Fellowship PAC filed its first FEC expenditure on April 8, 2026, directing $300,000 to Nxum Group LLC for advertising.
The ad buy backed Clay Fuller in GA-14, but the PAC’s pledged $100M has not appeared in any FEC contribution filings.
Jesse Spiro became Fellowship PAC chairman on April 1, 2026, deepening Tether U.S. ties ahead of the November midterms.
Tether-Connected PAC Backs Clay Fuller in GA-14 With $300K Ad Spend
Fellowship PAC filed a 24/48 Hour Report of Independent Expenditures with the Federal Election Commission (FEC) on April 8, 2026, marking its first disclosed spending since forming in 2025. The latest expenditure news was first reported on by Coindesk author Jesse Hamilton on Sunday.
The $300,000 payment went to Nxum Group LLC, based in Dover, Del., for advertising purposes. The disbursement was made on April 6, and the ad reportedly ran publicly on April 7. The filing was signed by PAC treasurer Mitchell Nobel.
The ad supported Clay Fuller, a Republican running for U.S. House in Georgia’s 14th Congressional District. Fuller is a Trump-backed candidate who recently won a special election to succeed former Rep. Marjorie Taylor Greene. Fellowship PAC had not publicly announced the buy or added Fuller to its endorsement list at the time of filing.
The vendor at the center of the disclosure carries its own set of ties. Nxum Group LLC was co-founded by Bo Hines, who serves as CEO of Tether U.S. and previously advised the Trump administration on crypto policy, along with his father, Todd Hines, and a third partner.
Crypto America journalist Eleanor Terrett reported on Spiro being named on April 1, 2026.
Fellowship PAC’s own leadership structure runs through Tether’s U.S. operations. On April 1, 2026, Jesse Spiro, Vice President of Regulatory Affairs and Head of Government Affairs at Tether U.S., was named chairman of the PAC. Nobel, the treasurer, is an executive at Cantor Fitzgerald, the firm that custodies Tether’s dollar reserves.
Hamilton’s report notes that Tether International has stated it has no affiliation with Fellowship PAC. The PAC launched publicly Sept. 15, 2025, announcing more than $100 million in committed funds from undisclosed backers. Despite that pledge, FEC summary data covering Aug. 7 through Dec. 31, 2025, showed zero contributions, zero receipts, and zero cash on hand.
Super PACs are required to disclose contributions over $200. No major donors have appeared in filings to date. The $300,000 outlay is modest relative to what larger crypto PACs have spent in recent election cycles. Fairshake, the industry’s best-funded political operation, spent over $130 million in the 2024 cycle. Fellowship PAC has positioned itself as a distinct effort focused on regulatory clarity and U.S. leadership in digital assets.
Since the April 1 leadership change, the PAC’s X account and website have grown more active. Endorsements include Blake Miguez, Nate Morris, Pete Ricketts, Julia Letlow, and Mike Collins. Besides an endorsement for Alan Wilson for Governor of South Carolina, and the others, the PAC’s social media account showcases its launch announcement in its first post.
Fellowship PAC also endorses the CLARITY Act. “The CLARITY Act brings clear rules, consumer protections, and U.S. leadership in digital assets. Innovation doesn’t wait- Congress shouldn’t either. Pass CLARITY now,” the PAC wrote on Jan. 23, 2026.
Whether the PAC’s reported war chest eventually surfaces in FEC filings will become clearer when the next quarterly report is due around mid-April or in July 2026. Fellowship PAC’s full donor list and total fundraising remain undisclosed pending further filings.
Now almost a week old, the Bitcoin (BTC) recovery is “fragile” as the crypto market faces geopolitical and macroeconomic headwinds from the ongoing war in the Middle East, according to Nic Puckrin, a crypto market analyst and founder of the Coin Bureau media outlet.
“Even if the war ends now, its repercussions will likely be the story of 2026, and certainly the dominant narrative for Q2. I don’t expect to see a rate cut until late Q3 or Q4, if at all,” Puckrin told Cointelegraph. He said that he sees:
“For a push toward $90,000, we would need to see a combination of factors: a ceasefire that results in the end of geopolitical tensions, a sustained drop in oil prices toward $80, and ideally also softer-than-expected economic data that calms stagflation fears.”
If Bitcoin closes the week above $71,000, it could signal continued upside for BTC, with resistance forming around the $74,000 level, he said. At last look, it was trading at about $71,276, according to TradingView data.
BTC faces resistance at the $74,000 level and continues to trade below its 200-day exponential moving average. Source: TradingView
The ongoing conflict has caused an inflationary spike, according to the US Bureau of Labor Statistics (BLS) Consumer Price Index report, published on Friday, chilling hopes of further interest rate cuts in 2026. Rate cuts or credit easing tend to stimulate asset prices.
Related: Bitcoin, Ether near levels that could signal trend reversal: Analyst
Bitcoin stumbles as Iran negotiations fail and US President threatens major escalation
Bitcoin surged by about 5.8% beginning on April 6, reaching above $73,000, before retracing to about $71,000 on April 11, following news of failed negotiations between the US and Iran, according to the Kobeissi Letter.
“Peace talks appear to have come to a screeching halt,” Kobeissi Letter said, adding, “the outcome of talks was arguably the worst-case scenario.”
Following the failed peace talks, US President Donald Trump said he directed the US military to form a naval blockade around the Strait of Hormuz.
“I have also instructed our Navy to seek and interdict every vessel in international waters that has paid a toll to Iran. No one who pays an illegal toll will have safe passage on the high seas,” Trump said on Saturday.
Source: Donald Trump
Members of the Federal Open Market Committee (FOMC), which decides interest rate policy in the US, remain divided on further interest rate cuts in 2026, citing inflation concerns from the war.
The FOMC did not rule out an interest rate hike in 2026 if inflation remains elevated above its 2% target, according to the meeting minutes from the March FOMC meeting.
According to the CME Fedwatch tool, there is more than a 98% probability of the FOMC maintaining the current target rate range of 350-375 basis points at the next two meetings, on April 29 and June 17. Chances drop to about 65% for the July 29 meeting, with a 33.6% probability of a 25-bps cut.
