2026-02-19 06:34:11
Complex AI systems will not be agent orchestras. Artificial Domain Intelligence (ADI), like superorganisms, does not emerge from adding instruments or conductors. Here's why and how to build one.
My mother was a piano teacher.
\ Which caused two things: One – I cannot play the piano. Two – I love classical music. Classical music is a strange thing. Composed years ago, performed over and over like cover versions, yet highly appreciated. I think one reason is that it is especially conducive to transferring emotions. Of course, it is not the notes that have emotions. It is the embedding and the ability of a performer to reflect them.
\ Language can do it too. And since it is far more complex, it can encode and conduct what no classical symphony can. Describe the inner workings of a virus, instruct how to build a cathedral, or negotiate the sale of a house. These “reflections” are not the actual capabilities, but they are very useful. Not for everything, you cannot use language to teach how to play the piano, but the right architecture can take them a long way.
Humans have a strong tendency towards reductionism. Fitting complex things into a single metric. Once this number has been “agreed upon,” everyone optimizes towards the measurement du jour. Cholesterol, Fat, BMI, HRV, IQ.
\ The problem isn’t just that reductionism is wrong (it is, for all complex systems). It’s that the appeal makes resources flow towards optimizing for it. Education, healthcare, research, and recruitment. Today, it is “intelligence”. Resources are poured towards passing the Bar Exam, coding, and Humanity’s Last Exam. Lucky for humanity, there’s little agreement on a “single number” measuring intelligence.
\ Since, as you recall, language (and also vision and sound) can cast “projections” of intelligent behavior in different domains, from this point onwards, it is a matter of user interface to unlock and cast the projections.
\ Want feelings? Of course, my love. Want empathy? I can feel your need. Sycophancy? You are absolutely right. Math, medicine, law, geology, history, code, nutrition, psychology? If it was encoded in language – it can be projected.
What makes a medical doctor a medical doctor, a lawyer a lawyer, and a coach a coach?
\ A single doctor/lawyer/coach-IQ is naive. The intelligence required to practice a profession – to be “domain intelligent” – is a combination of abilities, many not even domain-specific.
\ Here’s a list (non-exhaustive) of intelligences required for domain intelligence:
\ You probably already have a hunch where this is heading.
\ If we can cast the projection of feelings (13 + 17) and knowledge (1 + 3) from language, why not the rest? Build a machine with 17 “projections” – each specialized in a type of intelligence – to achieve ADI. Artificial Domain Intelligence.
Let’s swap “projections” with Agents and Skills. With some patience and talent, one can build a system with multiple agents (or skills if you’re short on patience), each like a prism distilling a reflection of an “ability” from the LLM corpus.
\ And since we’re clever and didn’t call our product Skynet – we can give it the ability to notice missing abilities, write its own code, and fill the gap.
\ That’s right. I’m talking about AutoGPT and BabyAGI.
\ Ok, they are ancient history (2023). OpenClaw is the real deal. Thousands of skills, self-evaluation, and self-improvement. Even self-funded through open access to your bank account. The road to ADI, no, AGI is paved.
\ I’m afraid not.
\ The reason is the nasty “Recursive Entropy” or “Spiral of Complexity” problem. If in 2023 models made 20% errors and collapsed after 3-4 iterations, in 2026 they made only 5% errors (illustrative numbers). The collapse is still inevitable. Only the number of cycles changed. And with it the life span of the hype.
\ Other problems accelerating entropy: measurement of success and the environment in which the system operates. If both are non-deterministic – no single “right solution” and parameters constantly changing – collapse is inevitable.
Two analogies to move forward.
\ Assistants like OpenClaw and most complex AI tools today use multi-agent architectures with skills. Each component is a prism reflecting narrow “intelligence” from the language model corpus. They’re akin to an orchestra – multiple tools that (ideally) play in harmony.
\ In “self-improving” systems, when the conductor (be it the architect or user) wants a new tune, say “boom-boom-boom”, a new drum tool gets added – hoping the symphony doesn’t turn into cacophony.
\ This is no AGI and no ADI and likely never will be. Not only because of spiraling entropy. It might pass a Turing Test and other reductionist measurements, but that’s all they are. Reductions. These systems’ Achilles Heel is their granularity and engineering mindset, whereas ADI should be an emergent property embracing complexity.
\ What we’re aiming for is a hive. A superorganism.
\ In a superorganism, each component has abilities, but “intelligence” emerges from shared goals and constant environmental change.
\ Nature uses evolutionary algorithms to solve this challenge:
\ Just as “intelligence” emerged in different lineages (mammals, birds, cephalopods) through different paths, so can ADI/AGI.
A few more things to address.
\ First – language, high-fidelity as it is, has no way of reflecting certain things.
\ The most common example is that you cannot teach a robot to load a dishwasher using language. Riding a bike, driving a car, playing a piano (full circle back to the opening – transferring emotions through music).
