How to Map Your Whole Business Into One Workflow — Transcript

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1. 0:00AI probably occupies half of my time
2. 0:02right now
3. 0:03in terms of like what I'm thinking about
4. 0:05within the business.
5. 0:11And so
6. 0:18Okay.
7. 0:20Okay, so from a beliefs perspective,
8. 0:22right? Like one of the big shifts that
9. 0:23everybody here has to make is shifting
10. 0:25away from thinking about roles based
11. 0:27growth and expansion towards workflow
12. 0:30based automation. So
13. 0:33Imagine that you're you're like I want
14. 0:35to hire
15. 0:37I want to hire an editor. All right, I'm
16. 0:38just making this up. I want to hire an
17. 0:40editor.
18. 0:41This is how we used to think about
19. 0:43things. I need to hire an editor so they
20. 0:44can do XYZ.
21. 0:46The way that we all have to think about
22. 0:48our businesses now is that this editor
23. 0:50really was going to do
24. 0:53these four or five things, right? And
25. 0:55each of these things should exist
26. 0:59in a workflow. Like the reason that like
27. 1:01and this is the editor does this one and
28. 1:03they're doing this one
29. 1:05in this workflow and maybe they're doing
30. 1:06these three in this workflow. And so
31. 1:09basically you have to go more granular
32. 1:12to the level of like because every
33. 1:13single business, if you really think
34. 1:15about it, can be connected at the most
35. 1:16intricate level of like this action to
36. 1:18this action to this action to this
37. 1:19action all the way through. Now might be
38. 1:21120 actions that go from
39. 1:23inbound lead to dirt, you know, turf,
40. 1:26whatever, right? And it's getting
41. 1:28granular and this is the thinking that
42. 1:29most people won't do, which is why they
43. 1:31will lose and why I think a lot of
44. 1:32people are going to get [ __ ] But if
45. 1:33you have a little bit more horsepower
46. 1:34and have a little bit more time to think
47. 1:36about things, that's where instead of
48. 1:38saying I need to hire an editor, you say
49. 1:39I need an agent who just does this and I
50. 1:42need an agent that just does this and an
51. 1:44agent that just does this. And so it's
52. 1:47switching from
53. 1:49again roles to workflows.
54. 1:52And everything just has to be organized
55. 1:53in workflows. And so it's like a very
56. 1:55fun project is thinking like can you
57. 1:57actually draw your entire business in
58. 1:59one linear workflow? Cuz it does happen
59. 2:01and if you can't draw it, how the [ __ ]
60. 2:03do you have a business, right? But it
61. 2:05really starts with like
62. 2:09like the business for us for example
63. 2:10starts with an idea. It sounds silly,
64. 2:12but like it starts with an idea. So, how
65. 2:14does an idea come to happen?
66. 2:16Well, the what is the workflow around an
67. 2:18idea? For us it would be like, okay, um
68. 2:21I check our school community and I look
69. 2:24at what's happening. Okay, that is a
70. 2:26workflow, which is
71. 2:28uh search, you know, search this
72. 2:31database, which is school, but it could
73. 2:33be, you know, trends.com or you know,
74. 2:35one of 10.com, whatever.
75. 2:37Um where you look at what things are
76. 2:39outperforming in this particular market.
77. 2:41And then it says, okay, then it gives
78. 2:43you this list
79. 2:44of the out-performers. And then there's
80. 2:46going to be a match between this list
81. 2:48and our competency. So, it's like I have
82. 2:51a list of things that I like talking
83. 2:52about. These are list of things that
84. 2:54people want to hear about. This is the
85. 2:55intersection between those things.
86. 2:57Great.
87. 2:59What does this look like in terms of
88. 3:01uh
89. 3:01uh scripting, right? So, it's like,
90. 3:03okay, we're going to have some sort of
91. 3:04scripting around this.
92. 3:05So, I want uh templated ideas. AI does
93. 3:08this, so it gives us
94. 3:09um okay, this is a seven-step, whatever.
95. 3:12And it has each of the steps underneath
96. 3:14of it and we like, great. Now that the
97. 3:15scripting's done,
98. 3:17we're going to go into
99. 3:18packaging.