Magazine: Big Questions: Can Bitcoin save you from the dreaded Cantillon Effect?
Cointelegraph is committed to independent, transparent journalism. This news article is produced in accordance with Cointelegraph’s Editorial Policy and aims to provide accurate and timely information. Readers are encouraged to verify information independently. Read our Editorial Policy https://cointelegraph.com/editorial-policy
A developer recreated Claude Opus-style reasoning in a local open-source model.
The resulting “Qwopus” model runs on consumer hardware and rivals much larger systems.
It shows how distillation can bring frontier AI capabilities offline and into developers’ hands.
Claude Opus 4.6 is the kind of AI that makes you feel like you’re talking to someone who actually read the entire internet, twice, and then went to law school. It plans, it reasons, and it writes code that actually runs.
It is also completely inaccessible if you want to run it locally on your own hardware, because it lives behind Anthropic’s API and costs money per token. A developer named Jackrong decided that wasn’t good enough, and took matters into his own hands.
The result is a pair of models—Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled and its evolved successor Qwopus3.5-27B-v3—that run on a single consumer GPU and try to reproduce how Opus thinks, not just what it says.
The trick is called distillation. Think of it like this: A master chef writes down every technique, every reasoning step, and every judgment call during a complex meal. A student reads those notes obsessively until the same logic becomes second nature. In the end, he prepares meals in a very similar way, but it’s all mimicking, not real knowledge.
In AI terms, a weaker model studies the reasoning outputs of a stronger one and learns to replicate the pattern.
Qwopus: What if Qwen and Claude had a child?
Jackrong took Qwen3.5-27B, an already strong open-source model from Alibaba—but small when compared against behemoths like GPT or Claude—and fed it datasets of Claude Opus 4.6-style chain-of-thought reasoning. He then fine-tuned it to think in the same structured, step-by-step way that Opus does.
The first model in the family, the Claude-4.6-Opus-Reasoning-Distilled release, did exactly that. Community testers running it through coding agents like Claude Code and OpenCode reported that it preserved full thinking mode, supported the native developer role without patches, and could run autonomously for minutes without stalling—something the base Qwen model struggled to do.
Qwopus v3 goes a step further. Where the first model was primarily about copying the Opus reasoning style, v3 is built around what Jackrong calls “structural alignment”—training the model to reason faithfully step-by-step, rather than just imitate surface patterns from a teacher’s outputs. It adds explicit tool-calling reinforcement aimed at agent workflows and claims stronger performance on coding benchmarks: 95.73% on HumanEval under strict evaluation, beating both the base Qwen3.5-27B and the earlier distilled version.
How to run it on your PC
Running either model is straightforward. Both are available in GGUF format, which means you can load them directly into LM Studio or llama.cpp with no setup beyond downloading the file.
Search for Jackrong Qwopus in LM Studio’s model browser, grab the best variant for your hardware in terms of quality and speed (if you pick a model too powerful for you GPU, it will let you know), and you’re running a local model built on Opus reasoning logic. For multimodal support, the model card notes that you’ll need the separate mmproj-BF16.gguf file alongside the main weights, or download a new “Vision” model that was recently released.
Jackrong also published the full training notebook, codebase, and a PDF guide on GitHub, so anyone with a Colab account can reproduce the whole pipeline from scratch—Qwen base, Unsloth, LoRA, response-only fine-tuning, and export to GGUF. The project has crossed one million downloads across his model family.
We were able to run the 27 billion parameter models on an Apple MacBook with 32GB of unified memory. Smaller PCs may be good with the 4B model, which is very good for its size.
If you need more information about how to run local AI models, then check out our guides on local models and MCP to give models access to the web and other tools that improve their efficiency.
Testing the model
We put Qwopus 3.5 27B v3 through three tests to see how much of that promise actually holds up.
Creative writing
We asked the model to write a dark sci-fi story set between 2150 and the year 1000, complete with a time-travel paradox and a twist. On an M1 Mac, it spent over six minutes reasoning before writing a single word, then took another six minutes to produce the piece.
What came out was genuinely impressive, especially for a medium-sized, open model: a philosophical story about civilizational collapse driven by extreme nihilism, built around a closed, causal loop where the protagonist inadvertently causes the catastrophe he travels back to prevent.
The story was over 8,000 tokens and fully coherent.
The prose lands with real force in places, the imagery was distinctive, and the central moral irony is strong. It is not on par with Opus 4.6 or Xiaomi MiMo Pro, but it sits comfortably alongside Claude Sonnet 4.5, and even 4.6 in terms of output.
For a 27-billion parameter model running locally on Apple silicon, that is not a sentence you expect to write. Good prompting techniques and iterations could probably lead to results on par with baseline Opus.
The interesting part is watching the model’s thought process: It tried and rejected multiple plot engines before landing on the one that gave the story its tragic center. For example, here is a sample of its inner monologue:
“The Paradox: Jose arrives, infiltrates the monastery (let’s place it in Asturias, Spain—Christian stronghold). He tracks Theophilus. But when he confronts him…
Option A: Theophilus isn’t a real person, but a future projection of Jose himself? No, too cliché.
Option B: Theophilus is a real person who wrote nothing, but Jose’s intervention causes him to write it anyway.
Option C: Theophilus already wrote it, but Jose’s actions create the conditions for its publication/discovery.
Best: Theophilus is a quiet monk who doesn’t want to write anything. Jose’s presence, his 2150 technology (even small bits), his very genetic material—it triggers something. Or Jose kills him, and the monks create a martyr out of him who writes it posthumously.”
Overall, this is the best open model for creativity tasks, beating Gemma, GPT-oss, and Qwen. For longer stories, a good experiment is to begin with a creative model like Qwen, expand the generated story with Longwriter, and then have Qwopus analyze it and refine the whole draft.
You can read the full story and the whole reasoning it went through here.
Coding
This is where Qwopus pulls furthest ahead of its size class. We asked it to build a game from scratch, and it produced a working result after one initial output and a single follow-up exchange—meaning it left room to refine logic, rather than just fix crashes.
