[0:00] You're paying $20 a month for Gemini or
[0:03] Chad GPT. Meanwhile, there's a free AI
[0:06] model that just hit 96% on the toughest
[0:09] math benchmark in the world, matches
[0:12] GPT5 in reasoning, and won gold medals
[0:15] at international coding competitions.
[0:17] And I'm willing to bet most of you have
[0:19] never even tried it. It's called
[0:21] Deepseek V3.2. It dropped December 1st,
[0:24] completely free, completely open source,
[0:26] and it's shockingly good. Most people
[0:28] forgot Deepseek even exists. That's a
[0:30] mistake because in the next 20 minutes,
[0:33] I'm going to show you how to use this
[0:35] thing for real work, writing, research,
[0:37] coding, data analysis, all without
[0:40] touching a single line of code. You'll
[0:42] see which version to use when thinking
[0:44] mode actually matters and whether you
[0:46] can finally ditch your Chat GPT or
[0:49] Gemini subscription. So, let's go. So,
[0:51] here's the situation. Back in January,
[0:53] Deepseek made headlines with their R1
[0:55] model. cheap to train, open source,
[0:57] performed like the big boys. Then
[0:59] everyone moved on. Open AAI launched
[1:02] GPT5. Google dropped Gemini 3 Pro. The
[1:06] hype cycle kept spinning and Deepseek
[1:08] just kept building. On December 1st,
[1:10] 2025, they quietly released version 3.2
[1:14] and the benchmarks are wild. 96% on the
[1:18] American Invitational Mathematics
[1:20] Examination. That's M, one of the
[1:22] hardest math test on the planet. For
[1:24] context, GPT5 High scored 94.6. Deepseek
[1:28] beat it. On the Harvard MIT math
[1:30] tournament, Deepseek hit 99.2%.
[1:33] Gemini 3 Pro scored 97.5.
[1:36] Again, Deep Seek wins. But here's the
[1:39] thing. This isn't just one model.
[1:41] Deepseek V3.2 comes in two flavors.
[1:44] Standard V3.2, which is your everyday
[1:47] workhorse. Fast, reliable GPT5 level
[1:51] performance. Think of it as your Chad
[1:53] GBT replacement. Then there's V3.2
[1:56] Speciial. And Special is the beast.
[1:58] Maxed out reasoning, deep chain of
[2:01] thought. This thing won gold medals at
[2:03] the International Mathematical Olympiad,
[2:06] the International Olympiad in
[2:07] Informatics, second place at the ICPC
[2:10] World Finals. We're talking elite
[2:12] competition level AI. And here's what
[2:14] makes this release different. Deep Seek
[2:16] V3.2 2 is the first model to integrate
[2:20] thinking directly into tool use. Most AI
[2:23] models lose their train of thought every
[2:25] time they call an external tool. They
[2:27] have to restart reasoning from scratch.
[2:29] Deepseek preserves the reasoning trace
[2:32] across multiple tool calls. That means
[2:34] smoother workflows, better agent
[2:36] performance, and way more reliable
[2:38] multi-step problem solving. Now, there
[2:40] is one catch with special. It's API only
[2:43] right now and that API endpoint expires
[2:46] December 15th, 2025. Why? Because it's
[2:49] token hungry. To solve one code forces
[2:52] problem, Special uses 77,000 tokens.
[2:55] Gemini uses 22,000. The inference costs
[2:58] are insane. So, Deep Seek is treating
[3:00] Special as a research preview. After
[3:02] December 15th, they'll likely roll it
[3:05] into a more efficient production version
[3:07] or just keep the standard model as the
[3:09] main offering. But the standard V3.2 too
[3:12] that's available right now free on the
[3:14] web on mobile open source under an MIT
[3:17] license no credit card no limits and it
[3:20] performs at GPT5 level this isn't a toy
[3:23] this is production ready AI let me break
[3:26] down the two models so you know which
[3:27] one to use standard V3.2 2. This is the
[3:30] daily driver. It scored 93.1% on Emmy
[3:34] 2025. Code forces rating of 2386.
[3:38] That puts it in the top 1% of
[3:40] competitive programmers globally. It's
[3:42] fast, it handles tool use, and it's free
[3:45] via the web interface at
[3:46] chat.deseek.com.
