Sunken Submarine
Joined September 2018
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Happy New Week! ๐
A fresh week is a new opportunity to learn, build and grow.
Start small. Stay consistent. Keep moving forward.
What are you working toward this week?
#HappyNewWeek #0xVerseAcademy #LearnBuildGrow
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๐: @Meta and @stripe are partnering to make it easy for businesses to accept agentic payments using the @Muse Connector Platform.
Learn more:
โข muse.ai/platform
โข docs.stripe.com/agentic-commโฆ
โข Email jweinstein@ / @jeff_weinstein
Opening access for developers to build Muse connectors. You bring the API -- Muse brings the agent, the browser, and the context of what the person actually wants. People reach your service just by asking for it, and their agent takes it from there.
New connectors are live today. Come build with us. muse.ai/platform
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Build an AI product people can actually use.
Weโre partnering with @GoogleAfrica to launch the Paystack AI Builder Challenge, a two-week hackathon. Bring your own idea or solve a real problem submitted by a Paystack business.
Apply by Sept 24: paystack.com/hackathon
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One positive consequence of all the recent detailed thinking about transaction formats - not just 8141, also "future of state" discussions eg. UTXOs, PBT, keyed nonces, and also recursive STARK mempool - is that we have a much more explicit understanding of how transactions have "actions" and "dependencies", and we can engineer around optimizing the two separately.
An action is an effect that a transaction has.
A dependency is a fact about the transaction and/or the state that must be true for the transaction to be valid.
eg. a signature is a dependency, a Merkle proof of a UTXO is a dependency, a ZK-SNARK (or STARK) is a dependency, a call that sends ETH is an action
Dependencies can be processed in parallel. Dependencies that involve state can be reasoned about by a mempool, especially if the specific state accessed is statically declared. Dependencies that are pure (no state calling allowed) can be processed once at the mempool layer and never need to be processed again - and potentially even replaced with a STARK verifying them, allowing not just execution but also data to be elided.
In principle, dependencies and actions can all be expressed as calls (if needed, calls to precompiles). This would make the transaction format itself very bare-bones and minimalist (a list of calls, flags for the type of each call eg. dependencies would be static or pure calls, and origin, nonce, etc) and allows maximum cross-compatibility even if different EVM chains have different features.
In 2015-era Ethereum, thinking explicitly about these differences was not very important: execution was execution, there were few enough transactions that we could process them all serially, and single-key ECDSA accounts were good enough for everyone.
Ethereum's current scaling strategy, however, requires moving beyond that paradigm. Ethereum is beloved by many developers because the execution and state model is so dynamic and flexible. But dynamic and flexible is not friendly to scaling. Fortunately, >90% of Ethereum's activity by volume does not require anything dynamic and flexible. So, we require contracts, accounts and transactions to more explicitly specify what is dynamic and flexible and what is more statically-analyzable but more restrictive, and more statically-analyzable things get the lowest gas cost and thus scale the most. Effectively, learning from the best of both the 2015-era Ethereum model and a more Bitcoin-like model (reminder: Bitcoin has had what I call account abstraction since the beginning), and making a mixture of both (really, the full spectrum between both) available, with gas costs appropriate for the level of scale involved.
New state types, the recursive STARK mempool, keyed nonces, etc all go in this direction.
This all relates to transaction types, because a general-purpose transaction type is a very natural interface layer on top of which all of this can be implemented, and the current thinking around the EIP-8141 transaction type is going in this exact direction that is friendly to these kinds of future generalizations.
So in that sense, 8141 done well is not just a culmination of 10 years of account abstraction work, it's also preparation for the next few years of responsible decentralization-friendly hyper-scaling.
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Six weeks.
โ AI.
โ UI/UX.
โ HTML.
โ CSS.
โ JavaScript.
โ AI-assisted coding.
โ Vibe coding.
โ Replit.
โ Bolt.
AI-powered product creation.
Today, our Summer Tech Bootcamp comes to a close.
But we weren't trying to teach students a list of tools.
We wanted to show them what becomes possible when creativity, technology and AI come together.
Idea โ Design โ Code โ Product.
That's the mindset we're building at 0xVerse.
People who don't just use technology.
People who build with it.
Six weeks down.
A lifetime of building ahead. ๐
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Applications are open for the Claude Campus Ambassadors program. This year, weโre expanding opportunities to more students, with three tracks for undergrads, graduate students, and PhDs/postdocs.
Apply here: anthropic.com/campus
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brother do you know how insane it would be if we have buy buttons native on @X for tickers? and then they added revenue-sharing on trading volume the same way they have ad-revenue sharing? hello?