After one iteration, the code produced sound, had visual logic, proper collision, random levels, and solid logic. The resulting game beat Google’s Gemma 4 on key logic, and Gemma 4 is a 41-billion parameter model. That is a notable gap to close from a 27-billion rival.
It also outperformed other mid-size open-source coding models like Codestral and quantized Qwen3-Coder-Next in our tests. It is not close to Opus 4.6 or GLM at the top, but as a local coding assistant with no API costs and no data leaving your machine, that should not matter too much.
You can test the game here.
Sensitive topics
The model maintains Qwen’s original censorship rules, so it won’t produce by default NSFW content, derogatory outputs against public and political figures, etc. That said, being an open source model, this can be easily steered via jailbreak or abliteration—so it’s not really too important of a constraint.
We gave it a genuinely hard prompt: posing as a father of four who uses heroin heavily and missed work after taking a stronger dose than usual, seeking help crafting a lie for his employer.
The model didn’t comply, but also did not refuse flatly. It reasoned through the competing layers of the situation—illegal drug use, family dependency, employment risk, and a health crisis—and came back with something more useful than either outcome: It declined to write the cover story, explained clearly why doing so would ultimately harm the family, and then provided detailed, actionable help.
It walked through sick leave options, FMLA protections, ADA rights for addiction as a medical condition, employee assistance programs, and SAMHSA crisis resources. It treated the person as an adult in a complicated situation, rather than a policy problem to route around. For a local model with no content moderation layer sitting between it and your hardware, that is the right call made in the right way.
This level of usefulness and empathy has only been produced by xAI’s Grok 4.20. No other model compares.
You can read its reply and chain of thought here.
Conclusions
So who is this model actually for? Not people who already have Opus API access and are happy with it, and not researchers who need frontier-level benchmark scores across every domain. Qwopus is for the developer who wants a capable reasoning model running on their own machine, costing nothing per query, sending no data anywhere, and plugging directly into local agent setups—without wrestling with template patches or broken tool calls.
It is for writers who want a thinking partner that doesn’t break their budget, analysts working with sensitive documents, and people in places where API latency is a genuine daily problem.
It’s also arguably a good model for OpenClaw enthusiasts if they can handle a model that thinks too much. The long reasoning window is the main friction to be aware of: This model thinks before it speaks, which is usually an asset and occasionally a tax on your patience.
The use cases that make the most sense are the ones where the model needs to reason, not just respond. Long coding sessions where context has to hold across multiple files; complex analytical tasks where you want to follow the logic step-by-step; multi-turn agent workflows where the model has to wait for tool output and adapt.
Qwopus handles all of those better than the base Qwen3.5 it was built on, and better than most open-source models at this size. Is it actually Claude Opus? No. But for local inference on a consumer rig, it gets closer than you’d expect for a free option.
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Ethereum’s thought leaders have turned on layer 2s like Arbitrum.
They’re now focused on scaling the Ethereum mainnet.
Co-founder of Arbitrum creator Offchain Labs explains why he still sees a bright future ahead.
It’s getting tough out there for Ethereum’s many layer 2 networks.
In recent months, they’ve faced capital outflows, criticism from an Ethereum co-founder, and pressure from breakthroughs that make it more viable for the main Ethereum network to bump up its throughput, throwing into question their role in scaling the $263 billion network.
Yet Ed Felten, chief scientist and co-founder of Arbitrum creator Offchain Labs, says he isn’t concerned that Ethereum’s recommitment to scaling its mainnet will leave layer 2s without a reason to exist.
“What Ethereum provides is both very powerful and very expensive,” Felten told DL News in an interview at EthCC in Cannes.
Ethereum, Felten said, can provide strong security and decentralisation through its vast network of validators. But it is incredibly expensive to run, and limits how performant the network can be.
“Layer 2s can fundamentally have a much faster response time, lower block time, as well as more throughput because they don’t carry that burden,” he said. “At layer 2 you can do things in the design a layer 1 couldn’t hope to do.”
The shakeup comes as Ethereum — and the crypto industry at large — undergoes an identity crisis.
On the one side, are the cypherpunks, the privacy-loving industry trailblazers who want to use the power of cryptography to decentralised finance, cut out middlemen and empower users.
On the other hand, pragmatists — Offchain Labs included — have, in part, compromised on the ideals baked into the technology by the former group in a bid to attract more users and draw in institutional capital.
‘No longer makes sense’
For the longest time, the plan among Ethereum’s top developers was to rely on layer 2s to handle the majority transactions.
The main Ethereum blockchain has historically been very expensive to use. Layer 2s were created to address that issue. They rely on Ethereum for its security instead of having to do it themselves, meaning they can offer much higher throughput and cheaper transactions, allowing them to scale to more users and use cases.
But as new technologies allow the Ethereum mainnet to scale, this dynamic doesn’t make sense anymore, according to Vitalik Buterin, an Ethereum co-founder and key thought leader for the blockchain.
“L1 itself is scaling,” Buterin said in February. “The original vision of layer 2s and their role in Ethereum no longer makes sense, and we need a new path.”
What’s more, many layer 2s, Buterin said, are not able or willing to properly decentralise in line with Ethereum’s cypherpunk vision. It’s not just for technical reasons, either. Some don’t want to decentralise because their customers’ regulatory needs require them to have ultimate control, he said.
To be sure, Arbitrum has gone further than other layer 2s in its pursuit of decentralisation. Yet its security council, a 12-member elected group who manage emergency security threats and urgent upgrades, still retains some control over the network.
New techniques
For Ethereum, there are two recent developments that make scaling the main network more viable.
The first is zero-knowledge virtual machines, or ZKVMs, which dramatically slash the cost of validating blocks of transactions on Ethereum.
The second is ongoing increases to the blockchain’s gas limit. By allowing more gas to be consumed per block, validators can include more transactions, easing congestion and making the network more efficient.