[3:48] Use this for writing, brainstorming,
[3:50] quick analysis, code, and tasks, and
[3:52] anything you'd normally throw at chat
[3:55] GPT. Then there's V3.2 special. This is
[3:58] the high compute reasoning monster. 96%
[4:02] on Amy, 99.2 on the Harvard MIT math
[4:05] tournament, gold medals at IMO, IOI,
[4:08] ICPC, and the Chinese math Olympiad.
[4:11] Special is designed for deep reasoning,
[4:14] multi-step proofs, complex research,
[4:16] heavy analysis, but it doesn't support
[4:18] tool calling right now. It's pure
[4:20] thinking mode, and it's only available
[4:22] through the API until December 15th. Why
[4:25] can't you install Special locally yet?
[4:28] It's in a research beta phase. The model
[4:30] is publicly available on hugging phase,
[4:32] but running it requires serious
[4:35] hardware. 671
[4:37] billion parameters total, but only 37
[4:40] billion active per token thanks to the
[4:43] mixture of experts architecture. You'd
[4:45] need multiple high-end GPUs and
[4:48] distributed compute to run it smoothly.
[4:50] The standard V3.2 too. It's easier to
[4:54] self-host if you've got the hardware,
[4:56] but for most people, the web interface
[4:58] is the way to go. Rule of thumb,
[5:00] standard for speed, special for depth.
[5:02] But since Special is temporary and API
[5:05] gated, I'm going to focus this tutorial
[5:07] on the standard V3.2 model, which is
[5:10] what you can actually use today without
[5:12] jumping through hoops. All right, let's
[5:14] get you set up. This takes about 60
[5:16] seconds. Step one, open your browser and
[5:19] go to chat.deseek.com.
[5:21] You'll see a simple landing page. Click
[5:23] sign up. I just used the Google signin
[5:25] option. One click. No password to
[5:27] remember. Done. Step two. Once you're
[5:29] in, you'll see the main chat interface.
[5:32] The prompt box is right in the center.
[5:34] Below it, you've got two toggles. One
[5:36] says deep think. That enables extended
[5:39] reasoning mode where the AI thinks
[5:41] through your problems step by step. The
[5:44] other toggle is search, but as of right
[5:46] now, it's not reliably working. When it
[5:49] does work, it functions like Chad GBT's
[5:51] web search, but don't rely on it yet.
[5:53] You also see a file upload button.
[5:56] Deepseek is multimodal. You can upload
[5:58] text files, spreadsheets, PDFs, images.
[6:01] It'll extract the text and work with it.
[6:03] No video or audio support yet, but for
[6:06] documents and data, it's solid. On the
[6:08] left side, you've got your chat history.
[6:10] You can rename or delete chats by
[6:12] clicking the three dots next to each
[6:14] one. There's also a QR code button to
[6:17] download the mobile app, which I'll show
[6:18] you in a second. Step three,
[6:20] understanding the interface. In normal
[6:22] mode, Deep Seek gives you a
[6:24] straightforward answer. Simple, clean,
[6:27] fast. But when you enable deep think,
[6:29] something interesting happens. The AI
[6:32] thinks for several seconds first. You
[6:34] literally watch its thought process
[6:36] unfold in real time. Then it delivers
[6:39] the final answer. This is where you see
[6:41] the reasoning chain, the trade-offs.
[6:42] it's considering the logic behind its
[6:44] response. Step four, enable deep think
[6:47] when you need it. If you're doing
[6:48] something simple like writing an email
[6:50] or brainstorming ideas, leave it off.
[6:53] The model responds faster. But if you're
[6:55] working on complex problem solving,
[6:57] research, or multi-step tasks, turn on
[7:00] Deepthink. The model will take longer to
[7:02] respond, but the quality goes way up.
[7:05] Pro tip: Prompt in English or Chinese
[7:07] only. Deepseek's training is optimized
[7:09] for those two languages. Other languages
[7:11] go through a translation layer and the
[7:14] results can be hit or miss. If you need
[7:16] the output in another language, prompt
[7:18] in English first, then ask DeepSk to
[7:21] translate the final answer. That's it.
[7:23] You're set up. Now, let's put this thing
[7:25] to work. This is where it gets
[7:26] interesting. I'm going to show you five
[7:28] real use cases. Some are practical, some
[7:32] are just fun. All of them work without
[7:34] coding, without APIs, and without local
[7:36] installs. Just your browser and a
[7:38] prompt. Let's start with writing. I'm
[7:41] going to ask Deepseek to create a long
[7:43] form article outline. I'll turn on deep
[7:46] think so it thinks through the structure
[7:49] prompt. Create a detailed outline for a
[7:51] 2,000word article on remote work
[7:53] productivity. Include five main
[7:55] sections, each with three sub points.
