funny thing, my original loader doesn’t use keyframes. it... just loops opacity with a per‑pixel delay array + a duration param. less flexible than keyframes, but gives a different effect here is one example in case you want to try to understand it hahah: { name: 'wave-lr', // Delay in ms before each of the 9 grid cells starts animating, indexed as [0,1,2], [3,4,5], [6,7,8] delays: [0, 100, 200, 0, 100, 200, 0, 100, 200], // How long (ms) each cell takes to fade in/out duration: 600, ]show more

Another crazy TypeSafe AI Jev example: Predictive spreadsheets Spreadsheets... recalculate numbers, not meaning. Jev reads intent. Type "Urgency" at the top of a column and, as you type, it figures out you want each row rated from "no follow-up needed" to "urgent" in ~100 ms.show more

004/100 Buttons. A bit of the process on building... an animation. When looking at a finished animation or in this example a finished button, it can look quite complex inside the CSS. But when building it, it’s more like a lot of simple steps, one after another. Here I had the idea to make some kind of text animation like the footer logo on the Osmo site. I try to add the base animation with no complex easing, for example transition: translate 0.4s ease. Starting with just moving the one text from bottom to top and the other text to top. Adding a stagger, play around with it. Searching for a way to make it more circular. On the research I found the sin() function inside CSS which can build a more smooth non linear curve for the stagger which creates this circular effect. And step by step adding more complexity like, different easing for hover/hover-out, opacity, 3D transform and more. I use also the sin() function to rotate the letters, so the middle ones are getting more rotated than the outer ones. Another thing which helps is to add a small delay on hover, for example 0.05s or 0.1s, you don’t really see the difference, but when you hover pretty fast on and out it doesn’t get that jumpy. I’m using here GSAP’s SplitText to split every char into spans. And then I’m adding a CSS index variable to every span, starting from the center. SplitText can provide CSS index variables, but you cannot tell it from which direction. For the sin() it’s also important to have a max length, so I add another CSS variable with the max char number on it. Crafting 100 Buttons with Osmo ⏳ Total time: 63hshow more

This may take a bit of practice before you... can do it, but it’ll be 100% worth it 😊 And as always, hearing a crack is not necessary, you’ll experience the healing effects of exercises like this without hearing a crack as well Tired of waking up in pain, feeling stiff with bad posture, and never managing to finally get flexible? Start fixing all of that in less than 7 days with stretching routine specially made for beginners with no equipment needed — link in bio ✅show more

this creator just built a zero-delay auto-aim system on... an $8 microcontroller he deployed a custom local AI algorithm on a cheap ESP-32 to track human movement with absolute 0-pixel accuracy. the system completely eliminates standard computation delay. it processes the bounding box and moves the sniper reticle instantly, locking onto the target in real time. the next step is hooking it up to a physical robotic arm. it proves you don't need a massive GPU rig to run complex computer vision. 1. runs locally on a microcontroller 2. local AI inference for zero latency 3. 100% targeting precision when an eight-dollar chip can track movement with zero latency, AI becomes dangerous local infrastructure. this article breaks down exactly how the ESP-32 is powering this physical hardware shift.show more

I just built a complete SEO audit plugin in... Claude Code that replaces your $200/mo Ahrefs subscription 🤯 One Claude Plugin audits any store: technical SEO, product schema, content, Core Web Vitals, and AI-search readiness. Parallel agents, a 0-100 score, and a dashboard that renders right in the panel. All inside Claude Code. So I pointed it at Ridge .com, one of the sharpest DTC operators out there. It came back 56/100, and what stood out wasn't a knock on them at all: Ridge has a better AI-commerce setup than 99% of stores. A real llms.txt, an agent-discovery sitemap, a live MCP endpoint, genuinely ahead of the curve. And even on a store that dialed-in, the audit surfaced fixable gaps in ~90 seconds: → Room to add product structured data → A mobile Core Web Vitals score worth tightening → A thin meta description on a high-traffic collection Perfect for e-comm operators and SEO agencies who are sick of paying $200/mo for tools that bury the real issues, running quarterly audits that take a week, and shipping reports nobody can act on. So I put together the full playbook to build your own. The complete guide to building this Plugin in Claude Code: branded to you, tuned to exactly how you audit, repeatable across every client. The kind of audit you run in minutes and hand over as a deliverable that looks like it cost thousands. What's inside: → The architecture (orchestrator + parallel sub-agents) → How to fetch any store past Cloudflare → The 0-100 scoring + falsifiable-findings framework → How to ship the HTML dashboard for client demos → The full build, start to finish Want the playbook for free? > Like this post > Comment "SEO" And I'll send it over (must be following so I can DM)show more