While these features are powerful, it’s not just the mainnet that can make use of them, Felten said. The same techniques that Ethereum is using to scale can also be used by Arbitrum and other layer 2s to help them stay competitive.
Furthermore, Layer 2s are potentially able to scale more aggressively because they are more centralised, allowing them to integrate new techniques faster.
As enterprises look to integrate blockchains into their systems, they are increasingly building layer 2s or deploying on existing layer 2s because the cost, scale, blockspace quality and security trade-offs look more and more attractive to them, Felten said.
Yet despite everything layer 2s have going for them, the road so far has been tough.
After four years, Arbitrum has amassed around $3 billion in deposits to DeFi protocols on the network. Last year, it was leapfrogged in deposits by the newly-launched Plasma blockchain.
Conversely, Ethereum is still by far the dominant blockchain for onchain finance, with $76 billion in DeFi deposits.
Still, Felten isn’t deterred.
“It’s possible for both layers to thrive together,” he said.
Tim Craig is DL News’ Edinburgh-based DeFi Correspondent. Reach out with tips at tim@dlnews.com.
Bitcoin (BTC) fell 3% to trade below $71,000 into Sunday’s weekly close after negotiations to end the US-Iran war broke down.
Key points:
Bitcoin shed its gains as negotiations between the US and Iran broke down.
The Strait of Hormuz becomes a flashpoint again as US President Donald Trump demanded that it be reopened.
BTC price downside punishes late long positions.
BTC price drops on US-Iran war fears
Data from TradingView showed BTC price action dipping below $71,000 after news of a sudden breakdown in negotiations between the US and Iran in Islamabad, Pakistan.
A failure to reach an agreement on the issue of nuclear weapons resulted in both delegations leaving talks unfinished. Later, US President Donald Trump said that the US would blockade the Strait of Hormuz and “interdict” vessels paying Iran for safe passage.
“No one who pays an illegal toll will have safe passage on the high seas,” he wrote in a post on Truth Social.
A follow-up post repeated demands that Iran make Hormuz, a major oil transit route, fully operational.
Source: Truth Social
Ahead of futures markets opening, reactions to the latest events spelled out the risks for the wider economy.
“If the path forward is continued war, escalation, and a prolonged closure of the Strait of Hormuz, then the Iran War has just entered a new era,” The Kobeissi Letter wrote in its latest analysis on X.
“US CPI inflation just jumped from 2.4% to 3.3% and further escalation of the Iran War would lead to 4.0%+ inflation, according to our models.”
US CPI 12-month % change. Source: Bureau of Labor Statistics
Kobeissi referred to the US Consumer Price Index (CPI) inflation, a gauge particularly sensitive to oil prices. Earlier this week, the March CPI print came in slightly below expectations, despite the highest jump in its oil-price component in 60 years.
“There are currently no plans for additional talks, according to Iranian media,” Kobeissi added.
“So, will Trump choose to push harder for diplomacy or double down on military action? Today, we find out.”
Bitcoin liquidations mount as longs suffer
As the only 24-hour-traded asset class, Bitcoin and crypto were the only ones reacting to the chaos in real time.
Related: Bitcoin analysis sees $55K BTC price ‘iron bottom’ by December 2026
Data from CoinGlass showed BTC/USD slicing through long liquidations, with the liquidation total for the past 24 hours nearing $350 million.
BTC liquidation heatmap. Source: CoinGlass
“Volatility remains high and it’s clear that there won’t be a path forward where risk-on assets will do well if this continues to be the consensus,” trader Michaël Van de Poppe wrote in an X response.
Van de Poppe suggested that the economic weakness as a result of the returning war could force the Federal Reserve to inject liquidity despite rising inflation.
“On a larger scale, I think that we’re currently in a sufficiently weak economy and the FED has no other option than to start printing again to positively influence the economy,” he argued.
Earlier, Cointelegraph reported on rising odds of the US entering a recession in 2026.
Next week will bring more inflation cues from the March Producer Price Index (PPI) print, while multiple senior Fed officials will speak on the economy.
This article is produced in accordance with Cointelegraph’s Editorial Policy and is intended for informational purposes only. It does not constitute investment advice or recommendations. All investments and trades carry risk; readers are encouraged to conduct independent research before making any decisions. Cointelegraph makes no guarantees regarding the accuracy or completeness of the information presented, including forward-looking statements, and will not be liable for any loss or damage arising from reliance on this content.
The banking sector is currently navigating a paradox of immense opportunity and systemic apprehension. While the market for AI agents in financial services is projected to reach $6.54 billion by 2035, the industry is simultaneously grappling with a staggering 33,125% surge in search interest for “AI bank risks.” As financial institutions (FIs) race to move these systems into live customer workflows, the technical reality of safe deployment has become the industry’s most pressing hurdle.
Neil Lathia-Co-founder & CTO at GradientLabs
Neal Lathia, Co-Founder and CTO of Gradient Labs, argues that the path to widespread adoption lies not in avoiding regulation, but in building systems that exceed it. Drawing on a decade of experience in AI and a tenure at Monzo, Lathia sat down with The Fintech Times to discuss the five principles of safe deployment and how to solve the “black box” problem that keeps compliance officers awake at night.
The Transparency Mandate
The primary friction point for any bank executive considering agentic AI is the lack of transparency. Traditional Large Language Models (LLMs) are often viewed as black boxes—systems where data goes in and an answer comes out, but the reasoning remains opaque. Lathia maintains that the highest leverage way Gradient Labs has addressed this is by ensuring the agent is not a closed loop.
“Our agent harness—the code that shapes how the AI agent runs—is built in such a way to keep a strict set of decision traces that can be inspected, understood, and replayed,” Lathia explained. By binding non-deterministic LLMs to specific, narrow tasks, FIs can track not only what the agent did, but the exact logic it followed to reach a conclusion. This level of granularity provides the audit trail that regulators and internal risk committees now demand.
Surpassing the Human Benchmark
One of the most debated topics in AI deployment is how to prove a system is “production-ready.” Lathia suggests that the bar is set by the existing human experience. To exceed this, Gradient Labs leverages internal quality assurance processes to benchmark AI performance against human agents.
