In crypto trading, the execution price rarely matches the price you see on the screen.
The difference is called slippage. It is the gap between the expected price and the actual price at which the trade is executed.
In volatile markets or trading pairs with limited liquidity, slippage quietly increases trading costs and distorts price discovery.
🔹The Role of Market Makers
Market makers continuously place buy and sell orders, maintaining liquidity on both sides of the order book. This ensures that trades execute without sharp price jumps even when demand changes quickly.
This improves market quality in several ways:
• Deeper order books
More liquidity available at each price level
• Tighter bid-ask spreads
Smaller difference between buy and sell prices
• Lower price impact
Large trades move the market less
• Smoother price discovery
Trading becomes more efficient
🔹Why It Matters
Without consistent liquidity provision, even moderate orders can move prices significantly. This often occurs with newly listed tokens or low-volume pairs.
Stable markets require continuous liquidity that allows buyers and sellers to transact efficiently.
🔹Bitmaker Approach
At Bitmaker, liquidity provision runs through automated trading systems and algorithmic strategies that adapt to market conditions in real time.
🌐 https://t.co/1RmLjLrWR2
Projects approaching a token generation event often face several strategic and operational challenges.
🟢Tokenomics Under Market Pressure
Token models are typically designed in theoretical environments. Once trading begins, vesting schedules, liquidity depth, and early investor behavior begin shaping price discovery. Without a clear post-TGE framework for managing supply, liquidity, and potential cash-outs, early market performance can become unstable.
🔴Fundraising and Final Rounds
Technical progress alone rarely secures late-stage investment. Venture funds evaluate projects based on narrative clarity, financial structure, and long-term positioning. Structured fundraising processes, strong investor communication, and industry introductions often become critical in closing final rounds.
🟢 Exchange Strategy and Listings
Exchange selection significantly influences credibility, liquidity, and capital efficiency. Projects often underestimate listing costs and the operational requirements associated with different platforms. A staged listing strategy and realistic budget allocation for listings and liquidity are therefore essential.
🔴Market Infrastructure and Liquidity Support
Launching a token requires coordination with exchanges, market makers, legal advisors, and ecosystem partners. Market makers support liquidity and orderly trading, but their role is sometimes misunderstood, they facilitate market efficiency rather than determine long-term valuation.
🟢Partnerships and Industry Access
Strong networks across exchanges, infrastructure providers, and ecosystem partners can accelerate both fundraising and launch preparation. Limited access to these relationships often slows execution.
To address these challenges, the Bitmaker Pre-TGE Program provides a structured framework combining market-making expertise, launch strategy, and access to industry partners.|
Learn more about the program — [email protected]
Not many people know the story behind @origamitech_.
This is the first post: where we came from.
It all started 7 years ago, when my co-founder and I joined a centralized exchange trading desk. As recent graduates, we somehow ended up working on order book depth, market quality, accounting, and risk control around user actions.
It was fun, but not a long chapter. After about a year, we decided to move on. We felt we understood where the edge was, and started running our own algos on centralized venues with our own capital.
That was the real beginning of growth. I was writing code, he was helping across both technical work and management. In 2020, during DeFi summer, we became the top retail-volume account on @kucoincom - just two people doing billions in monthly volume on major venues.
That same year, we launched @bitmakerfi, a retainer market maker built around one principle: stay small, but compete with anyone. We hired developers and started building out the business.
For the first year, most of the engineering work was spent rewriting my original codebase to fit a new architecture. That became the first version of the protocol we internally called Typhoon.
It was already better than what most retainer market makers had at the time, but it still wasn’t enough for us. It was too conventional: a handful of strategies, a set number of variables, a defined set of inputs. Strong, but limited.
The model we kept coming back to was something closer to the WorldQuant external consultants idea: a unified framework where people can create their own algos, while the platform handles execution, connectivity, and data.
In 2022, we redesigned the architecture from scratch and released our own language, which allowed us to build strategies directly from math, market data, and trading indicators. Latency improved, we found more edge, and the client base grew significantly over the following year.
That period was productive. We released analytical tools, CEX-DEX systems, and arbitrage systems capable of handling up to 7 legs within one flow.
In January 2024, I found @HyperliquidX and started trading there. Not because I particularly wanted futures, but because I liked the idea of a CLOB-based DEX. Soon after, I got in touch with Ruslan from @extendedapp - back when they were still early, still on testnet, and still called X10. I still think the rebrand was a great decision.
Around that time, I also got @xulian_hl’s contact and texted him. He replied, and that became a turning point. I started thinking seriously about bringing our technology to users and connecting it to Hyperliquid.
At that point there were no builder codes or anything similar, but within a month we had built the first interface. It was glitchy, API-key based, and full of bugs. I wasn’t proud of it, and we never released it publicly. That was around October–November 2024.
After a few more months spent refining interfaces and fixing bugs, we finally launched Origami. At the time, I had postponed making perp DEXs the main focus, because the ecosystem still couldn’t support what we really wanted to build. For a while, API keys were the only realistic way to support trading.
So we launched first with trading competitions - a format where users come to compete for prize pools funded by crypto projects.
A month later, we launched liquidity mining competitions, giving projects a way to incentivize user liquidity provision.
Since then, we’ve run more than 90 competitions and distributed over $200k in prize pools. A strong result - but still not the core dream.
The bigger vision was always perp DEXs, and giving users the ability to create their own algos through Origami.
