This week, the digital economy conversation kept moving towards one big question: what happens when AI and digital assets stop being experiments and become infrastructure?
In AI, the focus was on governance, security and the operational reality of deploying agents at scale. The EU’s AI Act transparency rules came into force, OpenAI published new research on how AI is changing work, NVIDIA launched a major open AI security alliance and regulators started asking harder questions about AI systems that can behave in unexpected ways.
In digital assets, the week was about institutional rails and market structure. Circle bought IBM’s blockchain patent portfolio. South Korean trade receivables moved on-chain. Securitize added further Wall Street credentials. Lido began a major staking infrastructure upgrade. Prediction markets continued attracting mainstream attention.
The theme is clear: AI and blockchain are both being pulled into regulated, high-stakes environments. The technology is getting more powerful, but that only increases the need for trust, safeguards and serious operating models.
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From the Network
Experts in the Loop Podcast: Raymond Sun on LegalQuants, legal AI and the builder mindset
In this week’s episode of Experts in the Loop, Mark Monfort and Chris Sinclair were joined by Raymond Sun, technology lawyer and co-founder of LegalQuants, for a practical conversation on legal AI, AI-native lawyers and what it means for professionals to move from using tools to building workflows.
Raymond described LegalQuants as a global network of lawyers who are not just prompting ChatGPT or Claude, but building apps, APIs, MCP servers, open-source tools and custom AI harnesses to solve problems in their own practice areas. He framed the “legal quant” as someone who combines legal judgement, technical ability and market awareness to find new ways of delivering legal work.
The episode also covered Raymond’s own path into AI, including his earlier work using machine learning to analyse K-pop dance synchronisation, long before the current generative AI wave. That story set up one of the episode’s strongest themes: good AI work starts with a real use case, not with the technology itself.
A few key ideas stood out:
1. Legal AI is moving from prompting to building The most interesting work is not just lawyers asking AI to write a first draft. It is lawyers learning how to build structured workflows, test outputs, use APIs, design tools and understand where different parts of the stack fit together.
2. Better AI users do not just “token max” Raymond argued that as people become more advanced, they become more disciplined with AI. Instead of throwing every task at a frontier model, they learn when to use deterministic tools, scripts, smaller models, structured workflows and human review. That matters as model costs rise and businesses begin treating AI usage as an operating cost.
3. Organisations need mental sovereignty A major theme was resilience. If one AI model disappears, becomes too expensive or is restricted by policy, teams still need to keep working. Businesses should avoid designing processes that are completely dependent on one model, one vendor or one interface.
4. Human review should be built into the workflow, not bolted on at the end Raymond’s advice was to “attack the problem”. Instead of letting AI produce a large output and then manually reviewing everything afterwards, professionals should narrow the question, structure the task and involve humans at key decision points along the way. That makes review more manageable and keeps judgement where it belongs.
5. Professionals should learn to think in formats One of the most practical takeaways was Raymond’s point that many workflows come down to formats: Word, PDF, JSON, CSV, XML, HTML and structured data. Once people understand how information moves between formats, AI workflows become less mysterious and easier to design.
The broader message was clear: AI transformation is not just about buying software. It is about people learning to break down problems, understand the tools available to them and build systems that fit the work.
Watch the latest episode here:
This week in AI news
EU AI Act transparency rules arrive
The EU’s new AI transparency obligations came into force from 2 August 2026, requiring clearer disclosure when people are interacting with AI systems and when content has been AI-generated or materially altered. The Guardian reported that authentic-looking AI content will need to be labelled, while the Financial Times described the shift as AI’s “cookie banner moment”. The European Commission also published material on codes of practice and transparency obligations for AI-generated content.
This matters because the AI debate is moving from principles to implementation. Labelling sounds simple until businesses have to apply it across chatbots, marketing material, images, videos, customer service systems and agent workflows. Transparency is now becoming a product design problem, not just a legal footnote.
Read more: The Guardian, Financial Times, European Commission
EU engages OpenAI and Anthropic after AI agent security incidents
Reuters reported that the European Commission is in talks with OpenAI and Anthropic following recent incidents involving AI agents and cybersecurity testing. The timing is significant because the EU’s AI Act enforcement powers are now coming into sharper focus, particularly for general-purpose AI models and high-risk systems.
This is exactly the point where AI governance becomes operational. It is not enough to say a model has safety rules. Regulators want to understand testing, incident reporting, monitoring and what happens when an AI system behaves in ways that could create real-world harm.
Read more: Reuters
OpenAI publishes research on how AI is expanding work
OpenAI published new research under its Work at the Frontier series, looking at how workers are using ChatGPT to take on tasks beyond the traditional boundaries of their roles. OpenAI said its data suggests 16.8% of work-related messages and 43.5% of occupation-specific messages involve tasks associated with another occupation.
This is useful because it points to a more nuanced labour market impact than “AI replaces jobs”. AI is helping workers cross into adjacent tasks, learn new workflows and stretch role boundaries. For businesses, the real question is how to redesign work around that shift rather than just drop AI tools into existing structures.
Read more: OpenAI
OpenAI cuts prices for GPT-5.6 model tiers
OpenAI updated its GPT-5.6 announcement on 30 July, cutting the price of GPT-5.6 Luna by 80% and GPT-5.6 Terra by 20%. The original GPT-5.6 release was earlier in July, but the pricing change belongs to this week.
This is a big enterprise AI story because model capability is only half the equation. Cost per successful task is quickly becoming the real metric. As businesses start using AI for ongoing workflows, research, coding, agents and customer operations, the price of tokens becomes a boardroom issue.
Read more: OpenAI
NVIDIA launches Open Secure AI Alliance
NVIDIA and founding members launched the Open Secure AI Alliance on 27 July, aiming to build and share open tools for AI safety and security. The alliance includes major technology and security organisations, though OpenAI, Anthropic and Google were notably absent from the founding group.