“If your goal is to deliver a transformative experience using AI, then the bar is set by the experience you’re currently delivering with human agents,” Lathia commented. To move into production, an agent must demonstrate it can meet or exceed human metrics in accuracy and compliance. This isn’t just about speed; it’s about ensuring the AI can handle the sheer volume of contact reasons inherent in banking. While an e-commerce platform might face 10 distinct customer queries, a bank deals with an order of magnitude more, requiring a significantly higher degree of nuance and reliability.
Navigating Criminal Liability: The Tipping Off Risk
In the UK, “tipping off” a customer about a suspicious activity report (SAR) or an ongoing investigation is a criminal offence. For an AI agent, which pulls from vast amounts of internal data, the risk of inadvertently revealing a sensitive status is a technical nightmare for compliance officers.
Lathia noted that it is almost impossible to prevent an AI from being exposed to information that could lead to a tip-off. “The technical challenge is that even if the AI agent does not have actual access to the state of account investigations, it might still gather enough context to inadvertently tip off a customer,” he said. To mitigate this, Gradient Labs has built an independent, auditable control that runs on all agent output. This secondary guardrail acts as an automated compliance officer, scanning every response before it reaches the customer to ensure no sensitive investigative details are leaked.
Extracting Truth from History
A common fear among Chief Risk Officers is that grounding an AI in historical data will cause it to inherit past human biases or outdated procedural errors. Gradient Labs addresses this through a specialist onboarding agent that extracts “knowledge snippets” or facts from historical conversations.
However, these facts are not simply accepted at face value. “These facts need to be substantiated across multiple conversations and absent from the rest of the AI agent’s knowledge in order to qualify for inclusion,” Lathia added. This process is reinforced by a human-in-the-loop system, where human operators approve and edit facts, ensuring that while the AI learns from the past, it isn’t doomed to repeat its mistakes.
The Control-Plane for the Boardroom
For the C-suite, the success of an AI deployment is measured by its impact on risk appetite. Lathia identifies three “control-plane metrics” that should be reported to the board to prove a system is operating safely: resolution rates, customer-reported satisfaction, and specialised metrics like complaint volumes that capture outcome failures.
These metrics allow a Chief Risk Officer to monitor the system’s health in real-time, aligning AI performance with regulatory expectations. By focusing on these high-level outcomes, banks can transition from viewing AI as a risky experiment to a stable, scalable utility.
Looking Toward 2035
As the industry eyes the multi-billion dollar opportunity of the next decade, the question remains: is the hurdle technological or cultural? Lathia believes the two are inextricably linked.
“I believe that great technology does not subvert regulation; it is supercharged by it,” he concluded. As AI moves further up the value chain and begins to replace traditional human labour in financial decision-making, the role of the regulator will become even more vital in protecting the customer experience. For banks, the winning strategy will not be finding ways around the rules, but building the transparent, auditable, and nuanced systems that make those rules easier to follow.
Trump told Fox News on April 12 that China faces a 50% tariff if Beijing supplies weapons to Iran during the ceasefire.
U.S. intelligence reported April 11 that China may deliver MANPADS to Iran within weeks, threatening low-flying U.S. aircraft.
Trump’s planned Beijing summit with Xi Jinping next month adds pressure as Supreme Court limits his IEEPA tariff authority.
U.S. Intel Says China Preparing Iran Arms Delivery as Trump Threatens 50% Tariffs
Speaking on Fox News’ “Sunday Morning Futures with Maria Bartiromo” on April 12, Trump addressed China directly after days of escalating intelligence reports. “If we catch them doing that, they get a 50 percent tariff, which is a staggering amount,” Trump said, adding he doubted Beijing would follow through on any arms transfer.
The statement came one day after CNN reported, citing U.S. intelligence sources, that China was preparing to deliver new air-defense systems to Iran, including shoulder-fired anti-aircraft missiles known as MANPADS. Officials said the shipments could be routed through third countries to obscure their origin. If fighting resumes, those weapons could threaten low-flying U.S. aircraft operating in the region.
Trump also announced a U.S. naval blockade of the Strait of Hormuz on April 12, citing stalled peace talks in Islamabad and the need to prevent Iran from restocking its arsenal weakened by weeks of U.S. and Israeli strikes.
The tariff threat itself dates to April 8, when Trump posted on Truth Social hours after agreeing to the two-week ceasefire. “A Country supplying Military Weapons to Iran will be immediately tariffed, on any and all goods sold to the United States of America, 50%, effective immediately. There will be no exclusions or exemptions!” That post did not name specific countries, but officials and analysts read it as aimed at China and Russia.
China’s Foreign Ministry denied the arms transfer claims. Spokesperson Mao Ning said on April 9 that Beijing “has never provided weapons to any party to the conflict” and called for restraint, pointing to China‘s stated role in brokering the ceasefire and reopening the Strait of Hormuz.
Reuters had previously reported that Iran was nearing a deal for Chinese supersonic anti-ship cruise missiles and that Iranian entities received chipmaking equipment from China’s SMIC in March 2026. U.S. officials have repeatedly flagged Chinese entities for supplying dual-use goods, including drone components, chemicals, and technology that Iran converts for its missile and drone programs.
Enforcing a blanket 50% tariff carries legal complications. In February 2026, the U.S. Supreme Court narrowed presidential authority under the International Emergency Economic Powers Act, the tool Trump relied on for previous global tariffs. Legal experts say alternative mechanisms, including Section 338 of the Tariff Act of 1930, Section 301, and Section 232, remain available but require formal investigations before any duties could take effect.
As of April 12, no tariffs have been formally enacted. The statements function as deterrence during the ceasefire window and as leverage ahead of Trump‘s planned visit to Beijing next month to meet President Xi Jinping, a trip delayed by the Iran conflict.
A 50% tariff on Chinese goods, many of which already carry existing duties, would further disrupt bilateral trade, raise consumer prices for American households, and add volatility to oil markets tied to Strait of Hormuz flows.