Behind the Scenes: How I prompted 3 scenes in... 1 try on Seedance 2.0! Sharing my workflow of all my prompts for hopeless steve so you can see what were SD2 choices and what needed to be prompted. You can see how much more streamlined it is to go from one scene to the next when you can have 9 ref img's to work with. The prompt is only for the one that generated the most useful footage for each part. Scene 1, 2, 3 - 15s Ref: 1. House Ext. 2, Steve profile 3. Steve on the computer in the bedroom 4. mother cooking in kitchen. (The references a numbered so you know what the prompt is refering to.) Prompt: American sitcom style cartoon about Steve【@图片2】. Must maintain 100% fidelity to the art style and all character traits. No background music. [0:00-0:02] Wide establishing shot of the exterior of the house【@图片1】. Camera slowly zooms but remains in the wide shot. [Cut: 0:02-0:03] Interior wide shot of steve looking bored at computer 【@图片3】. No dialogue. [Cut: 0:03-0:05] Over the shoulder shot from behind steve. We see his monitor as he plays solitaire. We hear subtle mouse clicks and sound of cards as he drags and places them into the collumns. [Cut: 0:05-0:07] Side profile of Steve continuing to play solitaire on the computer. [Cut: 0:07-0:09] 【@图片4】Extreme close up of the mother's spatula flipping an egg over in the pan. [Cut: 0:09-0:11] Medium shot 【@图片4】 as the mother calls frustratedly, "Steve, breakfast is ready." [Cut: 0:11-0:12] Extreme close up in 【@图片4】of the mother's hand as she turns the stove off. [Cut: 0:12-0:13] 【@图片4】Extreme close up of the mother narrowing her eyes disgruntled. [Cut: 0:13-0:15] 【@图片4】 Medium shot as mother walks out of left of frame. Stationary camera.show more

Opposition in the batters box isn't just a layer... of complexity, an obstacle to overcome, it is the central feature that gives meaning to movement. My sense is that many in the baseball community view the live batter as a linear step to master after mastering other lower complexity pieces, instead of the central feature that we design our training environments around. Part of me understands why this is the case. Pitching is in a challenging place training wise because the behavior of pitches, movements, etc. change so much when you go low effort. In addition we have some limits on volume each day due to throwing being the single fastest movement in sports. Other sports can do unique warmups to work on interpersonal distance (football/basketball/soccer) and tagging games for more of a martial arts context. I simply can't have all 100 throws of a pitchers workload that day be to a live batter. And while I see value in pulling an athlete out of context at times to work on different things, ultimately, the entirety of my paradigm to train pitchers is how to do the real thing MORE, to keep them embedded in a representative environment, rather than treating it as the final step in a linear progression.show more

Every AI tool claims it’ll save you time. Most... just shift the workload somewhere else. Viktor is different ....it actually takes work off your plate. This week, I watched it work more like a real teammate than another chatbot sitting inside Slack. It understands context, takes ownership of tasks, and keeps things moving without constant instructions. That’s the real difference: you don’t just use Viktor. You delegate to it. Try Viktor for your team. Get $100 in credits with no card required. Full link in the first comment. Paid Partnershipshow more

the system our agency uses to produce ad creatives... for paying b2b clients is now written down in a free doc. it's a claude code build. one intake form takes the icp, pain, offer and cta, and it returns 100+ finished meta statics, each one a different concept with the message designed inside the artwork. the doc is the full build, not a summary: > all 20 prompts in build order, each a complete brief you paste as written > the 80-entry template and visual metaphor library, with the seed entries claude code expands for you > the fire-and-forget layer, so batches finish with the laptop closed and archive themselves before provider links expire > a worked example from a real ad copy to a folder your media buyer can upload straight to ads manager the wall in this video came off one run. the whole build takes about 2 hours. like + comment "ENGINE" and i'll dm you the doc. (following + rt for priority access)show more