100. 3:20All right, what are going to be the
101. 3:20headlines, what are going to be the
102. 3:21thumbnails?
103. 3:23This is an AI workflow.
104. 3:25And then we're going to get into
105. 3:26production, right? And so all of this is
106. 3:29broken down just so that we can get one
107. 3:30thing to happen, which is a click.
108. 3:32Right? But every single element of the
109. 3:34business can be broken down into the
110. 3:36into its constituent workflows. And so I
111. 3:38think the mistake that a lot of people
112. 3:39are making right now with AI is being
113. 3:40like, well, AI can't do what a human can
114. 3:42do, well, which is obviously [ __ ]
115. 3:44but like
116. 3:46you have to train it the way you train a
117. 3:47human.
118. 3:48So, saying like, well, I'm I'm to bring
119. 3:50this this human in and tell them nothing
120. 3:52and expect them to do a good job is
121. 3:53ridiculous, but we're somewhere else we
122. 3:55like believe that a machine should be
123. 3:56able to do that. But instead it's
124. 3:57thinking, okay, this editor or
125. 4:00videographer or whatever it is,
126. 4:03actually does 16 actual activities and
127. 4:07each of those activities we have to take
128. 4:09one at a time and we can have an agent
129. 4:11that's trained on that thing.
130. 4:13And so like right now, I know Alex is
131. 4:14working super hard with Julian on this,
132. 4:16but like
133. 4:17we have so I do like my Hormozi
134. 4:18hotlines. And so I do a hotline and then
135. 4:21that then goes into
136. 4:23um
137. 4:24basically an AI thing that does uh that
138. 4:26breaks down the the the transcripts.
139. 4:28That's like step one. From the
140. 4:29transcript it then says, okay, notice
141. 4:31when there's different speakers. All
142. 4:33right? So it has to do that two times.
143. 4:35One is notice when
144. 4:36it's Alex versus the other person. So
145. 4:38it's ABABAB, imagine I'm A, but then it
146. 4:41eventually switches to ACACAC and then
147. 4:43it goes to ADADAD because there's new
148. 4:47person that I'm on the phone with. So
149. 4:48it's going to say segment first between
150. 4:51when it goes from AB to AC. So great,
151. 4:53now we have 10 underneath clips. From
152. 4:55there, uh it'll run a separate script
153. 4:57that's like look cuz it's like what
154. 4:59would an editor do? The first thing
155. 5:00you're going to do is clip out the
156. 5:01individual portions. Okay, there's 10
157. 5:02different conversations Alex had. Okay.
158. 5:04Now that we have those 10 conversations,
159. 5:06look through this and try to find the
160. 5:07highest tension moment. And so it'll
161. 5:09read the words and say this is the
162. 5:10highest tension moment. And then great,
163. 5:12start the [snorts] clip with the highest
164. 5:13tension moment and then get into the
165. 5:16rest of the clip. What else do we want?
166. 5:17Remove all ums and ahs. Great. Now from
167. 5:20there, what are the um what data is
168. 5:23required in order to have the insight
169. 5:25that Alex delivers? Only these four
170. 5:27points. Great, collapse the rest. Now
171. 5:29export final file of that.
172. 5:32That's the workflow. And so it's really
173. 5:34just building this on a consistent basis
174. 5:36and continuing to update that prompt,
175. 5:37which is literally just like updating
176. 5:38the training for a human being of like
177. 5:40actually do this too, just like you
178. 5:41would with an editor, but doing that
179. 5:43across every function of the business.
180. 5:46So that is like that is the future. And
181. 5:48the nice thing is that with
182. 5:50there's a lot of businesses that
183. 5:52like agencies, for example, have been a
184. 5:54notoriously shitty business
185. 5:56to run.
186. 5:57Um
187. 5:59but in the future, I think they'll be
188. 6:01incredibly lucrative businesses for the
189. 6:03people who are really good with AI
190. 6:04because
191. 6:06the demand for more customers is
192. 6:07infinite.