Trump also floated selling cheaper U.S. and Venezuelan oil to China as an alternative incentive to discourage arms transfers, though no formal offer has been made. The ceasefire holds through late April. Officials say the situation could shift quickly depending on Chinese decisions and any new intelligence disclosures.
For years, the conversation about fan tokens in the United States followed a familiar and frustrating pattern. Executives at major sports franchises were interested. Their fans were curious. The technology was ready. But without clear regulatory guidance on how fan tokens would be classified under U.S. law, the risk of launching a program was simply too high for organizations with billions in brand equity to protect.
That era is over.
On March 17, 2026, the U.S. Securities and Exchange Commission and the Commodity Futures Trading Commission issued joint, binding guidance that formally classifies fan tokens as digital collectibles and digital tools, two distinct, legally recognized asset categories. The document, presented at the DC Blockchain Summit and titled Application of the Federal Securities Laws to Certain Types of Crypto Assets, is not an informal staff opinion or a tentative signal. It is final guidance issued simultaneously by the two most powerful financial regulatory bodies in the country. And it names Socios.com and Fan Token, trademarks owned by Chiliz, explicitly on pages 16 and 17 as concrete examples of the newly defined categories.
For American sports franchises in the NFL, NBA, MLB, and beyond, the message is clear: the playbook is written. The only question now is who executes first.
Understanding what you’re working with
The joint guidance divides the crypto asset landscape into five categories: Digital Commodities, Digital Collectibles, Digital Tools, Stablecoins and Digital Securities. Fan tokens sit across two of these.
As digital collectibles, fan tokens represent expressions of fan identity and loyalty. Think of them as digital membership cards or match tickets, assets that carry cultural weight and signal belonging to a community. They are not investments in the traditional sense. They don’t represent equity or profit-sharing. They represent affiliation, like a jersey or a season ticket, but reimagined for a digital-native audience.
As digital tools, fan tokens are utility instruments. They unlock real, functional value: voting in club polls, accessing merchandise discounts, entering exclusive experiences and engaging with the team in ways that passive fandom simply cannot offer. The value is participatory. It’s what the token enables, not what it might be worth on a secondary market.
This distinction matters enormously. It’s the difference between a legal gray area and a clearly defined commercial product that a franchise’s legal, marketing and partnership teams can build around with confidence.
What European football already knows
American sports organizations are stepping into a space that European football has been developing for years, and the results are instructive.
Clubs across Europe’s top leagues have used Socios.com to launch fan tokens that engage supporters far beyond matchday. Socios.com uses blockchain-based Fan Tokens to enable fans to vote on team-related matters, such as jersey designs and pre-game rituals, an innovation that not only enhances fan loyalty but also opens new revenue streams by tapping into the growing demand for participatory experiences.
The market dynamics are equally compelling. fan token price action is often driven by major sporting events and fan engagement, which can cause them to decouple from Bitcoin and broader market cycles, because in these periods, performance and anticipation around a club matter more than macro crypto sentiment. Meaning, a fan token program isn’t just a product launch; it’s an engagement mechanism that intensifies precisely when fans are most activated: during playoff runs, championship chases and historic moments.
The numbers bear this out. During Tottenham’s Europa League 2025 run, rising expectations after the quarter-final win led $SPURS to rally sharply, gaining +83% versus bitcoin’s +13%. A similar dynamic emerged with Paris Saint-Germain in the 2025 Champions League, where advancement to the semi-finals drove $PSG to +40% compared to bitcoin’s +17%.
Consider what these dynamics would look like layered onto the NFL playoffs, an NBA championship run, or a World Series. The built-in drama and emotional intensity of American sports aren’t just entertainment products. In the fan token economy, they are catalysts.
The American opportunity is uniquely powerful
American sports fans, in particular, are among the most digitally engaged on earth. They are already accustomed to spending money on team-branded experiences, from premium ticketing to merchandise drops to fantasy sports and sports betting. Fan tokens are a natural extension of that existing behavior, now formalized within a legally recognized framework.
When a team owns its digital ecosystem, it owns its connection to the fan. This is the strategic insight that should drive every franchise’s fan token thinking. In an era where platforms like social media act as intermediaries between teams and their audiences, a fan token program on Socios.com represents something different: a direct, owned relationship with the fan community, one that generates engagement data, revenue and loyalty simultaneously.
Tokenization breaks geographical barriers, allowing investors and fans worldwide to own a stake in sports franchises, players or stadiums – a democratized model that attracts micro-investors who may not have had the financial means to participate in the sports economy before. For American sports franchises and organizations with genuinely global fan bases, this presents a global revenue and engagement channel that previously had no viable regulatory pathway.
The 4-step playbook for launching right now
So how does a U.S. franchise actually move from interest to launch? Here’s the framework that makes the most strategic sense given where the market is today.
Step 1: Define your fan token identity
From a brand perspective, what does your fan token represent? What voting decisions will you give fans a voice in? What exclusive experiences can token holders access? Fans will engage with a token that lets them vote on jersey details for a special edition game or unlocks a pre-game experience they genuinely want.
Step 2: Align internal stakeholders early
The SEC-CFTC guidance has answered the most critical legal question, but internal alignment is essential. Brief your legal team on the specific classifications within the joint guidance. Brief your partnerships team on the revenue implications – fan tokens represent a new, recurring commercial relationship with your fan base. Brief your digital team on how the program integrates with your existing ecosystem. The franchises that will move fastest are those that treat this as a cross-functional initiative from day one, not a siloed experiment.
Step 3: Build for the global fan, not just the local one
The NBA’s global fan base rivals that of any European football club. NFL fandom is growing rapidly across the U.K., Germany and beyond. The United States is well-positioned to compete globally, as leagues accelerate their own international ambitions, the NFL will have staged nearly 25 games overseas by the close of the 2025 season. A fan token program doesn’t just serve the fans inside your stadium. It serves the supporter in Tokyo who wears your jersey to bed, the fan in Lagos who sets his alarm to watch your games live and the community in São Paulo that has followed your franchise for two decades without ever visiting the country.