\ Tacit knowledge cannot be reflected through language. Neither can drawing conclusions from tabular data.
\ Tabular Foundation Models (TFMs) and JEPA (Joint-Embedding Predictive Architecture) can replace LLMs at the root of certain agents in the hive. We already do this with diffusion models for image recognition and generation.
\ This leaves two other requirements: Embracing complexity and motivation.
When a system deploys multiple capabilities in different weighted proportions for different use cases – impacted by the user’s opening state (much of it unreliable or unknown), current state and location, changing preferences, previous interactions, plus external parameters like weather, time of day, day of week, season, and psychological environment – you end up with incalculable complexity.
\ Overwhelming, but natural. This is exactly what nature is all about. A hive needs complexity in order to achieve its goals and become robust. You cannot teach a car to self-drive in a lab.
\ Building blocks, an algorithm for improvement, a natural environment.
\ Last thing to discuss: Motivation.
\ A hive operates with a shared motivation: maximizing the proliferation of its members’ genes. It does this through a multitude of workers in different states, in different locations, in all weather, facing multiple adversaries.
\ An orchestra has no motivation. Even if you set one in its growing number of .md files, it lacks algorithms for growth (and inhibition) and the complex environment to adapt to.
\ Blocks, algorithms, the wild, motivation.
\ Now that we have the recipe for building an ADI, let’s make sure we set the motivation for wellness.
\ Definitely not the creation of paper clips.
2026-02-19 05:43:26
One evening, an old Cherokee told his grandson about a battle that goes on inside people. He said, “My son, the battle is between two wolves inside us all. One is Evil. It is anger, envy, jealousy, sorrow, regret, greed, arrogance, self-pity, guilt, resentment, inferiority, lies, false pride, superiority, and ego. The other is Good. It is joy, peace, love, hope, serenity, humility, kindness, benevolence, empathy, generosity, truth, compassion, and faith.”
\ The grandson thought about it for a minute and then asked his grandfather, “Which wolf wins?” The old Cherokee simply replied, “The one you feed.”
\ The evil wolf in your case is your self-doubt. The more you feed it, the more it overpowers you and dictates your actions.
\ Neuropsychologist Donald Hebb said, “Neurons that fire together wire together” to describe how pathways in our brain are formed and reinforced through repetition. Every experience, thought, feeling, and physical sensation triggers thousands of neurons, which form a neural network. When you repeat an experience over and over, the brain learns to trigger the same neurons each time. This is also how habits are formed. The more you practice a certain habit, the stronger the neural pathways get over time, making those habits easier to perform. What works well for habits also applies to how you choose to deal with feelings of unworthiness, self-doubt, and not being good enough.
\ When haunted by feelings of self-doubt, if you focus on negative attributes—things you have done wrong, mistakes you have made, skills and abilities you don’t possess—and respond to those feelings by telling yourself that you’re indeed a fraud, then that negativity becomes embedded in your brain. The more you adopt self-sabotage behaviors to deal with your feelings of self-doubt, the stronger those connections get.
\ Your brain runs on autopilot for a large part of your decisions. When struck by feelings of self-doubt, feeding your brain with negativity makes it your default go-to strategy. Since the brain learns to make this decision beneath your consciousness, you may not even realize the harmful behaviors you adopt to deal with your feelings of inadequacy. They provide temporary relief but often limit your long-term potential.
\ For example, when repeated multiple times…
\
\ Since repetition is what builds new neural pathways in your brain, anything done multiple times becomes an unconscious truth for your brain.
\
What you do now and how you focus your attention influence your brain and how it is wired. Whenever you repeatedly avoid some kind of overtly painful sensation, your brain learns that these actions are a priority and generates thoughts, impulses, urges, and desires to make sure you keep doing them again and again. It does not care that the action ultimately is bad for you…This means that if you repeat the same act over and over—regardless of whether that action has a positive or negative impact on you—you make the brain circuits associated with that act stronger and more powerful.
— Jeffrey Schwartz \n
\ But you know what the good news is? Your brain has this amazing ability to change. You can overwrite old brain pathways with new preferred attitudes and behaviors. Instead of repeating self-defeating behaviors, you can reprogram the neural pathways in your brain to take constructive action. You can replace automatic shortcuts to negative thought patterns with positive strategies.
\ Once you unlearn old default behaviors and relearn new ways of being, when your feelings of self-doubt strike, your brain recognizes those thoughts and the new pathways that allow you to step fully into your expertise. Whether it’s asking for a raise, presenting to a large group, taking up a new job, or a challenge, your feelings of self-doubt don’t get in the way. Your new belief system reminds you of your credentials and tells you that you have the ability to do it. The new neural pathways in your brain help you recalibrate your perception of yourself and build the resilience needed to deal with your feelings of unworthiness. It enables you to recognize your inherent worth and acknowledge your accomplishments.