[7:58] Target audience is freelancers and small
[8:00] business owners. Make it actionable.
[8:02] Watch what happens. Deepseek thinks
[8:04] first, breaking down the prompt. It's
[8:07] identifying the audience, thinking about
[8:08] pain points, structuring the flow. Then
[8:11] it delivers a clean, hierarchical
[8:13] outline with specific subtopics. No
[8:16] fluff, just structure. This is where
[8:18] Deep Seek shines for content work.
[8:21] You're not just getting an answer.
[8:22] You're seeing the reasoning. And if you
[8:24] don't like a section, you can ask it to
[8:26] revise just that part without starting
[8:28] over. Here's something cool. We've been
[8:30] using Deep Seek for text, but what about
[8:33] video? Because that's the other part of
[8:35] content creation. most people struggle
[8:37] with. I've been testing Luma AI's RA3
[8:40] modify for the visuals in this video.
[8:42] And the workflow is honestly
[8:44] fascinating. It's not just type a prompt
[8:46] and hope for the best. There is this
[8:48] reasoning engine built in that actually
[8:50] thinks through what you're trying to
[8:52] create before it starts generating.
[8:54] Here's how it works. You either type a
[8:56] detailed prompt or upload an image as
[8:59] your starting point. Ray 3 modify
[9:01] analyzes your creative intent, figures
[9:03] out the physics, lighting, motion paths,
[9:06] all of that. Then it gives you two
[9:08] generation modes. Draft mode, which is
[9:10] incredibly fast and cheap. Use that to
[9:12] experiment and iterate. Once you nail
[9:15] the concept, you upscale to hi-fi 4K HDR
[9:19] for your final render. But the real game
[9:22] changer, it's visual annotation. Instead
[9:24] of writing a 10-line prompt trying to
[9:26] describe motion, just draw on the image.
[9:30] Circle an object, draw an arrow showing
[9:32] how you want it to move. Ray 3 modify
[9:35] handles the rest. The physics, the
[9:37] lighting transitions, the camera work,
[9:39] it all just works. I tested this with a
[9:41] product demo concept. Started in draft
[9:44] mode, tweaked the motion a few times,
[9:46] then rendered the final 4K version. The
[9:49] output was clean enough to use straight
[9:51] out of the box. no post-processing. And
[9:54] compared to other AI video tools I've
[9:56] tried, this one actually preserves
[9:58] anatomy and handles complex motion
[10:00] without the usual AI artifacts. If
[10:03] you're building content, product videos,
[10:05] or anything visual, Ray 3 modify is
[10:08] worth trying. You can find it at
[10:09] dreamachine.lumalabs.ai.
[10:12] They give you credits to start so you
[10:14] can test draft mode and visual
[10:16] annotation yourself. Link below. All
[10:18] right, back to Deep Seek. Now, let's
[10:20] test file handling. I'm going to upload
[10:22] a sample CSV file with sales data. Then
[10:25] I'll ask Deepseek to analyze it. Prompt:
[10:28] Analyze this sales data. Give me the top
[10:30] three insights and identify any
[10:32] concerning trends. Deepseek reads the
[10:34] file, processes the data, and returns a
[10:37] structured summary. It highlights that
[10:39] Q3 revenue dropped 15%, identifies the
[10:43] underperforming product category, and
[10:45] flags a regional sales dip. All in plain
[10:48] English. No pivot tables, no formulas,
[10:51] just insights. You can also upload PDFs
[10:54] and ask for summaries, key takeaways, or
[10:57] specific extractions. For research work,
[11:00] this is a massive timesaver. All right,
[11:02] this is the showstopper. I'm going to
[11:04] show you three things you can build in
[11:06] Deep Seek right now. No coding knowledge
[11:08] required. These are instant playable
[11:11] visual demos. First, let's start with
[11:14] something fun. generating a simple
[11:16] JavaScript game and playing it right
[11:18] inside DeepSseek prompt. Create a simple
[11:21] snake game in HTML and JavaScript that I
[11:24] can play right now. Deepseek writes the
[11:26] code. A preview button appears. I click
[11:29] it. Boom. The game loads in the
[11:31] interface. I'm playing Snake inside the
[11:34] AI chat window. No libraries, no
[11:37] installs. 15 seconds from prompt to
[11:40] playable game. Now, let's take it a step
[11:42] further and build a simple space shooter
[11:44] arcade game. Prompt: Build a simple
[11:47] space shooter arcade game with HTML 5
[11:50] canvas. Make it playable. Again, Deep
[11:53] Seek generates the code. I hit preview.
