227. 8:19

    do that is by having a centralized place

  228. 8:22

    for all of the information to go.

  229. 8:25

    Uh I think this this tweet sums it up

  230. 8:27

    pretty well. Uh uh

  231. 8:29

    It's really effective to just put

  232. 8:31

    everything in a database and then give

  233. 8:33

    your agent a SQL tool and let it handle

  234. 8:36

    uh

  235. 8:37

    uh handle the rest.

  236. 8:40

    Okay.

  237. 8:41

    Next is free-range agents.

  238. 8:46

    Give your agents

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    a lot of space to play. Give them Give

  240. 8:50

    them a sandbox where they that won't get

  241. 8:52

    killed, where they can explore your code

  242. 8:54

    base, where they can work on really hard

  243. 8:56

    tasks, where they can they know that

  244. 8:58

    they're not going to get shut down when

  245. 9:00

    you close your laptop lid. Uh Give them

  246. 9:03

    Give them opportunities to create more

  247. 9:05

    of themselves. Um

  248. 9:07

    Give them ways uh to collaborate with

  249. 9:09

    other agents and other humans. Um

  250. 9:12

    I think what's really in- interesting

  251. 9:14

    about free-range agents and like this

  252. 9:16

    this concept and why this is important

  253. 9:18

    is the models are getting better, and

  254. 9:21

    they are able to run for much longer,

  255. 9:23

    and there're going to be many more of

  256. 9:24

    them. And so, if they are confined to

  257. 9:27

    your laptop, then the they're not going

  258. 9:30

    to be nearly as effective as uh as if

  259. 9:32

    they are free roaming.

  260. 9:34

    Um The other thing that's important here

  261. 9:36

    is that once you give them a a sandbox

  262. 9:39

    to play in that isn't confined to your

  263. 9:40

    laptop, there's a bunch of really cool

  264. 9:42

    stuff that you can build on top. Um and

  265. 9:45

    we have built some of those things into

  266. 9:46

    Conductor and I

  267. 9:48

    I'll give you a quick glimpse into into

  268. 9:50

    some of those cool things.

  269. 9:52

    So,

  270. 9:56

    this is Conductor.

  271. 9:58

    I'm going to make it a bit bigger.

  272. 10:00

    Um and this is actually a new version of

  273. 10:01

    Conductor that is

  274. 10:03

    uh coming out this week and it is

  275. 10:06

    centered around collaboration in the

  276. 10:08

    cloud.

  277. 10:10

    And so, the the the thing I said was you

  278. 10:12

    need a a sandbox for agents to play. You

  279. 10:14

    need a free-range agent. And so, you'll

  280. 10:16

    notice that each workspace has a little

  281. 10:18

    cloud icon at the top and I can click it

  282. 10:21

    and get information about the sandbox

  283. 10:23

    that the agent is running in.

  284. 10:25

    Um and what's what's awesome about this

  285. 10:27

    is I can close my laptop and the agents

  286. 10:29

    are going to keep running.

  287. 10:30

    Up up until basically this week, every

  288. 10:33

    uh every task in Conductor was built on

  289. 10:34

    a get work tree, but now they're in a

  290. 10:36

    cloud sandbox. They are free-range

  291. 10:38

    agents.

  292. 10:38

    But what's also really cool um that you

  293. 10:41

    can that we can build on top of uh cloud

  294. 10:44

    is collaboration.

  295. 10:46

    So, you'll see here, I'll make this even

  296. 10:48

    bigger.

  297. 10:49

    That's me.

  298. 10:51

    And here are a list of the things that I

  299. 10:52

    am working on. And you can see that I am

  300. 10:54

    in the Conductor org. But if I scroll

  301. 10:57

    down, I can see what Cadence is working

  302. 11:00

    on.