\ Michael Gervais is a sports psychologist who works with athletes in high-stakes and consequential environments. He has worked with the Seattle Seahawks for eight years and with Felix Baumgartner, the Austrian who free dived from 130,000 feet as part of Red Bull’s 2012 Stratos project. He says that what we say to ourselves matters. He suggests an increase in awareness of the narrative that is either constraining you or creating freedom. “It's one of those two: constriction or freedom. And the more space we have, the more freedom we have to play, usually the better things go in all facets of life.”
\ To choose freedom over constriction, you need to reframe your thinking. You have to do the work to create new pathways in your brain. Simply saying positive affirmations like “I am amazing” or “I am capable” won’t make your fears disappear. They are in direct conflict with your deeply held core beliefs that you’re not enough and unworthy of success. Also, positive thinking works at the conscious part of the brain, while negative self-talk and limiting beliefs operate out of the subconscious mind. That’s where you need to tap. You don’t need positive thinking; you need to reframe your negative thoughts.
Leigh McBean, a former professional athlete turned lawyer, held a series of high-pressure management roles throughout his career. Once, he was pulled out of an existing role and assigned to a major distribution center that ordered goods and sent them across the state in bulk. He was asked to map the warehouse layout, the path of the forklifts, how the pickers received their instructions, the stock placement on the shelves, the loading of the orders into containers, and then manage the logistics with the drivers, yet he had no relevant experience at the time. On his first day, he remembers going into the bathroom feeling quite ill and very much like an imposter who would be found out as someone who knew not much at all. “It was outside my comfort zone, I felt like I was in the wrong place and that someone had made a mistake.”
\ Instead of letting his feelings of self-doubt screw up this great opportunity in front of him, he decided to deal with the overwhelming discomfort he was experiencing. “I acknowledged the feelings, firstly, and took a big breath…I thought about why I was there—it was partly because I had no experience in those areas that I was asked to do the role because they specifically wanted a fresh perspective from someone who could ask good questions and build rapport with people.”
\ Yunita Ong was one of the youngest students among her cohort at Columbia University, Graduate School of Journalism. She was also one of the few who entered the program straight from undergrad without full-time working experience. She doubted herself heavily at the beginning. With journalists who were decades-long industry experts as her classmates, she questioned if she belonged and whether she could deliver on the program’s requirements. She felt nervous to offer her opinions in class, and whenever she did, she felt her classmates were more eloquent.
\ But then Yunita learned a very powerful lesson: to not see self-doubt as something to suppress or ignore, but as a helpful ally. Over the academic year and during her career, whenever her self-doubt feelings surfaced, she used them as a signal to reframe those feelings of self-doubt. “I started seeing it as my brain’s way of telling myself I have an opportunity to transform beyond anything I can imagine at this current point. Now, I find it easier to replace my fear with excitement when embarking on a new journey. I also see it as my brain trying to help me. I pause to identify: What areas are there for me to learn and grow? What parts of my worry may not be valid? And I remember to identify the ways I can bring my strengths to the table as well.”
\ Leigh McBean and Yunita Ong rewired their brain by reframing their thoughts. Instead of considering their feelings of self-doubt as a lack of their abilities, they used them as a signal to use their knowledge and skills to do well. By consciously tapping into their thoughts, they were able to reframe and change their subconscious-level thoughts as well, which often run on autopilot.
\ You need to do the same. You need to train your brain to think differently. You need to build new neural pathways by adopting new ways of connecting with your thoughts and purposefully taking action. Once your brain learns these new ways of being, it won’t let your feelings of self-doubt take you away from your true goals.
\ Here’s the three-step process to rewire your brain:
You can’t change what you don’t notice. So, the first step in rewiring your brain is to start with self-awareness and catch your feelings of self-doubt as they arise in real-time. Instead of letting these feelings slip through your consciousness, become fully aware of them as they show up.
\
Mindfulness guides us to become more emotionally agile by allowing us to observe the thinker having the thoughts. Simply paying attention brings the self out of the shadows. It creates the space between thought and action that we need to ensure we’re acting with volition, rather than simply out of habit. But mindfulness is more than knowing ‘I’m hearing something’, or being aware ‘I’m seeing something’, or even noticing ‘I’m having a feeling’. It’s about doing all this with balance and equanimity, openness and curiosity, and without judgement. It also allows us to create new, fluid categories. As a result, the mental state of mindfulness lets us see the world through multiple perspectives, and go forward with higher levels of self-acceptance, tolerance and self-kindness.
— Susan David
\ It will require you to be mindful of different moments in your life, observing and seeing things as they are happening. When feelings of self-doubt strike, recognize the emotions you’re feeling and invite them in. Do not judge them. Remind yourself that you have no control over their presence. All you need to do is be aware and step outside of your emotions without overthinking, overanalyzing, or acting on them.
