This guy built an HFT algorithm on Polymarket with an average trade size of $38.62 Result: +$489,494 The bot trades 5 minute BTC and ETH Up/Down markets using two-sided accumulation, complete sets, and a directional residual: 1. Starts accumulating both sides almost immediately The bot first buys one side and begins buying the opposite outcome almost immediately The median delay between its first Up and Down purchases is 7.5 seconds It then continues accumulating both sides as prices change within the market 2. Builds complete sets below $1 The main goal of the paired inventory is to achieve: VWAP(Up) + VWAP(Down) < $1 Its average combined VWAP is 97.93c, giving it an edge of 2.07c 3. Keeps a directional residual on top of the hedge The bot does not try to maintain a 1:1 balance between Up and Down In paired markets, the median ratio between the larger and smaller sides of its inventory is 1.44× If its fair probability leans more strongly toward Up or Down, the algorithm increases its inventory on that side while keeping the opposite outcome as a hedge leg Its Polymarket account: x-MoneyForWhiskas The bot’s main edge comes from combining complete sets with directional skew: the core position is hedged through Up + Down below $1, while additional inventory remains on the side its model considers underpriced

This guy built a directional/latency bot and made +$303,340 on Polymarket I analyzed its trades and found that the strategy is built around continuously re-estimating the probabilities of Up and Down in 5 minute BTC markets The bot starts trading as soon as each market opens Its model compares BTC’s movement with the opening reference price and factors in momentum, acceleration, volatility, and real-time spot/perp feeds If one outcome looks underpriced, the bot immediately starts buying it A typical sequence looks like this: > It buys Up at 55c > BTC reverses > Instead of selling its Up position, the bot starts buying Down > BTC then reverses again, and it adds more Up Buying the opposite outcome acts as a dynamic hedge and reduces net directional exposure. Some of these hedges become complete sets By the end of the market, a directional residual remains. It reflects the model’s latest probability estimate and is held until resolution Its Polymarket account: 0xAAAAA You can build your own trading bot here: join.horizon.trade/retrovali… (A trial is available after signing up) The main edge of this HFT algorithm comes from rapidly updating its fair probability estimates and continuously shifting exposure as BTC moves, while using the opposite outcome as a dynamic hedge

This guy built an HFT bot on Polymarket and made +$129,680 The bot trades 5 minute BTC Up/Down markets using complete-set accumulation and a directional residual: 1. Continuously accumulates both sides of each market It places BUY limit orders on both Up and Down and waits for BTC movements to change the outcome prices When one side becomes cheaper, the bot gets fills on that side. As the market reprices, it starts buying the opposite outcome at prices that keep the combined cost of Up and Down below $1 The weighted average cost of its complete sets is 98.43c, giving it an edge of 1.57c 2. Keeps part of the position directional After pairing, about 21.3% of the position value remains as unbalanced inventory. It chooses which outcome to hold based on its model’s signal Its Polymarket account: nagi777 Build your own trading bot here: join.horizon.trade/retrovali… (A trial is available after signing up) The bot’s main edge comes from two layers: most of its inventory is paired into complete sets costing less than $1, while the remainder is kept as a controlled directional residual

This guy built an HFT algorithm on Polymarket with an average trade size of $18.69 Result: +$88,641 The bot trades short-term crypto Up/Down markets using a passive maker grid, asynchronous accumulation, and a directional residual: 1. Places BUY limit orders across a fixed price grid It provides liquidity at multiple price levels in advance and waits for the orders to fill 2. Accumulates the opposite outcome as the market moves It bought both Up and Down in 63.6% of markets Orders on one side fill first. Once the market reprices, orders on the opposite side start filling Within each market, it switches between Up and Down a median of 2 times 3. Keeps part of its inventory directional After pairing both sides, a directional residual remains. The size of this residual becomes the main source of PnL In markets where it bought both sides, the outcome with the larger inventory won 53.7% of the time Its Polymarket account: 98euf98a Follow this account and trade on Polymarket through this app: ratio.you/r/SFWM9FFJ The bot’s main edge comes from a two-part strategy: matched Up/Down positions reduce exposure, while the remaining directional residual drives most of its PnL