[11:55] The game loads. I'm firing shots at
[11:58] targets. It works. Chad GPT would give
[12:01] you the code and tell you to paste it
[12:02] somewhere. Deep Seek lets you run it.
[12:05] And now, let's switch gears and create a
[12:07] simple to-do list app. Prompt. Create a
[12:10] to-do list app with add and delete
[12:12] functionality. Full web app, interactive
[12:14] UI. I can add tasks, delete tasks, check
[12:17] them off. It's live. It's functional.
[12:20] And I didn't write a single line of
[12:22] code. Now, before I move on to comparing
[12:24] Deep Seek with CHG GBT and Gemini, let
[12:26] me show you something that we've built.
[12:28] While you're learning DeepS or any AI
[12:31] tool for that matter, I can't stress
[12:33] enough how helpful it is to have
[12:35] everything in one place. That's exactly
[12:38] why I built AI Master Pro. It's an
[12:40] all-in-one AI hub where you're not just
[12:43] watching tutorials. You're actually
[12:44] applying what you learn in real time.
[12:47] Here's what's inside. The AI Master
[12:49] Method course which walks you through AI
[12:51] foundations, workflows, and how to
[12:53] actually sell AI services. Over a 100
[12:56] lessons, templates, PDFs, everything you
[12:58] need to go from beginner to building
[13:00] real AI products in four weeks. But the
[13:03] course is just the starting point. What
[13:04] I actually use every single day are the
[13:07] AI tools built right into the platform.
[13:09] There's a personal AI master trained on
[13:12] unique data that can teach you anything
[13:14] about AI 24/7. You can generate
[13:17] highquality prompts on the fly and with
[13:20] integrated tools like Sora, VO, Nano
[13:23] Banana directly into the platform. So if
[13:26] you join before the end of 2025, you
[13:29] will get bonus generation credits. You
[13:31] also get Prompt Lab Pro, 300 plus
[13:34] readyto-use prompts you can copy and
[13:36] paste, discounts on other AI tools, and
[13:38] a curated weekly AI digest so you never
[13:41] fall behind on what's new, so you can
[13:44] learn AI and use AI in the same place.
[13:47] No tab switching, no trying to remember
[13:50] which tool does what. Everything's
[13:52] organized. Everything's accessible and
[13:54] honestly, I'm on the platform every
[13:56] single day. If you want to check it out,
[13:58] we're offering a huge discount for the
[14:00] first thousand people who join the
[14:02] annual plan. Link below. All right, back
[14:04] to Deepseek. Let's push it harder. I'm
[14:07] going to give Deepseek a multi-step
[14:09] business problem and watch how it
[14:11] handles it. Prompt: I'm launching a
[14:13] subscription software product. Price is
[14:15] $49 per month. Target market is
[14:18] freelancers. I need a six-month growth
[14:21] plan. include customer acquisition
[14:23] strategy, price and experiments, and
[14:25] retention tactics. Show your reasoning.
[14:28] With Deepthink on, Deep Seek spends
[14:30] about 6 seconds thinking. It's breaking
[14:33] down the problem, customer personas,
[14:35] acquisition channels, pricing,
[14:36] sensitivity, retention metrics. Then it
[14:40] delivers a structured six-month plan
[14:42] with specific action items for each
[14:44] month. This is where the extended
[14:46] reasoning really pays off. You're not
[14:48] getting a generic answer. you're getting
[14:50] a plan that actually considered
[14:52] tradeoffs. Finally, let's test tool use.
[14:55] This is where V3.2's new architecture
[14:58] shines. I'm going to ask it to calculate
[15:00] compound interest and show me the
[15:02] formula step by step. Prompt, calculate
[15:05] the compound interest on $10,000
[15:08] invested at 5% annually for 10 years.