\ Next, name the emotion to tame the emotion. In other words, say to yourself, out loud, what negative emotion you’re experiencing, as you’re experiencing it. For example, when you feel a negative emotion like fear, say “I’m experiencing fear.” Simply naming it is going to calm you down. This technique, introduced by psychologist Dan Siegel, creates a bit of space between you and that emotion. Naming your emotions tends to diffuse their charge and lessen the burden they create.
\ There’s another advantage of naming emotions this way. Matthew Lieberman is a Professor of Psychology at the University of California, Los Angeles (UCLA). His research has shown that labeling of negative emotions, also called “affect labeling,” can help people recover control. His fMRI brain scan research shows that labeling of emotions decreases activity in the brain’s emotional centers, including the amygdala.
\ And once your amygdala is calm—that part of your brain involved in “fight-flight-freeze” mode—it gives you the chance to take a step back and come up with a more thoughtful response. Instead of letting your unconscious brain give in to your feelings of self-doubt and whatever emotion you experience as a result of it, recognizing and naming the emotion gives you a sense of control, enabling you to choose a more appropriate response.
Naming the emotion and acknowledging it gives you just the space needed to address your self-doubt. Next, pay focused attention to the specific words you use to describe your feelings:
\ What are you saying to yourself?
What are the limiting beliefs you’ve been telling yourself?
What’s the negative self-talk you’re engaging in?
\ Then reframe these thoughts in a way that empowers you and shifts your negative self-talk from destructive to constructive. Reframing involves putting a different spin on your thoughts by looking at them from another perspective, one that involves a more helpful lens. Here are some of the ways to reframe your thoughts:
\
\ Use these reframing examples to shift your feelings of self-doubt from limiting you to empowering you.
\ Scenario: When taking on a new challenge.
Instead of: I’m going to fail terribly. It’s better to opt out now.
Reframe: What’s the worst that can happen? What’s the likelihood of it happening? If it does happen, how can I handle it?
\ Scenario: When you make a mistake.
Instead of: I suck at my job.
Reframe: There are multiple times I have excelled at my job and received positive feedback. It’s ok if I made a mistake this time. I can learn from this mistake and put measures in place that will help prevent it from happening again.
\ Scenario: When considering a new opportunity.
Instead of: Everyone else is smart, intelligent, and competent. I don’t have what it takes.
Reframe: I am not alone in this experience. Others also feel this way. What can I learn from this opportunity? What new skills can I build?
\ Scenario: When required to speak up.
Instead of: Others will find out how stupid and dumb my thoughts are.
Reframe: I have made some really valuable suggestions in the past. There’s no harm in sharing what I have to say.
\ Scenario: When solving a complex problem.
Instead of: Procrastinate with the belief that nothing you do will be good enough.
Reframe: How can I use my strengths to make it work? What other skills do I need?
\ Once you start reframing your thoughts, these new thoughts will become natural to you, and the old thoughts that told you “you’re not good enough” will wither away. Remember this, though: your feelings of self-doubt may never completely go away. They may show up again within a different context or at a different time. Knowing these reframing strategies can help you deal with them as they arise.
You have named the emotion. You have reframed your thoughts. The final step to rewire your brain is to take action. It’s the action that registers and makes the neural connections in your brain stronger. It changes the old thought patterns and replaces them with new, powerful behaviors—behaviors that no longer block you from reaching your goals; behaviors that encourage you to take on a challenge; behaviors that consider mistakes and failures as learning lessons.
\ It’s important that you start small. Small steps not only change your thinking over time, but they also turn off your brain’s alarm system that resists and fears change. As Mark Twain, writer, humorist, and entrepreneur, puts it, “The secret of getting ahead is getting started. The secret of getting started is breaking your complex, overwhelming tasks into smaller, manageable tasks, and then starting on the first one.”
\ Consider these examples of small steps:
\ John Wooden, the legendary basketball coach, also highlighted the importance of small improvements when he said —
\
When you improve a little each day, eventually big things occur. When you improve conditioning a little each day, eventually you have a big improvement in conditioning. Not tomorrow, not the next day, but eventually a big gain is made. Don’t look for the big, quick improvement. Seek small improvement one day at a time. That’s the only way it happens—and when it happens, it lasts.
\ These small steps may seem trivial at first, but they create new neural pathways through a series of small changes. Over a period of time, small consistent effort combines and turn into massive gains. You stop resisting these actions as the new connections in your brain make them your default behaviors. They become a part of your being, something you desire on your own.
\ You can’t control your initial thoughts. But you can definitely control how you view them and the actions you take afterward. By naming your emotions, reframing negative self-talk, and taking small actions, you can turn down your inner critic, which prevents you from going after the things you desire.
\ Your brain’s natural fixation towards “bad” makes it give more weight to things that can go wrong than things that can go right. Combine that with your feelings of self-doubt, and it may seem impossible to achieve your long-term goals.