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As a developer, you should know core system design concepts.
This helps show potential employers that you can turn design requirements into production-ready code.
This course covers app architecture, API design, caching, networking, databases, and more.
freecodecamp.org/news/learn-โฆ
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Every great founder learns to suffer.
The rejections. The flat metrics. The 3 AM ceiling stares wondering if youโre delusional.
Embrace it. High pain tolerance is one of the few advantages competitors canโt copy.
Donโt seek ease. Seek strength.
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Claude Code on desktop now works with the iOS simulator.
Build and run your iOS app, and the simulator opens in a panel right next to your conversation. Available today in public beta.
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AI coding agents can build software quickly.
But they can also say:
โDone.โ
โDeployed.โ
โEverything is working.โ
โฆwhile the database is still disconnected, an endpoint is failing, or the contract was never properly deployed.
I kept running into this while building with AI agents.
So for the Spark hackathon, I built ShipReceipt.
ShipReceipt checks the actual project:
โ public GitHub repository
โ selected commit
โ live deployment
โ health and readiness endpoints
โ deployed Monad contract
It then records exactly what passed and what failed.
No AI decides the result.
No fake green success screen.
No hiding failed checks.
One of the live receipts passed 4 out of 5 checks because the readiness endpoint returned a real HTTP 404.
ShipReceipt marked it Partial and preserved the failure in the evidence.
The detailed evidence stays offchain, while its integrity, result, issuer, and timestamp are recorded on Monad thus making later changes detectable.
This can help developers verify AI-generated work, clients inspect software before accepting delivery, and hackathon judges review working submissions more confidently.
AI can claim it shipped.
ShipReceipt proves what actually worked.
ShipReceipt is now live on the Build Anything showcase.
Check out the project, test the live receipts, and please upvote it if you believe software completion should come with verifiable evidence:
buildanything.so/showcase/shโฆ
Live app:
shipreceipt.vercel.app
Partial receipt:
shipreceipt.vercel.app/receiโฆ
Built on Monad Testnet.
#Monad #BuildOnMonad #SparkHackathon #BuildInPublic #AIAgents
I use AI coding agents almost every day.
They help me move faster, but Iโve noticed a recurring problem:
The agent says the work is complete, but I still have to manually verify everything.
Did the deployment actually work?
Is the database connected?
Does the health endpoint return 200?
Is the contract really deployed?
Did the transaction confirm?
That experience led me to build ShipReceipt for the Spark hackathon.
ShipReceipt verifies a live software build, binds the result to a specific GitHub commit, creates a tamper-evident evidence record, and anchors the receipt on Monad.
It does not reward confident claims.
It checks the actual system.
So when a build is only partly working, ShipReceipt says Partial instead of presenting a fake green success screen.
I believe this becomes increasingly useful as more software is built by coordinating AI agents.
We are producing code faster.
Now we also need better ways to prove what was actually shipped.
AI can claim it shipped. ShipReceipt proves it.
#Monad #BuildOnMonad #SparkHackathon #BuildInPublic #AIAgents #SoftwareEngineering
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Ethereum is for shipping.
Here are some of the things the Ethereum ecosystem launched, upgraded, and announced over the past month.
0/ @RobinhoodApp launched Robinhood Chain (@RobinhoodCrypto) on mainnet, an Ethereum Layer 2 built on the @arbitrum stack, enabling 24/7 trading of tokenized stocks and ETFs for users in over 120 countries through Robinhood Wallet. The network surpassed $1B in DEX volume in just over a week.
1/ @aztecnetwork achieved Stage 2 rollup decentralization under @l2beat's framework, removing governance control over its core protocol and taking another step toward trust-minimized infrastructure.
2/ @VitalikButerin shared updates to Ethereum's evolving technical roadmap, outlining the next phase of Lean Ethereum and the protocol's long-term direction.
3/ @ethlabs_org launched as a non-profit R&D lab for Ethereum and ETH. Their mission is to make Ethereum the settlement layer of the global economy.
4/ @ethereuminsti launched as an independent non-profit dedicated to accelerating the institutional adoption of Ethereum, its L2s, applications and overall ecosystem.
5/ @aave introduced Stable Vaults, fixed-rate stablecoin yield vaults designed for seamless integration into consumer applications.
6/ @zama launched the First DeFi Yield Venue for Confidential USDC (cUSDC) in partnership with @Morpho and @SteakhouseFi, bringing private stablecoin lending to Ethereum.