  303. 11:01

    I can see what Lewis is working on. I

  304. 11:04

    can see what Tywan is working on and I

  305. 11:05

    can I can I can see that I can see

  306. 11:08

    Jackson's face pop up there. I can click

  307. 11:09

    in and see what he's working on in real

  308. 11:11

    time. Um and I think collaboration is

  309. 11:16

    the the one one of the most important

  310. 11:18

    new concepts uh in these tools that no

  311. 11:20

    one is really talking about right now.

  312. 11:21

    Um collaboration is important because

  313. 11:24

    uh not only as not only

  314. 11:26

    it is it true that all great things are

  315. 11:28

    built with teams of people. Like they're

  316. 11:30

    not built by individuals. They're

  317. 11:31

    they're built by teams. Um but also as

  318. 11:34

    the models get better, um as we've seen

  319. 11:36

    this with the two days of Fable, you can

  320. 11:38

    get a lot more ambitious with the kinds

  321. 11:39

    of things you're building. And if you're

  322. 11:41

    getting more ambitious, you're going to

  323. 11:42

    need more people and more agents to work

  324. 11:44

    on those things. So, I'm going to go

  325. 11:46

    into an uh

  326. 11:48

    a workspace that Caden is working on.

  327. 11:51

    Uh this one, and I'm going to say um I

  328. 11:54

    can review the changes that he's made.

  329. 11:57

    Um

  330. 11:58

    I'll make this a little smaller, and

  331. 12:02

    this looks fine, but I'm just going to

  332. 12:03

    say uh can we actually use tabs, not

  333. 12:07

    spaces?

  334. 12:10

    And

  335. 12:12

    Caden should be able to see that message

  336. 12:15

    happen in real time, and he can actually

  337. 12:17

    chat in the workspace as well. So, we

  338. 12:19

    can see here that he's typing.

  339. 12:22

    So, I see Caden is typing.

  340. 12:24

    Let's see what he says.

  341. 12:31

    Seems like he's typing a lot.

  342. 12:37

    Okay, maybe he stopped typing.

  343. 12:45

    I'll give him a second to take a look at

  344. 12:47

    it. But, the point is

  345. 12:48

    we can now have collaborative workspaces

  346. 12:50

    that are shared in real time with people

  347. 12:52

    on our team.

  348. 12:54

    Um

  349. 12:55

    Okay, he's typing again.

  350. 13:01

    Okay, come back. The agents have

  351. 13:03

    escaped.

  352. 13:04

    All right. So, I'm really excited about

  353. 13:07

    this, and we're rolling this out to all

  354. 13:09

    conductor users this week. Um I think I

  355. 13:12

    think collaboration is going to be one

  356. 13:13

    of the most important one of the most

  357. 13:15

    important new interface changes this

  358. 13:17

    year. Um the other really cool thing

  359. 13:20

    about cloud is that um and giving it the

  360. 13:23

    agents the free-range sandbox is that we

  361. 13:25

    can give the agents APIs to spawn

  362. 13:27

    themselves. So, I have here a uh I'll

  363. 13:30

    bring up my open claw.

  364. 13:32

    Uh this is my open claw called Lord

  365. 13:34

    Crandon.

  366. 13:36

    And

  367. 13:37

    you can see that it has I don't know how

  368. 13:39

    how well you can see this text, but it

  369. 13:42

    has access to a conductor API. And so,

  370. 13:44

    from my phone or from my Telegram or

  371. 13:47

    from really or from Slack or wherever I

  372. 13:49

    am, I can say, "Hi, can you create a new

  373. 13:52

    workspace for me that makes

  374. 13:56

    Yeah, makes all the buttons

  375. 13:58

    blue."

  376. 14:00

    And so, I'll I'll text that to Lord

  377. 14:02

    Crandon, and Lord Crandon has access to

  378. 14:05

    the conductor API and so can kick off

  379. 14:06

    work itself. Um

  380. 14:09

    So, let's see what it does here.

  381. 14:15

    Okay, so just created the workspace. The

  382. 14:17

    agent is on it. And then I can go into

  383. 14:21

    my conductor while I'm out and about,

  384. 14:23

    but it's still setting up the workspace,

  385. 14:25

    and it will do work for me while I am

  386. 14:27

    gone.