193. 6:09And so, there's like no one's like,
194. 6:10"Hey, what's product market fit for an
195. 6:11agency?" You don't have to ask. People
196. 6:13want customers. It's not hard to like
197. 6:14you don't need to ask for product market
198. 6:15fit. The issue is that
199. 6:18the ops around being good at getting
200. 6:20customers is significantly harder. But,
201. 6:22if you can operationalize each of the
202. 6:23flows, it becomes much better. And this
203. 6:25is why like
204. 6:27like I'm built for this movement because
205. 6:29it's all about being black and white
206. 6:31with observable behavior. And that's
207. 6:32like what I geek out on. And so, this is
208. 6:35where vague language like machines do
209. 6:37not understand like vague language.
210. 6:38Also, neither do [ __ ] humans.
211. 6:40Um we just nod our heads because we've
212. 6:42been reinforced for doing so. But, this
213. 6:43is where being very specific like, "Hey,
214. 6:45I need you to be more charismatic."
215. 6:46means nothing. We have to say, "I need
216. 6:48you to raise your voice in this way. I
217. 6:49need you to talk faster. I need you to
218. 6:51raise your head when you're speaking. I
219. 6:52need you to nod when the other person's
220. 6:53talking." We have to break it down into
221. 6:54what someone would do. And so, um as
222. 6:57though you were teaching a toddler, you
223. 6:58have to work the same way with the
224. 6:59machine, but the machine never forgets.
225. 7:02Hopefully that answered the question.
226. 7:03>> It does.
227. 7:04>> Okay.
228. 7:06But yeah, this is what I'm thinking a
229. 7:07lot about.
230. 7:10>> So, it starts with a clear process map
231. 7:12or workflow map of the every action in
232. 7:14the business.
233. 7:14>> Exactly. And I would I would start like
234. 7:16start start with the big ideas first.
235. 7:19So, it's like, "Okay, I do I I I have an
236. 7:21idea."
237. 7:22And then I make a script, and then I uh
238. 7:25I shoot it, and then I you know, then we
239. 7:27we export the clip, and then we edit it,
240. 7:29and then we post it. Okay, that's the
241. 7:30that's the big picture. But,
242. 7:33now underneath of each of those, there's
243. 7:34probably six or seven things that
244. 7:36actually happen in order to post it.
245. 7:39It's like, "So, I actually go to this
246. 7:40page. I look at the schedule of what
247. 7:42was, you know, last posted. I add 3
248. 7:44hours to it. I like you just have to
249. 7:46like
250. 7:47one word turns into six six actions. And
251. 7:50it's just continuing down until there's
252. 7:52you can't reduce it anymore, and then
253. 7:53that's what you automate.
254. 7:56>> Do you have special AI implementation
255. 7:57team to build this?
256. 7:58>> Oh, yeah, we have a full dev team. Yeah.
257. 8:00>> Yeah, but they're specifically on this
258. 8:02topic.
259. 8:03>> Yeah. So, I think I think many of you,
260. 8:05especially those of you who are online,
261. 8:08uh an amazing high-leverage hire is just
262. 8:10an AI like an AI automation person.
263. 8:13Um they will not lack for work to do.
264. 8:15Like they can just sit next to teams and
265. 8:17just watch what they're doing and then
266. 8:18just say like I can automate that. I can
267. 8:20automate that. I can automate that.
268. 8:23>> Okay.
269. 8:24Is that something that we should do
270. 8:25right now?
271. 8:27>> Yeah.
272. 8:27>> And hire?
273. 8:28>> Yeah.
274. 8:29If you have the cash flow for it.
275. 8:30Mhm.
276. 8:31>> What does a dev hire run?
277. 8:33>> Mhm?
278. 8:33>> What does that somebody like that run?
279. 8:36>> Depends on how good they are. I think
280. 8:38though as Lindsay Lohan said, "The sky's
281. 8:40the limit does not exist." So,
282. 8:42like there there's a there's a
283. 8:44there's a price tag for every level of
284. 8:45skill you want.
285. 8:47But even just somebody who would I would
286. 8:48just consider like a hacker, and I say
287. 8:50hacker like loosely, like somebody who
288. 8:51just duct tapes tools together,
289. 8:53probably like 150 grand a year.