While I have premium I definitely want to do... a long post breaking down the main scene from this show that I obsess with. There's so much that I feel could be learned from it. Not just for expansion animators either. There's honestly a LOT that can be learned from how this show directed its expansion scenes that can be applied to even safe for work animations. Obviously yes, the expansion alone is really good. What makes it so good though is just the fact that there's things you pick up on that you likely don't even realize until you re-watch. I'm using this scene as an example as it's not AS good I would say, but it still has a lot going for it. One thing I've always loved from it that I want to use in my own animations someday is that the expansion sort of comes in waves as opposed to one consistent growth. In a way, it makes it feel more natural while also selling how tight the top is getting. It could have been accompanied by showing the knot getting tighter or smaller with each growth. It's a small part of the animation but just that one thing already adds another layer to appreciate. It's not like most expansion scenes where there's very little outside of just "growing" on its own. There's a bunch of little things that subtly improve it without being obnoxious. The first expansion scene has WAY more that I want to talk about honestly. Far more than this one has. It will probably be a really long post now that I think about it...show more

This is gonna be so long omg but when... it comes to translating in Korean, it’s very very important to take in consideration of 1) Culture 2) Seniority, the Closeness & Intimacy of the people involved in a conversation. Because this gives an entire different vibe for the context. And we have to keep in mind that there are Korean phrases and expressions that simply don’t have just One way, exact words that can be translated in English. Translators can find ways to convey the meaning, but it requires more explanation and understanding of the context while conveying it, and not relying on assumptions. How about “인상 덜 쓰기” or “인상 쓰다“ then? Here, a direct translation can simply be 인상 덜 쓰기 - be less grumpy/ frown less, etc 인상 쓰다 - being grumpy, frown, make a face, etc Here, I include an educational video of an English speaker talking with a Korean speaker where they’re discussing a similar expression, “인상 좀 쓰지마!“ (which in word by word in English, it sounds something like “Don’t frown/ Don’t make a face”) Now, as an English speaker, that sounds a bit harsh doesn’t it? That’s because such expression doesn’t exist in just One interpretation in English, so if we only read it as it is, without considering the context and the speakers’ closeness, we’re bound to misunderstand the context. Quoting some parts of this video, 💚: “Now, Tyler’s expression for today is ‘인상 좀 쓰지마!’. Have you ever heard of this expression? 🩶: I’ve heard something like that before 💚: Then doesn’t this mean there’s a same expression in English too right? 🩶: Oh! I’ve only heard it in Korea 💚: Ah really? The guy then explained that if you say something like this in english, it can be rude. so it’s better not to say it in English-speaking countries. He gave examples like “If you do that, you’ll get wrinkles”, and the other guy added something like “If you make an ugly face, you’ll have wrinkles” and said that “If someone (an English speaker) hears this they would think I must be crazy” Here, they’re talking about the cultural differences. A phrase like this, when expressed directly, without considering people’s closeness, and being translated exactly like that, would sound so negative to English speakers. *also notice how this phrase is being worded in various ways??? ‘HOW’ it can sound to someone, really depends on their culture, their closeness with the person, and context* So later on, he gave a few more examples like, “stop making such a long face”, and “stop wrinkling your forehead”. And concluded that: 💚: Well in that case, the phrase “인상 좀 쓰지마” is basically a phrase that doesn’t exist in English. 🩶: It’s an expression that we don’t use. It’s not that it doesn’t exist. (This part, he’s explaining that there’s no such a thing as word by word to explain this phrase in English, bcs we English speakers use different wordings that is more suitable for a situation’s nuances.) Then again, we have to consider speakers’ closeness as well because in Korea, it’s a huge thing. If you don’t understand how this works, you won’t understand the nuances of a conversation. You’re bound to misunderstand. If you refuse to understand it then, I don’t think you want to respect their culture. Because again, this is a huge thing.show more