[15:11] Show each step of the formula and the
[15:14] final result. Deepseek doesn't just give
[15:16] me the answer. It breaks down the
[15:18] formula. explains what each variable
[15:20] means, shows the calculation at each
[15:23] step, then gives the final number in a
[15:25] clean box. This is thank plus tool
[15:28] execution in one flow. For anyone doing
[15:30] research, analysis or learning, this is
[15:32] huge. You're not just getting results.
[15:34] You're seeing the work. Let's talk
[15:36] honestly. Can Deepseek actually replace
[15:39] Chat GPT or Gemini? The answer is it
[15:42] depends. Here's where Deepseek wins.
[15:44] Cost. Deepseek Chat is free, but API
[15:47] usage is paid. Chat GPT Plus is $20 a
[15:50] month. Claude Pro is 20. Google AI Pro
[15:53] with Gemini is about $19.99 per month in
[15:57] the US and around €21.99
[16:00] per month in Germany. Varies by region
[16:02] and taxes. If you're just using the chat
[16:04] interface, Deep Seek cost you nothing.
[16:07] Transparency. Deepseek often shows you
[16:09] the visible thinking process. Chad GPT
[16:12] and Gemini usually show the result and a
[16:14] brief explanation without the full chain
[16:17] of thought for learning debugging or
[16:19] understanding why you got a certain
[16:21] answer. Deepseek's transparency is a
[16:24] massive advantage. Math and reasoning.
[16:26] Deepseek R10528
[16:29] scores 87.5%
[16:31] on Me 2025 while GPT5 reports 94.6%
[16:36] without tools. So GPT5 is ahead, but
[16:39] Deep Seek is still very strong. If
[16:42] you're doing data analysis, research, or
[16:44] technical problem solving, Deep Seek
[16:46] holds its own against most models. Open
[16:49] weights. You can download the weights,
[16:51] run locally, and use commercially
[16:53] depending on the license. No vendor
[16:55] lockin. For businesses worried about
[16:57] data sovereignty, that's a big deal.
[17:00] Here's where Chad GPT and Gemini still
[17:02] win. Polish. Chad GBTs and Gemini's
[17:05] interfaces are more refined, better
[17:07] onboarding, smoother UX. Deep Seek feels
[17:10] more utilitarian integrations. Chad GPT
[17:14] has GTS with tools and actions, built-in
[17:17] image generation, browsing, data
[17:19] analysis. Gemini integrates with Google
[17:21] Workspace. Deepseek is bare bones. You
[17:24] get the model. That's it. Stability.
[17:27] Deep See can show server busy messages
[17:30] during peak demand. Paid incumbents
[17:32] often feel more consistent, but no
[17:34] service is immune to outages. Custom
[17:36] instructions. Chat GPT has account level
[17:39] custom instructions. Deepseek doesn't
[17:41] yet offer the same kind of persistent
[17:44] personalization in its chat UI, at least
[17:46] not at the same level. Here's my honest
[17:48] take. Can you replace chat GPT or Gemini
[17:51] entirely? If you're doing writing,
[17:53] research, analysis, and coding, yes,
[17:55] absolutely. Deep Seek is good enough. If
[17:57] you rely heavily on GPTs, need
[17:59] guaranteed uptime, or want a more
[18:02] polished experience, not yet. But for
[18:04] 80% of tasks, Deep Seek is shockingly
[18:07] capable and it's free to use. Let me
[18:09] show you a quick side by side. Same
[18:11] prompt, both models. Prompt: Explain how
[18:15] to improve website conversion rates in
[18:17] five steps. Chad GPT gives a clean,
[18:20] structured answer. Five steps, good
[18:22] advice. Deepseek gives a clean,
[18:25] structured answer. five steps. Also,
[18:28] good advice. In this quick test, the
[18:30] quality looks nearly identical. For most
[18:32] everyday tasks, the performance gap is
[18:35] minimal. The question is whether you
[18:37] value the Chad GPT or Gemini ecosystem
[18:40] or whether you just need a smart AI that
[18:43] gets the job done. Now, let's talk about
[18:45] prompting because the way you ask
[18:46] matters. Deepseek isn't Chad GPT. It has
[18:49] quirks and if you learn them, you'll get
[18:52] way better results. Tip one, formatting
[18:54] matters. If you're doing something
[18:56] complex, structure your prompts with
[18:59] clear sections. Deepseek responds
[19:01] incredibly well to markdown style
[19:03] formatting. Here's the template I use
[19:05] for any non-trivial task. Task colon
[19:08] what you want. Constraints colon any
[19:10] limitations. Output colon how you want
[19:13] the response formatted. For example,
[19:15] task analyze this sales report.