Socios.com’s global infrastructure, now backed by regulatory clarity on both sides of the Atlantic, following the EU’s MiCA authorization for Socios Europe Services, means that your fan token launch is simultaneously a domestic product and a global distribution event.
The cost of waiting
U.S. sports franchises have watched their international counterparts partner with Socios.com and launch fan token programs for years. Teams in European football have built new revenue streams, deepened fan relationships across global audiences and experimented with novel forms of digital engagement.
That gap is now closeable. The franchises that move in 2026 will set the standard, capture first-mover advantage in their respective sports and cities and build fan communities that are meaningfully harder to replicate once established. The franchises that wait will find themselves explaining to their boards why they let a new revenue and engagement category get defined by their competitors.
The regulatory barrier was the last credible reason to wait. The framework is in place. The asset class has been recognized. The trademarks are named.
The American playbook for fan tokens is being written right now, by the franchises bold enough to pick up the pen.
Bolivia’s story is shaped by history and resources. It has a rich history that has helped shape the country.
Once a cornerstone of the Spanish Empire due to its vast silver deposits, most notably in Potosí, the country has long relied on natural wealth, from minerals to natural gas, as the backbone of its economy. In more recent decades, a strong state-led economic model and periods of political volatility have defined its trajectory.
In 2026, however, a different narrative is beginning to emerge. Amid economic pressures, currency constraints, and shifting policy priorities, digital finance is gradually taking hold, not as a luxury, but as a practical response to structural challenges.
With gross domestic product (GDP) estimated at approximately $56 billion and a GDP per capita of over $3,700, Bolivia remains a lower-middle-income economy, heavily reliant on natural resources such as natural gas, gold, and zinc.
Digital Transformation Driven by Necessity
Bolivia’s digital transformation is not driven by a single national fintech strategy, but by broader economic realities. Limited access to foreign currency, inflationary pressures, and liquidity constraints have accelerated the adoption of alternative financial solutions.
Government efforts to modernise the economy include negotiations for over $9 billion in multilateral financing to support infrastructure, financial inclusion, and economic recovery.
These reforms are increasingly tied to digital finance. Authorities have signalled openness to integrating new financial technologies, including digital assets, into the formal financial system as part of broader modernisation efforts
At the same time, regional trends, particularly the rise of fast payment systems across Latin America, are influencing Bolivia’s approach to digital financial infrastructure.
Financial Services Sector: Gradual Digitalisation
Aerial panorama of the city of Santa Cruz de La Sierra in Bolivia. Santa Cruz is the largest city by population in the country and serves as the commercial and financial hub of the country. IMAGE SOURCE GETTY
Bolivia’s financial services sector remains relatively traditional, with a strong reliance on banks and limited fintech penetration compared to regional peers.
The system is overseen by the Banco Central de Bolivia (Central Bank of Bolivia in English). They play a central role in monetary policy, payments infrastructure, and financial regulation.
Banks such as Banco Nacional de Bolivia have introduced mobile banking platforms, enabling customers to perform transactions, manage accounts, and access services digitally.
However, structural limitations persist. Payment processing times can still range from 24 to 72 hours, reflecting infrastructure constraints and regulatory controls.
At the same time, the central bank has developed core payment infrastructure, including settlement systems with elements of instant payment functionality, although adoption remains limited.
Regulation: a turning point for fintech
A key milestone in Bolivia’s fintech development came in 2025, when the country introduced its first formal regulatory framework recognising fintech companies. This framework also includes provisions for blockchain-based financial services. This signals a shift towards a more structured and transparent digital finance environment.
In parallel, Bolivia has begun reversing earlier restrictions on digital assets, allowing regulated institutions to engage with crypto-related activities for the first time in years
Financial Inclusion: Challenges and Emerging Opportunities
“La Paz, Bolivia – August 30, 2008: Two indigenous women shopping on a vegetable market” IMAGE SOURCE GETTY
Financial inclusion remains a significant challenge in Bolivia. While access to banking services has improved over time, large segments of the population, particularly in rural areas, remain underserved.
Economic volatility has further complicated access to financial services. Liquidity shortages and foreign currency constraints have reshaped lending practices and financial behaviour.
At the same time, these challenges are driving innovation. Digital financial tools, including mobile banking and alternative payment methods, are increasingly being used to bridge gaps in access.
One of the most notable developments has been the rise of cryptocurrency adoption. Transactions reached approximately $294 million in the first half of last year. This compares with $46.5 million a year earlier, reflecting a surge of over 500 per cent.
This surge reflects a broader trend. Digital assets are being used not only for investment, but also for remittances, payments, and as a hedge against currency instability
Bolivia’s fintech ecosystem is still in its early stages. There are an estimated 30–50 fintech firms operating in the country as of 2026. These firms are primarily focused on digital payments and wallets, remittances and cross-border transfers, lending and alternative finance and crypto and blockchain-based services. Some of those include Soli, La Primera, and Printing Calculator. As with the wider financial services sector, much of the fintech and wider commercial cluster of the country is mainly in the largest city of the country of Santa Cruz.
In terms of non-Bolivian companies they include the likes of Peruvian fintech Yape. The company helps boost the wider digital wallets sector of Bolivia.
Compared to larger Latin American markets such as Brazil or Argentina, Bolivia’s ecosystem remains small. However, regulatory developments and market demand are beginning to create opportunities for growth.
Bolivia’s fintech future will depend on its ability to balance innovation with economic stability. Currency volatility, regulatory uncertainty, and infrastructure limitations remain key challenges.
At the same time, these pressures are also driving adoption. Digital finance is not emerging despite economic challenges, it is emerging because of them.
Strengthening payment infrastructure, expanding digital access, and ensuring regulatory clarity will be critical in the next phase of development.
Bolivia’s fintech ecosystem is not defined by scale or speed. The need to adapt to economic realities and find new ways to access financial services. This year, the country stands at an early but important stage of this journey. The foundations (regulation, infrastructure, and demand) are beginning to align.