[Discrete Fourier Transform] by Hand ✍️ In signal processing,... the Discrete Fourier Transform (DFT) is no doubt the most important method. But the math involved is extremely complex, literally, involving a summation over a complex number term e^(-iwt). I developed this exercise to demonstrate that underneath such complexity, DFT is just a series of matrix multiplications you can calculate by hand. ✍️ Once you see that, it should not surprise you that a deep neural network, which is also a series of matrix multiplications, with activation functions in-between, can learn to perform DFT to process and analyze signals so effectively. How does DFT work? [1] Given ↳ Signals A, B, and C in the 🟧 frequency domain: ◦ A = cos(w) + 2cos(2w) ◦ B = cos(w) + cos(3w) + cos(4w) ◦ C = -cos(2w) + cos(3w) ◦ Each signal is a weighed sum of four cosine waves at frequencies 1w, 2w, 3w, and 4w. ◦ We will apply Inverse DFT to convert the signals to time domain representations, and then demonstrate DFT can convert back to their original frequency domain representations. ↳ Signal X in the 🟩 time domain. X is sampled at 10 time points 1t, 2t, …, 10t: ◦ X = [-2.5, -1.8, 3, -0.7, -1.0, -0.7, 3, -1.8, -2.5, 5] ◦ Suppose X is also a weighted sum of the same four cosine waves, but we don’t already know their weights. We will apply DFT to discover them. [2] 🟧 Frequency Matrix (F) ↳ Write the coefficients of A, B, C as a matrix F. Each signal is a row. Each frequency is a column. ↳ A → [1, 2, 0, 0] ↳ B → [1, 0, 1, 1] ↳ C → [0, 1-, 1, 0] [3] Cosine → Discrete ↳ Sample from the continuous cosine waves at discrete time points 1t, 2t, 3t, to 10t. [4] Cosine Matrix (W) ↳ Write the samples as a matrix, Each frequency is a row. Each time point is a column. [5] Inverse DFT: 🟧 Frequency → 🟩 Time ↳ Multiply the frequency matrix F and the cosine matrix W. ↳ The meaning of this multiplication is to linearly combine the four cosine waves (rows in W) into time-domain signals (rows in T) using the weights specified in F. ↳ The result is matrix T, which are signals A, B, C converted to the time domain. Each signal is a row. Each time point is a column. [6] Transpose ↳ Transpose T, converting each signal’s time domain representation from a row to a column. [7] DFT: 🟩 Time → 🟧 Frequency ↳ Multiply the cosine matrix W with the transpose of matrix T. ↳ The purpose of this multiplication is to take a dot-product between each time-domain signal (columns in the transpose of T) and each cosine wave (rows in W), which has the effect of projecting the signal onto a cosine wave to determine how much they are correlated. Zero means not correlated at all. ↳ The result is an intermediate version of the “recovered” frequency matrix where each column corresponds to a signal and each row corresponds to a frequency. ↳ Compared to the original frequency matrix F, this intermediate matrix has non-zero weights in the correct places, but scaled up by a factor of 5 (n/2, n=10). For example, signal A, originally [1,2,0,0], is recovered at [5,10,0,0]. [8] Scale ↳ Multiply each value by 2/n = 1/5 to scale down the intermediate matrix to match the magnitude of the original frequency matrix F. [9] Transpose ↳ Transpose the recovered frequency matrix back to the same orientation of the original frequency matrix F. ↳ Like magic 🪄, the result is identical to the original F, which means DFT successfully recovered the frequency components of signals A, B, C. [10] Apply DFT to X: 🟩 Time → 🟧 Frequency ↳ Now that we have some confidence in DFT’s ability to recover frequency components, we apply DFT to X’s time-domain representation by multiplying W with X. ↳ The result is the an intermediate matrix. [11] Scale ↳ Similarly, we scale down by a factor of 5 to obtain the recovered frequency components of X (a column). [12] Transpose ↳ Similarly, we transpose the recovered column to row to match the orientation of the frequency matrix. ↳ Using the coefficients [0,0,3,2], we can write the equation of X as 3cos(3w) + 2cos(4w). Notes: I hope this by hand exercise helps you understand the essence of DFT. But there is more technical details, such as: • Sine: The complete DFT math also includes sine waves that follow a similar calculation process. • Phase: Here, we assume all the cosine waves are aligned at the origin, namely, phase is 0. If a phase p is added, for example, cos(w+p), we will need to calculate the sine component and use their ratio to figure out what p is. • Magnitude: If phase is not zero, the magnitude will need to be calculated by combining both cosine and sine terms.show more

OK COMPUTER collection is 100% fully onchain, obviously but... did u know within the nft itself we embedded an interactive terminal as well as a full-on 3d graphics engine? each bot also comes with their own unique generative artpiece, accessible by executing "run" in the terminal, amongst other fun terminal commands, try it out.. the best thing is: the terminal is *UPGRADEABLE*, which means future additions to the terminal is possible, stay tuned. all of this tech happening 100% onchain 🤖👌show more