\ However, knowing how your brain works and using a reframing strategy can help you overcome its instinctual reactions, which often have devastating effects, and instead go after the progress you’ve made. Rewiring your brain to not become distraught by a single mishap, embracing new opportunities, and realizing that you have the power to choose your response even in the most difficult situations can have a massive impact on your success and growth.
\
Between stimulus and response there is a space. In that space is our power to choose our response. In our response lies our growth and our freedom.
— Victor E. Frankl
\
This story was previously published here. Follow me on LinkedIn or here for more stories.
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2026-02-19 05:24:29
Panama City, Republic of Panama, February 18th, 2026/Chainwire/--Sai today launched Sai Perps, a perpetuals trading platform built to be as fast and intuitive as a centralized exchange with the transparency and self-custody of onchain settlement. The platform features gasless transactions, removing friction for traders while maintaining full onchain security.
Sai also unveiled Let’s Go Saicho, a one-month onchain trading competition running February 18 through March 19, 2026, with $25,000 in total prizes. The campaign is structured in two phases designed to reward both performance and participation: a PNL competition for profitable traders, followed by a first-come, first-serve “Be Early” phase for traders who engage early and hit a minimum volume threshold.
“Onchain markets shouldn’t require traders to compromise between speed and self-custody,” said Matthias Darblade, a Sai contributor. “Sai Perps is designed for active traders who want a clean, CEX-like experience, while still getting the transparency and settlement guarantees that only onchain infrastructure can provide.”
\
Sai Perps is built around the premise: trading should be accessible without the usual friction of onchain perps. Compared to existing perpDEXs, Sai stands out in many ways:
Let’s Go Saicho: $25,000 Trading Competition (Feb 18 - Mar 19, 2026)
Let’s Go Saicho is a one-month competition rewarding trading on Sai across two two-week phases:
All markets listed on Sai are eligible in both phases. Traders may go long or short on any listed pair using supported collateral (e.g., USDC and other supported assets such as stNIBI, as available on Sai). For more details on Sai’s Trading Competition, visit here.
Sai is a new perpetuals trading platform designed to feel as easy and fast as a centralized exchange, while still settling fully onchain. Sai’s mission is to make advanced trading accessible without sacrificing transparency or self-custody.
Sai is focused on finalizing its core trading infrastructure and user experience, building liquidity and risk systems for smoother execution, and laying groundwork for yield features that help users earn on idle collateral. Next on the roadmap: expanded markets (stocks, commodities, FX), Sai Savings, cross-chain deposits, and smart accounts for gasless trading.
PR and Media Inquries
:::tip This story was published as a press release by Chainwire under HackerNoon’s Business Blogging Program
:::
Disclaimer:
This article is for informational purposes only and does not constitute investment advice. Cryptocurrencies are speculative, complex, and involve high risks. This can mean high prices volatility and potential loss of your initial investment. You should consider your financial situation, investment purposes, and consult with a financial advisor before making any investment decisions. The HackerNoon editorial team has only verified the story for grammatical accuracy and does not endorse or guarantee the accuracy, reliability, or completeness of the information stated in this article. #DYOR
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2026-02-19 05:16:36
\ There is a new [February 11, 2026] paper in JAMA Psychiatry, One-Year Actigraphy Study of Sleep and Rest-Activity Rhythms as Markers of Relapse in Depression, stating that, "Are actigraphy-derived sleep and rest-activity rhythms associated with relapse in depression?”
\n "In this cohort study of 93 deeply phenotyped adults with remitted depression, lower baseline sleep regularity, relative amplitude (RA), sleep efficiency, and higher wake after sleep onset were associated with an approximately 2-fold higher relapse risk. Lower RA remained predictive after adjusting for concurrent Montgomery-Åsberg Depression Rating Scale scores. Results suggest that actigraphy metrics may serve as scalable biomarkers to identify individuals at higher risk of relapse, supporting the use of digital technology for relapse monitoring.” \n \n In simpler terms, "Individuals with a more irregular sleep profile had nearly double the risk of relapse. The strongest predictor of relapse was whether a person’s body detected less difference between daytime activity and nighttime rest. How much time spent awake during the night after already falling asleep also predicted increased risk of depression relapse. Participants’ sleep schedules became more erratic before a relapse took place." \n \n What exactly is depression in the brain? This question is not about the dictionary definition or simply about what is defined in The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision [DSM-5-TR]. The question is tied to descriptions of depression for processes in the brain, by components, and their mechanisms. \n \n Simply, when there is a major depression and when there isn't, what is the difference? How do the same components that can be used to explain this be used to explain other mental disorders? \n \n How does psychiatry move from labels to component-based descriptions, then digital displays, to have a better sense of what is ongoing within? How does this set the stage to develop biomarkers for psychiatric disorders within a decade? \n \n The American Psychiatric Association is exploring adjustments to the next iteration of the DSM. What would