  387. 14:29

    So, I'm pretty excited about all the all

  388. 14:31

    the cool things you can build on top of

  389. 14:33

    of

  390. 14:34

    free range agents.

  391. 14:38

    Okay.

  392. 14:40

    The final principle that I want to talk

  393. 14:42

    about today and the title of this talk

  394. 14:44

    is orchestras, not factories.

  395. 14:48

    The whole like talk track today is about

  396. 14:50

    software factories. And I honestly kind

  397. 14:54

    of hate the term.

  398. 14:55

    I think it's the wrong way of thinking

  399. 14:57

    about these new tools that are emerging.

  400. 15:00

    I think like when I think of a factory,

  401. 15:03

    I think of automation. And I think of

  402. 15:06

    like there's a lot of amazing things

  403. 15:08

    about automation and like it makes our

  404. 15:09

    lives more efficient, and we can like

  405. 15:11

    create more of everything. But

  406. 15:14

    I don't want the future to be built

  407. 15:15

    around factories. I want the future to I

  408. 15:19

    want to feel like a human. I want to

  409. 15:20

    like be in the flow. I want to be like

  410. 15:23

    in front of an orchestra like waving my

  411. 15:25

    baton and we're and like I wave it this

  412. 15:27

    way and this this team of agents starts

  413. 15:30

    working and then this intermingling of

  414. 15:31

    humans and agents starts working as I go

  415. 15:33

    here. And I can when I want to I can

  416. 15:35

    zoom in on the details, but most of the

  417. 15:36

    time I can zoom out. And I don't think

  418. 15:39

    the future should be we are like

  419. 15:41

    managing swarms of agents and we are

  420. 15:44

    like factory line managers like pushing

  421. 15:46

    buttons getting the agents to like pump

  422. 15:48

    out the next feature. Like we can we can

  423. 15:50

    we tried this like 10 years ago with the

  424. 15:52

    term feature feature factories and it

  425. 15:55

    just doesn't work. Like I want my

  426. 15:57

    software to feel human and crafted. I

  427. 16:00

    want to feel like a human at the center

  428. 16:01

    of it all. And I think because we're all

  429. 16:03

    building these tools we actually have a

  430. 16:04

    responsibility to make the tools great

  431. 16:08

    for humans. I think it's really

  432. 16:10

    important to like use the words that

  433. 16:12

    make us feel excited and like feel feel

  434. 16:14

    capable and feel

  435. 16:16

    like we're in the flow and having fun.

  436. 16:18

    And so I don't think the future is

  437. 16:22

    is is something like this. I don't want

  438. 16:24

    to be I don't want to be in in my dark

  439. 16:26

    factory.

  440. 16:27

    I don't want to be a line manager. I

  441. 16:29

    want to feel like this.

  442. 16:31

    I want to be in the flow. I want to be

  443. 16:33

    having fun. I want to be crafting

  444. 16:34

    things. I want to feel like I'm Steve

  445. 16:36

    Jobs designing the Mac with a team of

  446. 16:39

    amazing humans and AI agents all in the

  447. 16:41

    same place. Like I want to feel like I'm

  448. 16:44

    in an orchestra.

  449. 16:46

    So here are my principles for

  450. 16:49

    for being the best builder in your

  451. 16:50

    organization.

  452. 16:52

    Stay near the frontier. Don't try and

  453. 16:54

    beat the market. Create slop free zones.

  454. 16:57

    Feed the beast. Free range agents and

  455. 17:00

    think about orchestras not factories.

  456. 17:05

    Came up with this handy acronym for for

  457. 17:06

    remembering it. Stickfo.

  458. 17:08

    All right. So thanks thanks a ton for

  459. 17:10

    for having me. I'll be around. Feel free

  460. 17:12

    to ask questions and

  461. 17:14

    I'll see you on the internet.