This guy built an asynchronous complete-set bot and made +$111,945 on Polymarket with a 50% win rate I analyzed its trades and found that its main strategy is based on gradually accumulating both sides of the same market In 88.76% of markets, it bought both Up and Down It looks something like this: > First, the bot accumulates one side > After the underlying asset moves, it starts buying the opposite outcome > Then it switches between both sides several times as the market reprices > This way, it tries to build a position where Up + Down < $1 The average cost of these complete sets is 98.69c, which gives an edge of about 1.31c But this is not pure arbitrage. Part of its inventory remains directional, with the side determined by its model’s signal Its Polymarket nickname: norm1e69 The main edge of this trading bot comes from switching between both outcomes to build complete sets below $1, while keeping the unpaired inventory as a directional residual

This guy built a two-sided inventory bot and made +$299,420 on Polymarket with a 50% win rate I analyzed his trades, and his main strategy is to use price movements of the underlying asset to buy Up and Down at different moments and build complete sets for less than $1 For example: > The bot accumulates Up at 42c > BTC changes direction, and some time later Down falls to 53c > It buys Down > Up + Down = 95c After resolution, one of the two sides settles at $1, so this pair leaves 5c of gross edge Intramarket volatility becomes part of its edge In every market I analyzed, it bought both Up and Down, and roughly 86% of all purchased shares could be paired into complete sets The remaining inventory stays directional, with the side determined by its model’s signal Its Polymarket nickname: aswfadq1555 The main edge of this trading bot comes from repeating the same mechanic at scale: building complete sets below $1 while keeping a small directional residual in the remaining inventory

After integrating Grok Bot into an existing business, I realized something very important: One of the principles of an AI-first business is that key company processes should be understandable not only to people, but also to AI People can work well even inside poorly formalized systems An employee can understand from context what qualifies as a good lead, find the right number in an old chat, and figure out who should receive the result next In my B2B growth agency, some workflows worked exactly like this But once I started integrating AI agents, I realized that for them to work reliably, processes need to be better structured and formalized This is where the difference between a business with AI added later and an AI-first company starts to become clear If I were building the agency again as AI-first, I would design every important process roughly like this: INPUT -> RULES -> CONTEXT/STATE -> OUTPUT -> EXCEPTION -> NEXT OWNER And I would not just create instructions for AI. I would make the business itself machine-readable by design This creates advantages even when the work is still being done by a human employee: > A new employee can understand the process faster > Less information gets lost between stages > It is easier to replace one tool with another > It is easier to add a new Bot > It is easier to see exactly where the system breaks So one of the main advantages of an AI-first business is that key recurring processes are designed from the start with clear rules, inputs, outputs, and ownership That makes them easier to automate, scale, and hand off between people and AI employees

This guy built a trading bot and made +$142,620 on Polymarket with a 50% win rate After analyzing all of his trades, I realized that the bot’s main strategy is to build positions where Up + Down < $1 A typical setup looks like this: > The bot buys Up at 47c > A few seconds later, the market moves > It buys Down at 52c > Total cost = 99c After resolution, one side settles at $1 and the other at $0 That means the complete set locks in 1c of gross edge regardless of the underlying asset’s direction In 64% of these pairs, the combined price was $1 or lower It also keeps a small directional residual based on its model’s signal, but most of the position remains hedged His Polymarket nickname: Polkadot-Frog Follow this account and trade on Polymarket through this app: ratio.you/r/SFWM9FFJ Its edge comes from execution price and inventory management. It accumulates both sides for less than $1, and by repeating this setup at scale, a tiny edge turns into significant PnL

If I were building my online business today, I would integrate Grok Bot into many processes from the start The old approach looked something like this: hire people -> assign responsibilities -> build processes -> add software -> then try to automate some of it Today, I would take a different approach First, I would map out every process in the company and divide them into three groups: > What should be decided by a human > What AI can execute > What AI can monitor Only after that would I build the team Some functions would stay with people, while part of the recurring work would be delegated to AI employees For recurring work, I would use Skills, Routines, and Handoffs AI would not be an extra tool added on top of an already-built company It would be part of the company’s architecture from the beginning I think this is how more and more new digital businesses will be built