[19:18] Constraints focus on Q3 data only.
[19:20] Ignore outliers above $10,000. output
[19:24] bullet list with top three insights.
[19:26] Each insight under 50 words. Watch how
[19:30] clean that is. You've told the model
[19:31] exactly what to do, what to avoid, and
[19:34] what format you expect. No ambiguity, no
[19:37] back and forth. There's also a second
[19:39] format called think and answer. This
[19:42] one's powerful for reasoning tasks. You
[19:44] split your prompt into two sections
[19:46] using tags. The think section is your
[19:48] background context. The answer section
[19:51] is your specific request. Here's an
[19:53] example. Think I'm a freelance designer
[19:55] launching a new service. My target
[19:57] clients are small startups with budgets
[20:00] under $5,000. I need a pricing strategy
[20:03] that feels premium but accessible.
[20:06] Answer: propose three pricing tiers with
[20:09] specific dollar amounts and
[20:10] justifications for each. The thank
[20:12] section primes the model's reasoning.
[20:14] The answer section narrows the output.
[20:16] You get better, more tailored responses
[20:19] this way. Tip two, be hyper specific.
[20:22] Deep Seek needs detail way more than
[20:25] Chad GBT. Don't just say write an email.
[20:28] Say write a 200word professional email
[20:31] to a client named Sarah explaining a
[20:33] twoe project delay caused by supply
[20:36] chain issues. Tone should be apologetic
[20:38] but confident. Include a revised
[20:40] timeline and next steps. See the
[20:42] difference? You've given the model
[20:44] length, tone, recipient context, reason
[20:47] for the email and deliverables. Now, it
[20:49] has everything it needs to nail it on
[20:51] the first try. This applies to every
[20:53] task. If you're asking for a comparison,
[20:55] name both options and specify what
[20:58] criteria matter to you. If you're asking
[21:00] for a plan, state your constraints
[21:02] upfront. Time, budget, team size,
[21:05] whatever is relevant. Vague prompts give
[21:07] you vague answers. Specific prompts give
[21:10] you work you can actually use. Tip
[21:12] three, use personas. Tell Deepse seeek
[21:15] to act as someone. A career counselor, a
[21:17] financial analyst, a creative director,
[21:20] a systems engineer. This shapes the
[21:22] style and knowledge it brings to the
[21:24] response. Example, act as a senior
[21:26] product manager. Review this feature
[21:28] road map and identify the three biggest
[21:30] risks to hitting our Q2 launch date. The
[21:33] persona tells the model what lens to
[21:35] use. You're not just asking for generic
[21:37] feedback. You're asking for product
[21:39] management feedback. The output changes.
[21:41] I use this constantly for content work.
[21:43] Act as a copywriter specializing in
[21:46] landing pages. Rewrite this headline to
[21:48] be more benefit driven and under 10
[21:51] words. Boom. Focused output. No wasted
[21:53] tokens. Tip four. Ask for multiple
[21:56] approaches. Instead of asking how do I
[21:58] solve this problem, ask give me three
[22:00] ways to solve this problem with pros and
[22:03] cons for each. This forces the model to
[22:05] think deeper and consider trade-offs.
[22:07] You're not getting one solution. You're
[22:09] getting options. and options let you
[22:11] make better decisions. Example, I need
[22:13] to grow my email list by 5,000
[22:16] subscribers in 3 months. Give me three
[22:19] strategies. One, high effort, high
[22:21] reward, one loweffort, lowreward, and
[22:24] one experimental. Include estimated time
[22:27] commitment and success probability for
[22:29] each. That prompt gives you a strategic
[22:31] breakdown, not just ideas, evaluated
[22:34] ideas. Tip five, request selfch checks.
[22:37] After getting an answer, ask what are
[22:39] the potential risks with this approach?
[22:42] Or what assumptions are you making here?