290. 8:58>> And in terms of prioritizing for us,
291. 8:59would you focus on the delivery side
292. 9:01first?
293. 9:02>> I think that you getting um
294. 9:06the elements that we walked through
295. 9:07specifically around the expectation
296. 9:09setting number one.
297. 9:11Um
298. 9:12I think CAC expectations number two. And
299. 9:15then the controllables around brand.
300. 9:17Like the the brand controllables, I
301. 9:18think that should be largely automated.
302. 9:21Um because it is automatable. It's
303. 9:23literally pattern detection, which is
304. 9:24like machines do better than humans do
305. 9:26anyways.
306. 9:27And so, what what humans do shitty at is
307. 9:29giving the pattern to recognize. And so,
308. 9:32that's like in terms of like what skill
309. 9:33will you need to be get good at is when
310. 9:36someone says like this is off brand, be
311. 9:37like what the [ __ ] does that mean? Like
312. 9:39tell me in describables so that
313. 9:41otherwise how am I if you can't tell me
314. 9:43how am I going to know?
315. 9:45So it has to be in black and white
316. 9:46language.
317. 9:50Yeah.
318. 9:51I think for like home services and brick
319. 9:53and mortar
320. 9:54a lot of um
321. 9:56basically all administrative work should
322. 9:58just not really be a thing.
323. 9:59Like you know, invoicing, matching
324. 10:02billables, like back office for sure is
325. 10:05or like that's already there. Like
326. 10:06that's like now.
327. 10:08Um
328. 10:09receivables, that's like now. Like you
329. 10:12don't need to There's nothing there.
330. 10:13Lead nurture,
331. 10:15that's now. Like you don't
332. 10:17Like a lot of that stuff's already
333. 10:18already kind of done. The advantage that
334. 10:21um y'all have for in person is that like
335. 10:23I don't know how horses will respond to
336. 10:25robots.
337. 10:26So you probably have a little bit of You
338. 10:28probably have a little bit of security,
339. 10:29you know, like
340. 10:30otherwise you're getting, you know, mule
341. 10:31kicks into the into the into the side of
342. 10:33the stall.
343. 10:34Um
344. 10:35uh
345. 10:37I think that from a landscaping
346. 10:38perspective
347. 10:40there will be kind of like once Optimus
348. 10:42comes out and you can teach it how to
349. 10:43like mow lawns and [ __ ] like that'll be
350. 10:44a thing for sure.
351. 10:46Um
352. 10:47Hm?
353. 10:49Yeah.
354. 10:50Yeah, yeah, I mean it can do it.
355. 10:52Um there'll also be I think like job
356. 10:54specific ones, but most likely I think
357. 10:56the biggest proliferations going to be
358. 10:57around generalized humanoid robots
359. 10:58because the world is already built for
360. 10:59us. And so like as much as it's like,
361. 11:02you know, I'm sure you've seen like the
362. 11:03like the Zoomba of lawn care, I'm sure
363. 11:06you've seen these things where it's like
364. 11:07you drop it around, but like I haven't
365. 11:09seen anyone really take off with that.
366. 11:11At least I haven't seen it. And I think
367. 11:13it's just because like there's too many
368. 11:14unique scenarios, it costs too much like
369. 11:16the cost doesn't make sense yet. Maybe
370. 11:18in three or four generations it'll be
371. 11:20there. But in the meantime, the skeleton
372. 11:23key for the world is just the way the
373. 11:24human body works.
374. 11:26Door handles, everything's already built
375. 11:27for that. So it's like as silly as it
376. 11:29sounds, it's like the world's already We
377. 11:30already built the world for ourselves.
378. 11:32If there's a robot that can fit
379. 11:33underneath the door, we could make a
380. 11:35special purpose robot that does that,
381. 11:36but it's like you'd have to do that in
382. 11:37every door in every building. Or you
383. 11:39just build a [ __ ] human robot, which
384. 11:41is what everyone's doing.
385. 11:44Yeah, I think I think you're fine for
386. 11:45the short term. The The stuff that you
387. 11:46should be focused on from an automation
388. 11:48perspective is going to be back office.