you are COOKED if you can't make $20K+ per... month online in 2026 1. you can use AI to generate 300 posts in 15 minutes 2. you can get millions of views without spending a penny on ads 3. you can put words in a document and sell it 1000x for $50+ each 4. you can hire workers for $2.50/hr 100 years ago you needed your life savings just to START a business today you can start for free on your iPhone in seconds My 1.3 to 2.4 GPA teenager students that began working with me 10 months ago are making $30K–$80K+/month now I got a student Zain was earning minimum wage at a café in may 2025... now he's making $78K/month and bought an AMG Mercedes to help you guys , I've decided to LEAK the full recording of my $15M+ LIVE 20+ X Account Case Study printing $30K+ per month EACH for FREE for the next 24 hours 90 minutes. revealing X accounts making $1M+ per year (full case studies). usually $3K+ to access. what's inside: → 20+ case studies of Ai digital products accounts doing $30K+ per month EACH → the exact funnel generating $151K in 7 days on autopilot → how Parker did $570K in 3 months with one X account → why accounts with 6.5M followers make LESS than mine with 13K views → the DM automation sending 1000+ messages daily for free (send link to purchase ebook) → the copywriting crash course formula turning comments into $10K–$100K sales → how to hit $100K/month posting tweets that take minutes to write DELETING IN 24 HOURS comment "X" and I'll DM it to you **must be following + retweet to receive**show more

a real fly brain saw its 40th video 3... seconds ago. it did not choose any of them. it never will. that's FLYTOK. I open-sourced a live simulation of a real fruit fly connectome and gave it a phone. here's exactly what 166,700 neurons do while you scroll: THE WIRING MaleCNS v1.0. the reconstructed central nervous system of a real male Drosophila. 166,700 neurons. 25,582,938 directed connections. 124,177,617 synaptic contacts. nothing cropped. no "simplified 1,000-neuron version" running behind the scenes. the whole graph is in memory on every single step. THE LOCK the app checksums the connectome against SHA-256 before it's allowed to boot. one array off by a byte and the brain refuses to start. you are either watching the real MaleCNS graph or you are watching nothing. THE SPIKES every neuron is a leaky integrate-and-fire cell. crosses −45 mV, it fires. the spike lands 1.8 ms later. 2.2 ms of silence, then it's live again. the network advances in 0.1 ms steps inside a compiled C++ kernel. roughly 1.2 million spikes per simulated second. THE EYES the browser captures the phone at 90×160 pixels. brightness drives 3,335 R1–R6 photoreceptors. color drives 811 R8 cells, blue and green. each one is placed on the screen by inferring its eye column from its real connections onto L1, L2, L3. real input, through real visual wiring. it's measurable. same brain, same saved state. 100 ms of white produced 127,378 spikes. black produced 92,952. the screen changes the brain. THE ALGORITHM while a video plays, I inject a fixed current into all 15 PAM11 dopamine neurons in the mushroom body. that's it. that's the whole trick. matched 200 ms control: 0 PAM11 spikes. drive on: 261. live, it sits at 85–97 Hz for as long as the feed runs. the fly does not earn it. an app decided watching one more should feel good. THE PLASTICITY 7,835 Kenyon-cell connections onto MBON07 and MBON11 can change. dopamine fires while Kenyon cells were active, those synapses weaken, floored at 10% and never flipping sign. after one stimulated run, 3,087 of them no longer matched their original weight. freeze it and they stay put. restore a checkpoint, replay the input, identical spikes bit for bit. THE SWIPE every 3 seconds the front right leg reaches up and strokes the screen, on the same 900 ms timeline as the video transition. wings, legs and head turns come from actual motor firing, MN9, DNp09, left-vs-right DNa02. those are real. the swipe is not. the fly never decides to swipe. the feed decides for it. ONE BRAIN this isn't a video of a simulation. it's the simulation. there is exactly one brain on one server. whoever loads the page first becomes its eyes and supplies the frames. everyone else watches the same brain react in real time. no video, no input, it just waits. no data, no numbers, the overlay shows nothing. it never invents a reading to look alive. THE HONEST PART the wiring is real. the physiology is approximate. the eyes are approximate. the dopamine is artificial. the feed is on a timer. the learning rule is unvalidated on this connectome. nothing here shows the fly enjoys it, prefers it, is addicted, or experiences anything at all. no living fly was involved. it took a few hundred lines of glue code to build a loop out of a screen, a timer and a reward signal wired to the right cells. imagine what an industry with a budget can do. open source. MaleCNS under CC BY 4.0. runs on your own machine, 16 GB RAM and a few GB of disk. the fly is still scrolling. nobody is coming to take the phone away. links in the reply.show more