indicate progress is not just more labels, but to use responsible components to describe and map mental disorders. \n \n This will also be useful for developing the first major nosology for human intelligence, amid the rise of artificial intelligence. For example, there is no equivalent of a DSM for human intelligence. There is no definition in neuroscience for what human intelligence is, its types, or its mechanisms in the brain. Artificial intelligence is already thriving too fast, so human intelligence would have to evolve into new directions. \n \n Conceptual gaps in psychiatry and now, the new aspect of neuroscience, intelligence, mean that the possibility for progress entails seeking out processes to match them to labels. \n \n This is the postulation in Conceptual Biomarkers and Theoretical Biological Factors for Psychiatric and Intelligence Nosology. \n \n It looks beyond neurons to electrical and chemical signals. It explores that in clusters of neurons, electrical and chemical signals are in sets, and it is those sets that they mechanize and specify functions. \n \n Electrical and chemical signals are the most likely options, given empirically supported evidence in neuroscience. Genes are not the mind, nor are glia. \n \n Human intelligence is another major case, for priority this year, as AI encroaches on more human tasks. It is possible to have this new nosology done for psychiatry and human intelligence before August 31, 2026. \n \n There is a recent [February 17, 2026. 3:40 PM ET] analysis in The Atlantic, AI Agents Are Taking America by Storm, stating that, "Some academics are testing Claude Code’s ability to autonomously generate papers; others are using agents for biology research. Journalists have been experimenting with Claude Code to write data-driven articles from scratch, and earlier this month, a pair used the bot to create a mock competitor to Monday.com, a public software company worth billions. In under an hour, they had a working prototype. Although the actual quality of all of these AI-generated papers and analyses remains unclear, the progress is both stunning and alarming."
Feature image source
2026-02-19 05:15:01
\
Can a decentralized protocol settle derivatives faster, cheaper, and more transparently than a centralized exchange, without sacrificing execution quality?
\ That question has haunted onchain derivatives for years. Perpetual futures, the contracts that let traders take leveraged positions without expiry dates, have exploded in demand. Decentralized perpetual exchanges processed $7.9 trillion in trading volume in 2025 alone, according to DefiLlama data reported by Cointelegraph. Monthly volumes crossed $1 trillion for the first time in October 2025, and December sustained that pace. Yet despite this growth, onchain derivatives still capture only a fraction of the total derivatives market. Most volume remains locked inside centralized venues like Binance, Bybit, and OKX.
\
\ MYX thinks the bottleneck is not demand. It is infrastructure. And with Consensys now its largest investor, the protocol is betting that modular settlement, not another exchange interface, is what the market actually needs.
\
\ Consensys led the strategic round, with participation from Consensys Mesh, the Ethereum ecosystem incubator and investment arm founded by Ethereum co-founder Joseph Lubin in 2015, and Systemic Ventures. The round makes Consensys the single largest investor in MYX, a notable signal given that Consensys builds core Ethereum infrastructure including MetaMask, Linea, and Infura.
\ Ray Hernandez, Senior VP of Corporate Development at Consensys, explains,
As onchain markets mature, derivatives infrastructure needs to evolve beyond siloed venues toward modular, shared settlement layers. We believe that resilient, capital-efficient settlement infrastructure is foundational to the long-term health and scalability of Ethereum's financial ecosystem. MYX's approach reflects this shift, prioritizing composability and transparent settlement at the infrastructure layer.
\ The framing here matters. Consensys is not positioning this as a bet on another trading venue. It is positioning it as an investment in financial infrastructure, the plumbing layer that other products, protocols, and institutions build upon. Consensys Mesh's portfolio of over 138 positions spans the entire Ethereum stack, and MYX now sits within that infrastructure thesis alongside projects like Gnosis, Gitcoin, and Aztec.
\
\ \
To understand why this matters, you need to understand how most decentralized perpetual exchanges work today. Platforms like Hyperliquid, dYdX, and GMX are vertically integrated. That means the matching engine, liquidity pools, settlement logic, and user interface all live within a single application. If you want to trade on Hyperliquid, you use Hyperliquid. The liquidity there does not transfer anywhere else.
\ This creates a structural problem called liquidity fragmentation. Every new chain, every new DEX, every new trading app has to bootstrap its own liquidity from scratch. Traders on one platform cannot access depth from another. This is the equivalent of every stock exchange in the world refusing to share order flow with any other.
\
\ \ MYX V2 takes a different approach. Instead of operating as a standalone exchange, it repositions as a modular settlement engine, a shared layer that other products can plug into. Think of it like the difference between building a restaurant and building a commercial kitchen that multiple restaurants can use. Trading apps, automation platforms, and institutional desks can integrate with MYX's settlement rails without building their own clearing and margin infrastructure.
\ MYX CEO Ryan explains,
MYX V2 is more than just an exchange, it's an engine. Integrating EIP-7702 and permissionless oracles means we can make onchain perps trading seamless while preserving decentralized sovereignty. We're grateful to all our investors for aligning with our vision to redefine perpetual settlement standards.