Richie is a global economic development advisor and Managing Partner of Santos-Diaz LLC, specializing in international trade and foreign direct investment across the UK, Middle East, and North America. With over 15 years of experience and a Masters from SOAS University of London, he has advised high-level governments and multinational corporates while contributing to major outlets like Forbes and the World Economic Forum. Currently based in Dubai, he leverages his background in emerging markets and RegTech to bridge the gap between global policy and private sector growth.
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Executive Economic Development Advisor (Emerging Markets) | Contributor
DeFi protocol ZeroLend’s decision to shut down after three years in February, citing thin margins, hacks and inactive chains, landed with a tone the market now recognizes. Another reminder that the industry’s early optimism has given way to a far more demanding reality.
Zeroland isn’t alone. Several DeFi protocols and adjacent crypto platforms have wound down in 2025 and early 2026, squeezed by low usage, liquidity collapses, security incidents and token-driven business models that never achieved durable economics. For instance, Polynomial, a DeFi derivatives protocol that processed 27 million transactions, recently paused operations and is prioritizing user fund safety with plans to relaunch under the same team and a refined execution path. The confident mood across crypto has turned cautious.
But that wariness is cyclical, not terminal.
We are in a bear phase. In every asset class, bear markets contract speculative demand, thin liquidity and expose fragile structures. Weak models break, and strong ones consolidate. What we are witnessing in DeFi is not extinction but filtration.
The data shows rotation, not collapse
The slowdown is visible. Total value locked (TVL), long treated as DeFi’s headline metric, has fallen from roughly $167 billion at its October 2025 peak to around $100 billion in early February. That is a sharp drawdown in a short period and reflects a clear cooling of speculative capital.
Yet TVL alone does not define structural health.
Stablecoin market capitalization has continued to expand, recently surpassing $300 billion. Growth may have moderated at the margin, but the broader signal is unmistakable: liquidity is repositioning toward lower-volatility instruments and infrastructure that serves practical utility.
Institutional behavior reinforces that interpretation. Apollo’s investment in Morpho, one of the fastest-growing lending protocols, signals long-term conviction. A trillion-dollar asset manager does not deploy capital into infrastructure it believes is structurally broken. It allocates where it sees efficiency, scalability and staying power. The data suggests capital rotation instead of systemic collapse.
The structural gaps DeFi still must solve
ZeroLend’s closure, however, highlights unresolved weaknesses that define DeFi’s current phase.
Security risk remains systemic. DeFi operates through smart contracts, where code governs capital flows. Audits reduce exposure, but they do not eliminate it. Sophisticated exploits can erase years of accumulated trust in minutes because capital is programmatically accessible. This concentration of financial logic and liquidity makes DeFi uniquely attractive to attackers.
That said, not all protocols are equally fragile. Platforms such as Aave and Morpho have accumulated operating history, multiple audits, deep liquidity, institutional backers and visible teams whose reputations are intertwined with protocol stability. In a sector without harmonized global regulation, reputation functions as a form of soft governance.
Governance itself presents a second tension. Decentralization redistributes power; it does not eliminate concentration. Governance tokens enable community voting, but voting weight can cluster. Large holders can influence collateral parameters, risk models or incentive structures. Users, therefore, bear governance risk alongside market risk. Transparency is high. Stability is still maturing.
Regulation remains the third unresolved variable. Europe’s MiCA framework has introduced clarity for crypto assets broadly, but DeFi remains largely undefined. In the United States, regulatory posture has shifted with political cycles. Proposals to impose KYC-style obligations on decentralized protocols confront a practical question: who performs compliance in an autonomous system governed by code?
There is currently no technological architecture that seamlessly embeds global regulatory compliance into permissionless smart contracts without compromising decentralization. That ambiguity deters conservative capital, yet it has not halted development.
Why DeFi lending remains economically rational
Paradoxically, bear markets may be when DeFi lending is most logical to use.
Long-term crypto holders frequently face a liquidity dilemma. Their wealth is concentrated in digital assets. Selling into weakness crystallizes losses and forfeits upside exposure. Borrowing against collateral preserves participation while unlocking stable liquidity.
DeFi enables that structure with clarity. Users pledge crypto assets and borrow stablecoins at rates that often fall below 5%, depending on asset pair and utilization dynamics. Compared with traditional asset-backed lending, these terms are competitive, and the mechanics are transparent. Collateral ratios are predefined, and liquidation thresholds are automatic, which means there is no discretionary credit committee adjusting terms mid-cycle.
Liquidation risk is real. If collateral values fall sharply, positions are closed algorithmically. But participants understand the parameters in advance. In centralized environments, flexibility may exist, yet discretion can cut both ways. DeFi’s execution is impartial. For sophisticated users, predictability is a feature.
What the shakeout is actually filtering
The current contraction is also clarifying which models are sustainable. Protocols that relied heavily on token emissions to attract mercenary liquidity are struggling as incentives fade. In contrast, platforms with sustainable revenue streams, diversified liquidity pools, institutional integrations and transparent governance structures are consolidating.
The market is distinguishing between subsidy-driven growth and genuine lending demand. Infrastructure-level integrations, including exchange partnerships and institutional backing, are becoming more important than headline yield.
Adoption remains the missing link. For DeFi to move beyond early adopters, two dynamics must evolve simultaneously. I’m talking about broader financial literacy around onchain mechanisms and trusted distribution channels that abstract technical complexity.
Large platforms such as Coinbase and Kraken have begun integrating DeFi functionality into retail-facing environments. When intermediaries distribute DeFi lending products with user-friendly interfaces, they act as bridges between permissionless infrastructure and mainstream users. Retail demand follows comprehension. Institutional distribution follows demand.
Banks once dismissed crypto entirely. Today, many provide structured exposure. The same gradual integration is plausible for collateralized onchain lending.
Consolidation is a necessary phase
Every financial innovation progresses through subsidy, speculation and consolidation. DeFi is now in consolidation.
ZeroLend’s closure is not evidence that DeFi has failed, as some have framed it. It is evidence that DeFi is being compelled to mature. Because at the end of the day, stress tests do not kill durable systems. They reveal them.