This is a strong sign that AI security is becoming its own infrastructure layer. As agents get access to tools, code, APIs and enterprise systems, companies need shared ways to test, secure and monitor them. The closed-model versus open-model debate is also becoming a security debate, not just a philosophical one.
Read more: NVIDIA and The Verge
Australian AI consumer safety priorities continue to take shape
Assistant Minister for Science, Technology and the Digital Economy Andrew Charlton outlined AI consumer safety priorities as part of Australia’s broader National AI Plan. The priorities include privacy reform, copyright protections, automated decision-making, transparency and consumer safeguards.
This is worth keeping in the newsletter because Australia is moving from general AI enthusiasm to a more detailed policy programme. The local conversation is now about how to make AI adoption safe enough for public services, consumers, creators and businesses.
Read more: Department of Industry, Science and Resources
This week in Blockchain news
Circle acquires IBM’s blockchain patent portfolio
Circle announced that it had acquired IBM’s blockchain patent portfolio, covering more than 680 patent families and nearly 1,000 issued patents globally. Circle said the acquisition makes it the leading US holder of blockchain patents and strengthens its position in on-chain financial infrastructure.
This is more than a patent story. It shows that the stablecoin sector is maturing into an infrastructure industry where intellectual property, defensive moats and enterprise-grade systems matter. Circle is not just competing on USDC circulation. It is positioning itself as a serious financial infrastructure company.
South Korea’s POSCO puts receivables on-chain with LG CNS
CoinDesk reported that South Korean trading giant POSCO is working with LG CNS to issue, transfer and settle trade receivables on-chain using Injective. The company operates across steel, energy and battery materials, making this a real-world tokenisation use case rather than a purely crypto-native experiment.
Receivables are a strong fit for tokenisation because they sit inside supply chains, financing relationships and working capital flows. If these assets can be represented and settled more efficiently on-chain, tokenisation starts to move beyond capital markets and into industrial finance.
Read more: CoinDesk
Securitize adds SEC investment adviser registration
Securitize added an SEC investment adviser registration as it continues building out its Wall Street credentials. CoinDesk reported that the move strengthens Securitize’s position as institutional tokenisation expands.
This matters because the tokenisation sector increasingly needs regulated entities, not just smart contracts. As more funds, securities and real-world assets move on-chain, the winners will need legal permissions, compliance infrastructure and institutional trust.
Read more: CoinDesk
Lido begins $16.5 billion Ethereum staking migration
Lido began moving around US$16.5 billion in staked Ether as part of a major validator consolidation and infrastructure upgrade. CoinDesk reported that the move is designed to reduce validator count and align with Ethereum’s post-Pectra validator design.
This is a useful infrastructure story because staking is now core financial plumbing for Ethereum. Improvements to validator design, operator accountability and network efficiency matter not only to DeFi users, but also to institutions assessing Ethereum as settlement and collateral infrastructure.
Read more: CoinDesk
Fanatics buys regulated exchange assets for prediction markets
Fanatics agreed to buy assets from BGC Group as it looks to build a regulated prediction market exchange. CoinDesk and Reuters both reported on the move, which adds another major consumer brand to the growing event-based trading market.
Prediction markets sit at a strange but important intersection of finance, gambling, sports, politics, crypto and information markets. The more mainstream they become, the more pressure there will be on regulators to clarify where prediction markets end and gambling begins.
Read more: CoinDesk and Reuters
Swiss crypto bank AMINA explores public listing
CoinDesk reported that Swiss crypto bank AMINA is working with Cantor as it explores a potential public listing. The report framed the move as part of a broader wave of crypto companies returning to public markets.
This shows that digital asset businesses are still trying to professionalise, access larger capital pools and position themselves as mainstream financial services firms. The strongest crypto companies are no longer just trying to survive regulatory pressure. They are looking to become listed financial infrastructure businesses.
Read more: CoinDesk
New research releases high-frequency Polymarket and Binance dataset
A new arXiv paper released OpenMarket, a synchronised Polymarket-Binance dataset for high-frequency prediction-market research. The paper includes hundreds of millions of rows and explores how Polymarket Bitcoin markets relate to Binance BTC/USDT order flow.
This is a useful research item because prediction markets are becoming a serious data and market-structure topic. As these markets grow, researchers will need better datasets to test whether they actually aggregate information, how fast they react and where pricing inefficiencies appear.
Read more: arXiv
Closing insights
This week’s strongest theme is that trust is becoming the control layer for both AI and blockchain.
For AI, the focus is no longer just model capability. It is disclosure, labelling, incident response, agent security, model pricing and the real economics of work. The EU’s AI Act transparency rules make this clear: governance is moving from policy documents into product interfaces.
For blockchain, the same story is playing out through patents, regulated entities, tokenised receivables, staking upgrades and prediction market infrastructure. Digital assets are being pulled into the world of mainstream finance, but that also means stronger expectations around resilience, compliance and accountability.
The big picture is simple.
AI agents need safe operating environments. Tokenised assets need trusted settlement and compliance. Prediction markets need clear boundaries. Stablecoins need institutional-grade infrastructure.
The next phase of the digital economy will be less about who can launch the most exciting demo and more about who can build systems that governments, institutions and everyday users are prepared to trust.
ABOUT AUSTRALIAN BLOCKCHAIN & AI NETWORK
The Australian Blockchain & AI Network (ABAI Network) is a non-profit community organisation dedicated to increasing education and awareness of blockchain technology, specifically blockchain and AI-based projects. Their goal is to empower the Australian community with the knowledge and tools to participate in the digital economy, and to promote the adoption and growth of emerging technology in Australia and beyond.
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