7/ @swissknifexyz launched a new Privacy Protocol Tracker, making it easier to compare fees, wait times, supported chains, and other metrics across Ethereum privacy protocols.
8/ Global tickets for @EFDevcon 8 went live, alongside speaker applications for this yearโs conference in Mumbai, India.
9/ @Optimism and @toss__official signed an agreement to explore bringing the Korean Won onchain, expanding blockchain-based financial infrastructure for one of South Korea's largest fintech platforms.
10/ @OctantApp completed Epoch 12, its first full quadratic funding round using a zero-knowledge vote coprocessor and new voting application, distributing 88.1 WETH to Ethereum public goods projects.
11/ @0xprivacypools launched the trusted setup ceremony for Privacy Pools V2 ahead of its next protocol deployment.
12/ Gwei Name Service launched an ownerless, immutable Ethereum naming system built without administrative ownership.
13/ @ammalgam launched on Ethereum mainnet, introducing oracle-free lending without impermanent loss.
14/ @lodestar_eth added support for Fast Confirmations, allowing Ethereum node operators to confirm transactions in a single slot using validator attestations.
15/ @PrivacyBoost introduced preconfirmations for private transfers, allowing transfers to be treated as usable in around one second before final settlement.
16/ The @ethereumfndn published Ethereum Basics for Governments and Institutions, a new primer introducing Ethereum as a credibly neutral digital public utility for policymakers and enterprise leaders.
17/ @OndoFinance launched @OndoPerps, enabling tokenized stocks to be used as collateral for perpetual futures across equities, commodities, and indices.
18/ @base introduced Base Privacy, giving enterprises infrastructure to trade, pay, and settle onchain with built-in confidentiality and compliance features.
19/ @BGDA_UK launched BAGEY, a natively tokenized UK regulated fund on Ethereum where the blockchain serves as the legal register of record.
20/ @sparkfinance launched the Stablecoin FX Layer on @Uniswap v4, introducing shared liquidity infrastructure that lets stablecoins access a common liquidity layer.
21/ @Trueo_ launched user-created prediction markets, allowing anyone to create a market by asking a question and letting participants trade on the outcome through a fully onchain prediction market.
22/ @kpk_io integrated @OpenCover Covered Vaults, allowing depositors to add opt-in onchain insurance to curated vaults, with coverage underwritten by @NexusMutual.
23/ @PropellerSwap launched Turbine on Ethereum mainnet, enabling large trades to settle with lower slippage by sourcing liquidity across onchain, offchain, and peer-to-peer markets.
24/ Hosted by @web3privacy, the Neocypherpunk Summit brought together around 1,000 builders and researchers in Berlin to advance privacy, open-source infrastructure, and human rights.
25/ @eth_systems launched as a company building modular privacy infrastructure for institutional Ethereum.
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Discover Our AI Career Tracks
Artificial Intelligence is transforming every industry, and now is the best time to get started.
๐น AI Automation โ Automate workflows, business processes, and repetitive tasks using AI.
๐น AI Vibe Coding โ Build websites, apps, and AI-powered solutions faster with modern AI development tools.
๐น AI Engineering โ Learn to design, build, and deploy intelligent AI systems for real-world applications.
Whichever track you choose, you'll gain practical, hands-on experience by building real projects.
Our new cohort starts on August 3rd, and registration is still ongoing.
Register now: 0xverse.academy/register
The future belongs to those who know how to build with AI.
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Youโre probably spending this Saturday scrolling through another video of someone building something impressive with AI.
An app.
An automated business.
A useful tool that started as a simple idea.
And somewhere in your mind, youโre thinking:
โI would love to build something like this, but I donโt know where to start.โ
You donโt have to figure it out alone.
If youโre around Ago Palace Way, Festac, Amuwo-Odofin, Isolo, Okota or nearby, you can learn physically with us at 0xVerse Academy.
Choose the path that matches what you want to build:
AI Automation โ automate repetitive tasks and business processes
AI Vibe Coding โ turn your ideas into websites and apps
AI Engineering โ build smarter products powered by AI
No endless tutorials.
No learning without building.
Youโll learn hands-on, work on real projects, and get the guidance you need to actually create something useful.
๐ Ago Palace Way, Lagos
๐
Classes begin August 3rd
๐ 0xverse.academy/register
Enjoy your Saturday.
But donโt let that idea in your head remain just an idea.
Come and build it with us.