[22:44] Deepseek's reasoning mode makes this
[22:46] especially powerful. You'll literally
[22:48] see it questioning its own logic. This
[22:50] is how you catch blind spots before they
[22:52] become problems. I do this on any high
[22:54] stakes task. Legal advice, ask for
[22:57] risks, financial projections, ask for
[22:59] assumptions, strategic plan, ask what
[23:02] could go wrong. The model will walk
[23:04] through failure modes you might not have
[23:06] considered. Tip six, placeholders for
[23:09] templates. If you're writing something
[23:10] reusable like an email template or a
[23:13] sales script, use placeholders. Prompt,
[23:15] write a cold email to potential clients,
[23:18] use company name, your name, and product
[23:21] name as placeholders. Then in the
[23:23] response, every mention will use those
[23:25] brackets. You just find and replace
[23:27] later. This is huge for batch work. And
[23:30] by the way, if you want 300 plus prompts
[23:32] like this already written and ready to
[23:34] copy paste, check out Prompt Lab inside
[23:37] AMS Pro. I use them constantly.
[23:40] Everything from freelance templates to
[23:42] business automations saves me hours
[23:44] every week. Tip seven, comparison
[23:46] prompts. One thing I love doing is
[23:48] setting up a pros cons list and then
[23:51] asking the model to pick the best option
[23:52] for a specific situation. Example,
[23:55] compare working from home versus
[23:56] co-working spaces. Give me five pros and
[23:59] five cons for each. Then recommend which
[24:01] one is best for a freelance software
[24:04] developer with a tight budget and no
[24:06] team. You get both the analysis and the
[24:08] recommendation. And because DeepSeek
[24:10] shows its reasoning, you can see exactly
[24:12] why it picked one over the other. Tip
[24:14] eight, iterate without fear. The first
[24:16] response is rarely perfect. Follow up.
[24:18] Make that more concise. Revise the
[24:20] second paragraph to be less formal. Give
[24:22] me a version that's more data driven.
[24:24] The back and forth is how you dial in
[24:26] exactly what you need. Don't treat the
[24:29] first output as final. Treat it as a
[24:31] starting point. Let me show you a quick
[24:33] before and after. Bad prompt. How do I
[24:35] market my product? Result from deepseek.
[24:38] Vague, generic advice, social media,
[24:40] email marketing, maybe try ads. Nothing
[24:43] you couldn't Google in 5 seconds. Good
[24:46] prompt. I'm launching a B2B SAS product
[24:48] for small marketing teams. Budget is
[24:51] $5,000 for the first quarter. What are
[24:54] three lowcost customer acquisition
[24:56] channels I should test and what metrics
[24:58] should I track for each result from
[25:00] deepseek specific actionable advice
[25:03] LinkedIn organic outreach with reply
[25:06] rate as the key metric content marketing
[25:09] via SEO optimized blog posts track and
[25:12] domain authority and organic traffic
[25:14] partner referrals with conversion rate
[25:16] and cost per acquisition clear next
[25:18] steps for each that's the difference
[25:20] specificity wins every time is this to
[25:23] Chad GBT or Gemini Killer? No, it's an
[25:25] alternative. For most people, it's good
[25:27] enough to save $240 a year. The real
[25:30] question is this. Do you actually need
[25:32] Chat GPT's ecosystem or Gemini's Google
[25:35] Workspace integration, or do you just
[25:37] need a smart AI that writes well,
[25:40] reasons clearly, and handles data? If
[25:42] it's the latter, Deepseek delivers. My
[25:44] recommendation, try it for one week. Use
[25:47] it for your actual work, writing,
[25:49] research, analysis, whatever you
[25:51] normally throw at Cad GBT or Gemini. See
[25:53] if you miss anything. I'm betting most
[25:55] of you won't. And if you do need Chat
[25:57] GBT for specific GPTs or Gemini for
[26:01] Google integration, fine. But use
[26:03] Deepseek for everything else. There's no
[26:06] reason to pay for tasks a free model can
[26:08] handle just as well. One more thing, the
[26:11] fact that this model is open weight
[26:13] matters. You can download it, you can
[26:15] modify, you can run it on your own
[26:17] hardware. If you've got this setup for
[26:19] developers, researchers, and businesses
[26:22] building AI products, this is a
[26:24] gamecher. You're not locked into OpenAI
[26:27] or Google. You've got options now. And
[26:30] if you want more AI tools like this,
[26:32] free, powerful, and actually useful,
[26:34] subscribe. I test these every week and
[26:37] break them down so you can start using
[26:38] them right away. And if you are serious
[26:41] about mastering AI beyond just one tool,
[26:44] check out AI Master Pro in the
[26:46] description below. That's where I keep
[26:47] all my workflows, prompts, and training
[26:49] in one place. And see you next time.