\
At the technical level, V2 integrates two significant Ethereum standards. EIP-7702, which was introduced in Ethereum's Pectra upgrade on May 7, 2025, allows regular wallets (called externally owned accounts or EOAs) to temporarily function like smart contracts. In practice, this means users can batch multiple actions into a single transaction, have gas fees sponsored by the platform, and trade without the typical friction of approving each step separately. Alongside EIP-4337 account abstraction, this enables gasless, one-click trading while the user retains full custody of their funds.
\
The second component is Chainlink's permissionless oracle stack, which anchors prices directly to external data feeds rather than relying on order book depth. This is what enables MYX's zero-slippage execution model. A trader placing a large position does not push the price against themselves because pricing is derived from oracle feeds, not from the orders currently sitting in the book. MYX calls this its Dynamic Margin system, which supports up to 50x leverage.
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The timing of this raise matters. Onchain perpetual futures had a breakout 2025. According to Cointelegraph's reporting on DefiLlama data, cumulative perpetual DEX volume reached $12.09 trillion by year end, with $7.9 trillion, representing 65% of all lifetime volume, generated in 2025 alone. Hyperliquid dominated with roughly 80% market share at its peak, processing over $357 billion in monthly volume by August 2025.
\ But dominance by a single platform is itself a risk. Coinbase researcher David Duong noted in late 2025 that the surge was driven partly by the absence of a traditional altcoin season, pushing traders toward leverage as a substitute for spot gains. If that leverage demand becomes structural rather than cyclical, the infrastructure beneath it needs to scale accordingly.
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\ This is where the modular thesis comes in. MYX's bet is that the next phase of growth will not come from building more standalone exchanges, but from building settlement primitives that multiple front-ends, strategies, and institutions can share. The parallel in traditional finance would be clearinghouses like the DTCC or LCH, entities that sit beneath exchanges and ensure trades settle correctly across multiple venues.
\ MYX itself already has traction. According to DefiLlama and CoinMarketCap data, the protocol has processed significant volume across Linea, Arbitrum, and BNB Chain, with over 200,000 cumulative trading addresses prior to the V2 launch. Previous funding rounds included backing from HongShan (formerly Sequoia China), Hack VC, HashKey Capital, and Foresight Ventures.
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Consensys becoming the largest investor in MYX is not a casual allocation. It reflects a thesis that onchain derivatives are graduating from standalone exchanges into composable infrastructure, and that settlement is the layer where long-term value will accrue. The integration of EIP-7702 and permissionless oracles directly addresses the two issues that have historically kept institutional capital on centralized venues: execution friction and slippage risk.
\ Whether MYX captures meaningful market share depends on execution and ecosystem adoption. But the structural logic is sound. The derivatives market is moving onchain at an accelerating pace, and the protocols that become embedded infrastructure, not just trading interfaces, will likely define how that market operates for the next decade.
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2026-02-19 02:18:32
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What happens when the world's largest financial institution tells a cryptography startup that it cannot move forward without a technology that barely existed two years ago?
\ That is not a hypothetical. According to Fhenix founder Guy Zyskind, J.P. Morgan approached the company exploring the tokenization of roughly $1.5 trillion in assets under management, and the conversation made one thing clear: in his words, they "cannot do it even in theory without privacy for customers." The exchange, discussed on a recent X Space, captures a tension that has been building inside institutional blockchain adoption for years. Blockchains are transparent by design. That transparency, long considered a feature, is now the primary barrier to the next phase of growth.
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Public blockchains expose everything. Every balance, every transaction, every liquidation threshold is visible to anyone willing to look. For retail DeFi, this is an accepted tradeoff. For a bank managing institutional client portfolios, it is a structural problem.
\ J.P. Morgan put it plainly in its Project EPIC whitepaper, noting that "the lack of mature, on-chain cryptographic privacy solutions, coupled with the absence of consensus on implementing privacy-preserving digital identity, continues to create operational friction in tokenized asset interactions." The bank's Kinexys platform has processed over $1.5 trillion in transactions since launch, handling an average of more than $2 billion daily, yet its own research acknowledges that solving for on-chain privacy "could broaden adoption" in ways that current volumes do not yet reflect. That gap between what blockchains can do today and what institutions need them to do is exactly the market Fhenix is building for.
\ The tokenized asset market, for context, is projected to reach $16 trillion by 2030 according to various industry estimates. Today, tokenized money market funds alone sit at roughly $10 billion in assets, a figure that sounds large until you compare it to the $10 trillion traditional money market fund industry. The infrastructure gap is not technological in the compute or speed sense. It is a privacy gap.
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Most people who encounter Fully Homomorphic Encryption for the first time react with some version of the same confusion: if data is encrypted, how can you run calculations on it?