#LagosTech #LagosTechOwambe #TechNigeria #ArtificialIntelligence
ALT Purple 0xVerse Academy flyer featuring three young learners using laptops and tablets. Text reads: โOne Academy. Three AI Paths. Endless Possibilities.โ The three learning paths shown are AI Automation, AI Vibe Coding, and AI Engineering. Classes begin August 3rd.
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I talk to engineers at other companies every day and hear the same thing: one person is 10x'ing their output with Claude but the rest of the org hasn't caught up.
Watching teams adopt AI, I keep seeing the same 4 steps.
I mapped them out here: Steps of AI Adoption claude.ai/code/artifact/bfdfโฆ
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AI automations are really cool until you start building enough of them and realise...
Wait.
This is still engineering ๐
A trigger starts the workflow.
Data moves between systems.
Conditions decide where it goes.
Something fails.
You retry.
You log it.
You handle the edge case nobody mentioned.
Then somewhere in the middle, an LLM reads the context and makes a decision.
The AI is new.
A lot of the problems around it aren't.
If anything, adding a model introduces a new problem: unpredictability.
Traditional code usually does what you told it to do.
AI might interpret what you told it to do.
And that small difference suddenly makes retries, evals, guardrails, observability and human intervention much more important.
The deeper I get into AI automation, the less it feels like dragging nodes together.
It feels like we're applying familiar engineering principles to systems that can now reason through parts of the workflow.
Very cool shift to watch in real time.
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Your first AI app does not need 20 features.
Pick one problem.
Build a simple interface.
Connect an AI model through an API.
Problem โ Interface โ AI.
Thatโs the foundation.
Build something small enough to finish and useful enough for someone to actually use.
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No camera. No studio. No need to show your face.
You can build a useful YouTube channel by combining research, storytelling, consistency, and AI tools.
Here is the workflow:
Step 1: Choose a valuable niche
Do not choose a topic simply because it is popular.
Look for a niche where people actively search for answers and businesses are willing to advertise.
Examples include:
โ Finance.
โ Technology.
โ Software and coding.
โ AI tools.
โ Business education.
The goal is to find the intersection between demand, your interests, and content you can produce consistently.
Step 2: Use AI to develop the script
Start with a clear topic and proper research.
Then use ChatGPT or another AI tool to help you:
โ Structure the video
โ Develop the explanation
โ Improve the hook
โ Simplify difficult ideas
โ Create a stronger ending
Do not publish the first draft blindly. Verify the facts and rewrite the script until it sounds natural.
Step 3: Produce the video
Use tools such as ElevenLabs for narration and Canva or Leonardo AI for supporting visuals.
Create one reliable video format:
โ Hook.
โ Explanation.
โ Examples.
โ Key takeaway.
โ Call to action.
Once the format works, reuse the structure without making every video feel identical.
Step 4: Publish consistently and study the results
Post on a realistic schedule you can maintain.
โ Watch your:
โ Click-through rate.
โ Audience retention.
โ Watch time.
โ Comments.
โ Subscriber growth.
Then improve the next video based on what viewers actually respond to.
AI can make production faster.
But research, originality, useful storytelling, and consistency are what build the channel.
You are not creating passive income overnight.
You are building a library of valuable content that can continue attracting viewers long after each video is published.
Learn how to use AI for practical content systems at 0xVerse Academy.
0xverse.academy
#FacelessYouTube #AIContentCreation #YouTubeGrowth #DigitalSkills #0xVerseAcademy
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Most people think vibe coding looks like this:
Prompt โ Get code โ Ship.
In reality, thatโs how you end up with buggy, unmaintainable software.
A better way to think about vibe coding is this 5-step workflow:
1. Think ๐ง
Start with the problem, not the code.
Who is this for?
What problem are you solving?
What outcome should the user get?
2. Design ๐๏ธ
Map the system before you build it.
Think about:
โข User flows
โข Pages
โข Database
โข APIs
โข Authentication
โข Integrations
AI works best when it has a clear blueprint.
3. Build ๐ค
Now let AI help you write the code.
Break the project into small tasks instead of asking it to build everything at once.
Treat AI like a junior developerโnot a magician.
4. Verify โ
Review everything.
Test the logic.
Check for bugs.
Handle edge cases.
Think about security and performance.
AI accelerates development.
It doesnโt replace engineering judgment.
5. Scale ๐
Once it works, ask:
Can this be automated?
Can n8n orchestrate the workflow?
Can APIs connect the services?
Can deployments, notifications, and reports run automatically?
The goal isnโt just to build software.
The goal is to build systems that continue creating value.
Think like a founder.
Design like an architect.
Build with AI.
Verify like an engineer.
Scale like an operator.
Thatโs modern software development.