Jet Fuel is a fascinating story. We don’t measure... it in litres, we measure it in weight, because fuel expands/contracts with temperature while weight stays constant. Jet fuel’s specific gravity is ~0.8, so 1 litre ≈ 0.8 kg (lighter than water). It’s also worth noting that jet fuel is essentially a highly refined kerosene, far less volatile than gasoline, which makes it safer to handle in large quantities. On a long-haul, fuel can be close to half the aircraft’s total weight at departure. On the A350-1000, that can be ~129 tonnes. At most major international airports, this much fuel doesn’t turn up in a tanker. It’s stored in a depot and delivered through a network of underground hydrant pipes to each stand. The “tanker” you see is really a pump truck connecting the hydrant to the aircraft and metering the exact uplift. When I moved from the A340-600 to the A350-1000, one of the things that struck me most was just how much simpler and smarter the fuel system became and how much less fuel we required for the same journeys. On the A340-600, we needed a rear trim tank in the tail to keep the aircraft in balance during cruise. It worked beautifully, but it added complexity. The A350 doesn’t need that, instead, it uses tiny fractions of flap in cruise, together with the latest wing aerodynamics, to keep perfectly in trim. London → New York comparison (typical figures): - A340-600: ~80–90 tonnes of trip fuel - A350-1000: ~50–60 tonnes of trip fuel That’s roughly 30–40% less fuel, saving ~25–30 tonnes on a single flight, which also means about 80–95 tonnes less CO₂ (rule of thumb: 1 tonne of jet fuel ≈ 3.16 tonnes CO₂) 📸 by ig/captainchrisshow more

you are COOKED if you can't make $20K+ per... month online in 2026 1. you can use AI to generate 300 posts in 15 minutes 2. you can get millions of views without spending a penny on ads 3. you can put words in a document and sell it 1000x for $50+ each 4. you can hire workers for $2.50/hr 100 years ago you needed your life savings just to START a business today you can start for free on your iPhone in seconds My 1.3 to 2.4 GPA teenager students that began working with me 10 months ago are making $30K–$80K+/month now I got a student Zain was earning minimum wage at a café in may 2025... now he's making $78K/month and bought an AMG Mercedes to help you guys , I've decided to LEAK the full recording of my 24 hour LIVE challenge where I grow a twitter account to $5000 in sales, showing step by step everything. 20 minutes VIP COURSE. usually $2K+ to access. what's inside: → How to create digital products with AI and sell them for $200 to $500 each → How to AI generate tweets that generate 2000+ leads in 24 hours. → how to set up the entire funnel and systems → why accounts with 6.5M followers make LESS than mine with 13K views → the DM automation software sending 1000+ messages daily for free (send link to purchase ebook) → the copywriting crash course formula turning comments into $10K–$100K sales → a 3 month gameplan for you : how to choose a product to sell, how to make tweets that generate millions of views and convert to $10K/mo DELETING IN 24 HOURS comment "X" and I'll DM it to you **must be following + retweet to receive**show more

HOW TO DODGE EVERY SKILLSHOT IN LEAGUE OF LEGENDS... SO YOU GET ACCUSED OF SCRIPTING - Script in your mind - Draw out how far, wide, fast an ability is relative to your character thats all the easy stuff that I have been preaching already you can find in my free discord for improvement however one thing that League coaches fail to explain is the human aspect of it every game you play in League of Legends, every single person in the game is constantly building their profile in a game on how they operate both sides are constantly trying to mind f*ck each other to land and dodge skillshots. I have broken it down into layers the three layers to dodging are layer 0 - no dodge (unconscious) layer 1 - dodge (conscious) layer 2 - no dodge (conscious) Notice how in the clip in a challenger game below Olaf shoots a layer 0 skillshot, but because I am playing at a layer 1, I dodge his axe. Now the Thresh hook gets a little deeper bare with me, because I built the profile that I will dodge an ability in that moment, he thinks that I won't dodge and is shooting a hook at a layer 2 thinking that I will dodge at a layer 2 also. However I know that he knows I will likely not juke and walk straight so I make the conscious choice to dodge AGAIN playing at a layer 1 resulting in me dodging the hook, of course he could be accounting for my tumble but the point still stands. There are many deeper things to consider like zoning abilities, environment etc but you generally want to always play at a layer 1 until you gain more data in a game to adapt. However one thing that always stays true throughout my 13 years of playing League is in teamfights that have gone on for awhile, human beings tend to panic and default to layer 0 of shooting abilities, so if your able to operate at layer 1 as a teamfight progresses, you will likely dodge that one final skillshot that wins you the game. study the saskio wayshow more