By October, we had integrated with all existing builder programs. We didn’t build a massive user base there, and we understood the reasons clearly:
> onboarding was too complex
> UI/UX wasn’t good enough
> strategy creation was still too difficult
We tried simplifying things into lighter bot versions, but quickly understood that wasn’t our path. We know how to do this better.
This huge interface update is the first step. The major things are on the line.
If you read it, please leave a comment and thank you.
Stay tuned.
Bitmaker Newsletter #1
A few signals shaping the current crypto market structure ↓
✔️Against the backdrop of Vitalik admitting that Ethereum’s heavy push toward L2-centric scaling may have been a misstep, the narrative battlefield is shifting.
LayerZero is quietly positioning itself as a structural competitor to Ethereum’s dominance model.
But the bigger signal is different.
Even strong headlines fail to sustain momentum.
The Uniswap–BlackRock integration pushed UNI up nearly 40%.
Within days the entire move was erased.
That tells you a lot about current liquidity conditions.
Original news:
https://t.co/GcWqR9e33b
✔️Meanwhile Binance controversies continue.
DefiLlama briefly removed Binance outflow statistics, triggering FUD about record capital flight.
It later turned out to be a data display issue and the metrics were restored.
Soon after, reports appeared that investigators who flagged potential Iranian sanctions violations were dismissed.
Either ignoring those warnings or acknowledging them creates reputational pressure.
Original news:
https://t.co/4MK9te9Q9h
📊According to market research, the global algorithmic trading market is estimated at $3.28B in 2025 and is projected to reach $6.05B by 2032, growing at a 9.1% CAGR.
This growth reflects the continued expansion of electronic and automated execution across global markets.
> In electronic markets, trading activity is executed automatically through continuous order placement, updates, and matching. This execution model operates at scale and requires stable conditions for price discovery and execution.
> At this scale, liquidity is delivered through infrastructure and continuous quoting. Stable order books, predictable spreads, and consistent execution become structural characteristics of the market.
> To maintain these conditions, exchanges formalize liquidity provision through market-making programs. Within these programs, market makers act as core liquidity providers under explicit operational constraints:
• ~90–95% liquidity uptime
• continuous two-sided quoting
• spread and depth obligations
• risk and inventory limits
As algorithmic trading adoption grows, liquidity programs expand across more instruments and venues. This expansion increases demand for professional market making, as automated strategies rely on predictable execution, stable spreads, and consistent order book depth.
🌐 https://t.co/oSjGOq2gmz
AI is already part of crypto market making.
But its role is widely misunderstood.
Here is why
▪️To understand it, start with what market making actually is. Market making is continuous liquidity provision under strict constraints: exchange rules, latency, and risk limits.
▪️Within these constraints, AI is used as adaptive models that adjust in real time:
• spreads
• quote placement
• inventory exposure
• response to volatility and order flow
▪️AI operates inside deterministic execution logic, tuning parameters rather than making discretionary trading decisions. Every action remains bounded by risk limits and exchange rules.
The idea of a fully autonomous AI trader is appealing, but in real markets, sustainability breaks during stress and regime shifts.
The edge comes from infrastructure, where AI enables adaptation without breaking risk boundaries.
🌐 https://t.co/1RmLjLrWR2
Why most market making teams cannot maintain 90–95% liquidity uptime
Many market makers promise stable liquidity.
Only a limited number consistently maintain 90–95% liquidity uptime, which reflects the actual requirements of top tier centralized exchanges.
▪️Liquidity uptime is an engineering outcome.
It depends on:
• fast execution architecture
• fully automated trading
• proper rate limit management
• reliable risk guards and kill switches
• pipelines that operate without errors
When market conditions deteriorate, weak systems lose the ability to quote consistently.
At Bitmaker, liquidity uptime is the result of technical design. Our systems run in colocated clusters with Rust based runtimes, real time monitoring, and automated safeguards. This approach keeps markets stable around the clock.
🌐 https://t.co/1RmLjLrWR2
Most market makers talk about uptime and rarely clarify what they mean.
There are two different metrics.
▪️System uptime
Bots, backend, algorithms, monitoring.
For any serious market making operation, this should be around 99% or higher.
▪️Liquidity or order book uptime
The percentage of time quotes are present in the exchange order book.
For top tier centralized exchanges, realistic requirements are 90–95%.
Across the broader market, around 70% is common.
These metrics are often mixed together, which leads to unrealistic expectations.
At Bitmaker, 99% plus system uptime enables 90–95% liquidity uptime, including periods of elevated market volatility.
🌐 https://t.co/1RmLjLrWR2
Between a price update and a new order appearing in the book, the system completes a sequence of coordinated steps.
The full cycle takes approximately 150–300 ms.
Order flow at Bitmaker:
• Market data is received
• Strategy logic is evaluated in WASM
• Risk guard verifies parameters
• Rate limit checks are applied
• The router selects the execution path
• The order is submitted to the venue
• Fill information is reconciled
• The dashboard updates in real time
This workflow is the basis for stable spreads, predictable execution, and consistent market depth.
🌐 https://t.co/1RmLjLrWR2
Effective market making depends on a reliable technical foundation. It is built on systems that execute consistently, manage risk automatically, and operate close to exchange infrastructure.
At Bitmaker, strategies compile into WASM and run inside isolated Rust runtimes located near CEX matching engines.
This setup provides:
> Millisecond level execution
> Independent and isolated strategy state
> Integrated risk guards
> Automatic kill switch mechanisms
> Secure handling of short-lived keys
This architecture supports stable uptime, predictable depth, and controlled spreads at scale.
🌐 https://t.co/1RmLjLrWR2