389. 11:50Yeah, and there's And the thing is it's
390. 11:52great at that. It's [ __ ] awesome at
391. 11:54it. And you should totally use it for
392. 11:55that.
393. 12:00The UAJ?
394. 12:01>> Yeah, like like would that be something
395. 12:02like using AI for like the nurture like
396. 12:04that stuff and like
397. 12:05>> 100%.
398. 12:09Right now, voice is almost there. This
399. 12:11is supposed to be the year of voice.
400. 12:13Um it's close. It's not.
401. 12:16There's a lot of tools out there. I
402. 12:17won't make any recommendations cuz like
403. 12:19they change all the time.
404. 12:21Um I would say voice is very close.
405. 12:23Text is there.
406. 12:25>> Yeah, I was [snorts] thinking about like
407. 12:27off hours having
408. 12:29like a voice
409. 12:31like auto call auto attendant.
410. 12:34>> I went to a gym
411. 12:35that was local here. It's a It's like a
412. 12:37very exclusive like whatever. I think
413. 12:39it's like 10 grand a year or something
414. 12:40like that. It has like
415. 12:42400 members, and that's the deal.
416. 12:44Um pretty interesting model. But I went
417. 12:47to the site, and it was just a chat
418. 12:48interface. It just said like, "What do
419. 12:49you want to know?"
420. 12:51And so I was like, "Hours." And it was
421. 12:52like, "Here's the hours." I was like,
422. 12:53"What else do you want to know?" And I
423. 12:54was like, "Membership prices." And it
424. 12:55was like, "Here's the membership
425. 12:56prices." I was like, "What else do you
426. 12:57want to know?" I was like, "Uh."
427. 13:00I mean, it should have asked me for my
428. 13:01information, but
429. 13:03it's not per It was not well trained
430. 13:04enough.
431. 13:04>> [laughter]
432. 13:05>> Um but like I was like, "This is pretty
433. 13:07slick."
434. 13:11Like why navigate when it just already
435. 13:12has the answers?
436. 13:16Not to get very odd for you guys, but in
437. 13:17the next I would say 12 to 24 months, a
438. 13:19lot of like the UX is going to
439. 13:20disappear.
440. 13:22Like we're not going to be clicking
441. 13:23things.
442. 13:24Like the mouse Like what brought
443. 13:27computers into mainstream was a mouse.
444. 13:30Like that was the big innovation was
445. 13:32having a mouse you could point and click
446. 13:33and then all of a sudden people were
447. 13:33like, oh, I just want that thing. It's
448. 13:34like click and it worked. And so,
449. 13:37nothing's really kind of happened in the
450. 13:39computational besides speed and power
451. 13:40and all that stuff, but it's all been um
452. 13:42more of the same. The next phase shift
453. 13:45is that UX disappears, which is that you
454. 13:47just have an agent that you just talk
455. 13:49to.
456. 13:50Right? And you say, hey, you know, what
457. 13:51did we do in cash flow last month? And
458. 13:53then you just text it or you say it and
459. 13:54it just answers.
460. 13:56And like the world of CRMs is going to
461. 13:58change. Like this is this is the next 12
462. 13:59to 24.
463. 14:00Yeah.
464. 14:01Yeah.
465. 14:03>> Don't you think that we are very into
466. 14:04it, but 99% of people are still
467. 14:06>> Yeah. Oh, yeah. I mean, there are legal
468. 14:08firms that use fax machines now. And so,
469. 14:11there's this idea that like, oh my god,
470. 14:12the whole world It's like, no, just like
471. 14:13always, humans plus technology will beat
472. 14:16humans with inferior technology. And so,
473. 14:18if you learn how to use the tech, you'll
474. 14:20do better. But there will be people who
475. 14:22still have law firms and use fax
476. 14:24machines that will make money.
477. 14:25It's just there will be people who don't
478. 14:26use fax machines that will make more
479. 14:28money.
480. 14:32So, I'm not like an AI alarmist. I think
481. 14:33it's going to take a while, but
482. 14:35um
483. 14:36I do think there's I won't even get into
484. 14:38that, so I'll just stop, but
485. 14:40we just get too much of a future no one
486. 14:41knows anything about.