Webot CEO: Trading bots are blind, AI will teach them to see

Webot organised an event titled Beyond the Bot: How AI Is Rewiring Automated Trading. Automated trading is now common. The conversation centred on the extent to which artificial intelligence should be integrated into an existing bot that operates in the background, and what prerequisites must be met before it gains additional autonomy.

The main speaker was Jay Hua, CEO of Webot US and a former vice president at Goldman Sachs. He was joined by several panellists: Alevtina Labyuk, chief strategic partnerships officer at BeInCrypto, who formerly held marketing roles at firms including Visa; Abay Beyshenkulov, a partner at VComms, a PR agency that collaborates with business and tech companies on media visibility; and Modern Mining, the founder of a YouTube channel by the same name, who has been operating Webot grid bots for approximately three years.

The session followed a clear progression: market conditions were discussed first, followed by the practical applications of AI, and finally Webot's upcoming plans.

Present market conditions

Modern Mining anchored the price conversation. Bitcoin was rangebound for months before ultimately rising. He did not dismiss the possibility of a short-term decline, nor did he appear to be done with the cryptocurrency.

Hua took a more optimistic stance. He stated that the market is maturing. The recent two-week period was encouraging, and he believes the best days lie ahead.

Alevtina offered a structural perspective. Over the past few years, Bitcoin's price drivers have shifted from cryptocurrency-specific news to ETF inflows, interest rates, and institutional investment. To gauge future price direction, she suggested tracking capital movements.

Abay contributed an additional dimension. Venture capital in the cryptocurrency sector has been relatively scarce compared to other industries, and some of that capital is now exploring the intersection of Web3 and artificial intelligence. He noted that institutional money is returning.

This background gave the AI discussion more concreteness. With larger capital flows driving much of the market activity, a bot that merely replicates previous settings will become outdated more quickly.

AI's utility and its boundaries

Alevtina placed the tool in a pragmatic role. AI excels at collecting contextual data—news, sentiment, positioning—and converting a collection of weak signals into something more actionable than a solitary instinct. However, she cautioned that the output is not infallible, nor should traders delegate decision-making entirely. Experience remains crucial in determining which signals to rely on. AI can offer guidance but cannot ensure outcomes.

The topic of trust was integral to the conversation. In light of recent exchange collapses, Alevtina emphasised that the primary consideration is whether the platform is regulated and secure, particularly in Europe. Only after that can AI progress from strict rules to advisory suggestions, and eventually to something that aligns with a user's personal risk appetite and preferences.

Webot's upcoming developments

Modern Mining did not request that Webot abandon grid trading. He has used these bots for roughly three years and has occasionally held the majority of his portfolio in them. He appreciates the AI backtesting provided during configuration. His next wish is for a similar analysis after the bot is operational: details on the actual returns over the past 30 days and how those returns might have differed if the number of grids had been adjusted. He noted that the grid count is not an intuitive setting. Reducing grids can either increase or decrease profits, depending on the bot's trading frequency.

Hua's response formed the core of the event. He described the current bot as reliable and tireless, but also lacking awareness. Users configure parameters and the system executes continuously. It fails to recognise when market conditions shift, so those parameters can gradually become misaligned with actual trading conditions.

According to Hua, Webot's effort is not aimed at creating a larger universal model. Rather, it focuses on enabling the system to interpret real-time conditions relative to the existing settings. This involves three phases.

First, AI that can describe the product and its functions in simple language. Second, AI that can monitor an active bot and provide recommendations worth evaluating. Third, AI that can execute actions, but strictly within predetermined limits.

This three-stage plan is part of a larger corporate transformation. Webot operates as a licensed exchange with integrated trading bots, as opposed to a third-party application connected via API keys. In the US, it holds licenses in 48 states and the U.S. Virgin Islands. In Europe, it has a MiCA Trading Platform Authorisation granted in Ireland. Hua stated that the rebranding from Pionex.US to Webot came after obtaining the EU license. The company was no longer solely American, so the name needed to indicate that.

Audience questions via chat centred on similar topics: the rebranding, risk management features, and a bot's behaviour during heightened volatility. The session felt more like users inquiring about future controls rather than a celebration.

Webot's strategic bets

Market activity has regained some momentum. Simultaneously, regulations are becoming less permissible to ignore, particularly in the US and Europe. AI adds a third dynamic. Nearly every trading product must now disclose its use of AI.

These three factors do not coexist easily. A more active market increases demand for automation. Stricter regulations prompt questions about platform safety for leaving a strategy active. AI enhances the tool's intelligence while simultaneously raising trust issues.

Webot's stance is that automated trading will only grow in importance. If that holds, the platforms that survive will be those that operate under genuine licenses while making bots more valuable—more comprehensible, more attuned to current conditions, yet still constrained by the user. This narrative is more measured than a full AI rollout. It was the narrative Hua presented during the public session.

For Webot, this is not merely a list of features to develop. It represents the future of trading: bots that perceive the market and platforms that can withstand regulatory scrutiny.