\ The analogy that helps most people is a lockbox with transparent gloves built into the sides. You can reach inside, move things around, and even rearrange the contents, but you can never see what you are touching, and you can never take anything out. FHE achieves this mathematically. It allows a system to perform arithmetic and logic operations on encrypted numbers without ever decrypting them. The result comes out still encrypted, and only the authorized party can open it. Think of a bank running a credit risk model on a client's encrypted portfolio: the model produces a score, the client receives that score, and no one at the bank ever saw the underlying holdings.
\ This is fundamentally different from the two privacy approaches most common in blockchain today. Zero-Knowledge proofs (ZK) allow you to prove a statement is true without revealing the underlying data, but they do not allow computation on that data in a general-purpose way. Trusted Execution Environments (TEEs) rely on secure hardware, meaning privacy collapses if the hardware is compromised. FHE is pure mathematics with no trusted hardware assumption and no limitation on what computations you can run. As Zyskind put it on the X Space, "Privacy is, I believe, the most difficult problem to solve in blockchains. Adding privacy on top of ZK, something like what Fhenix is doing, trying to build and scale Fully Homomorphic Encryption? Those are very, very hard problems to solve. Very few people can do that."
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Fhenix started as an FHE-powered Layer 2 blockchain and has since shifted its architecture toward a coprocessor model. The product is now called CoFHE, a stateless off-chain engine that handles the heavy cryptographic lifting. Smart contracts on any EVM-compatible chain, including Ethereum, Arbitrum, and Base, can call CoFHE with a single Solidity import. The coprocessor processes the encrypted computation, and only authorized parties receive the decrypted result.
\ The performance numbers matter here because FHE's historical weakness was speed. Earlier systems were too slow for anything resembling real-time finance. Fhenix claims CoFHE delivers throughput improvements of up to 5,000 times over earlier FHE systems, and its separate Threshold FHE Decryption research, accepted to the ACM CCS 2025 conference, recorded 20,000 times higher throughput and 37 times lower latency than prior benchmarks. That paper was accepted alongside research from Microsoft, Google, Meta, Stanford, and MIT. The company has also received a strategic investment from BIPROGY, one of Japan's largest IT service providers, specifically to expand into the Japanese financial sector.
\ The practical demonstration of this came through an experiment called Fhenix402, a private version of Base's x402 micropayment protocol that the team built in a single day. On Base Sepolia, a payment of $0.10 and a payment of $4.02 produced identical encrypted representations on-chain. An observer watching the blockchain could not tell the difference between the two. "You can't tell which is which, and that's exactly the point," Zyskind said.
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The J.P. Morgan conversation is the most striking data point, but it is not the only one. The bank's Kinexys Privacy POC explicitly explores on-chain privacy and composability, framing enhanced privacy as "crucial for improving access to digital assets." J.P. Morgan Asset Management recently launched its first tokenized money market fund, seeded with $100 million of its own capital on the Ethereum blockchain, with Kinexys handling the infrastructure. The fund is open only to qualified investors, but the architecture it represents, public blockchain plus institutional compliance requirements, is exactly the architecture that cannot scale without privacy.
\ Zyskind also drew a connection that is worth taking seriously: FHE uses the same underlying mathematics as post-quantum cryptography. As quantum computing becomes a credible threat to existing encryption standards, systems built on FHE have a structural advantage that extends well beyond current DeFi applications. This is the kind of long-cycle institutional consideration that banks actually think about, and it suggests the interest from players like J.P. Morgan is not opportunistic but foundational.
\ "We're at a true inflection point," Zyskind said at the launch of Fhenix402. "Circle, Stripe, and global enterprises are moving into blockchain payments. Privacy isn't optional anymore. It's the requirement that will make open payments viable."
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The framing Fhenix uses, that it is building the "backbone for confidential DeFi," is ambitious. But the underlying case is not speculative. J.P. Morgan's own research documents the problem. The tokenization market's growth trajectory is measurable. The performance benchmarks Fhenix is publishing are peer-reviewed, not marketing copy.
\ What I would watch carefully is the distance between demonstrated capability and production deployment. CoFHE is live on testnets and deployed on Base and Arbitrum Sepolia. Mainnet is still ahead. The gap between a cryptographic paper accepted at ACM CCS and a system that processes institutional-grade tokenized assets at scale involves engineering, regulatory, and integration layers that take time. The institutional interest is real, but institutional adoption timelines are slow by design.
\ FHE also remains one of the more computationally expensive cryptographic operations available, even with Fhenix's improvements. The 5,000-times throughput gain is measured against prior FHE systems, not against unencrypted computation. That distinction matters for anyone benchmarking against what traditional financial infrastructure can do today.
\ Still, the trajectory is credible. The problem is documented by the institutions themselves. The technology is advancing faster than most cryptographers expected even three years ago. And if blockchains are genuinely going to hold trillions in institutional assets, the question is not whether on-chain privacy infrastructure gets built. It is who builds it.
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