Shiven👨🏾‍💻(d/acc)

pure cypherpunk 👾 hacking @veilnyx_hq | blockchains | ZK | smart-contracts | decentralisation | trustless systems | software engineering |

[Shiven👨🏾‍💻(d/acc) @0xShiven]

Today I’m excited to open-source the Guardian Smart Wallet Contract kit 👮🏻‍♂️!
It is a roll-up to @thirdweb's smart wallet contracts, offering a secure and invisible wallet experience for your users through smart wallets, social account recovery, and locking features!💥
Links👇🏾

[Arpit Bhayani @arpit_bhayani]

One of the easiest ways to tell whether the context you gave your agent is actually good enough is to look at the "apology" metric.

If your AI agent keeps saying things like "sorry" or "you're absolutely right," that is an indication that the context can be improved.

When an agent apologizes repeatedly on the same task, the problem is usually not the model - it is the context. Again, I said usually. Very likely, the problem would be solved by passing a better context rather than switching to a more expensive model.

So when you are deploying agents, instrument them - i.e., capture the responses and build a simple apology counter :) alongside your usual correctness metrics.

Some keywords and phrases to watch for are "sorry," "my mistake," or "you're absolutely right."

Depending on your use case, the root cause could be unclear documentation, an ambiguous API description, instructions that do not cover an edge case, or even a retrieval that is not bringing in the right context. These are all things that can be improved once you know where to look.

In a gist, track apologies as a metric and use them to debug your agent. It is simple, but it works.

Hope this helps.

[Bitinning @bitinning]

🇮🇳 India saw an average of 25 government school closures per day over the past 10 years.

lost about 94,000 government schools between 2014-15 and 2024-25.

Government schools: 11.07L -> 10.13L (10 years).
Government schools fell by 8.5% in a decade.

- NITI Aayog

[Veilnyx @veilnyx_hq]

A privacy layer that takes custody of your funds isn't privacy; it's a bank with extra steps.
The version worth caring about never touches your keys. Your assets stay in your control the whole time; what changes is who can see your activity, not who holds it.

Shielded, not surrendered.

[Palliora @palliora]

You've been paying for AI with data you'll never get back.

Every model you use was trained on someone's information, often yours, handed to a company that promised to be careful and gave you nothing in return. The whole knowledge economy runs on that quiet trade: your data for their product. Trust us with the rest.

Palliora is built to break that trade.
The idea is simple to say and hard to do: let people share data for computation without giving up control of it. Your data stays encrypted. A network of independent nodes runs the workload on it for training, inference, and analysis, without ever seeing the raw inputs. The result is provable on-chain, so you don't have to take anyone's word that it was done right. You set who gets access, for what, and for how long. When your data is used, you get rewarded automatically.

No black box. No "trust us".
Just a confidential computation you can verify.
It's written by cryptographers, lives on testnet now, and is open for anyone who wants to run a node or build on it.

See how it works: https://t.co/akpwlMbv1n

[Veilnyx @veilnyx_hq]

Every public blockchain has the same quiet flaw: your entire financial life is readable by anyone with your address. Salary, savings, who you pay, what you hold, all of it, forever.

"Just add KYC" makes it worse.

Now there's a database linking that open ledger to your real name, sitting somewhere waiting to be breached.
Zero-knowledge proofs take a different route: prove a transaction is valid without exposing the sender, receiver, or amount, and reveal identity only when a lawful request clears an independent approval threshold.

Private by default. Accountable when it counts.
Testnet: https://t.co/31vSy5WdG8

[Ethlabs @ethlabs_org]

Announcing Ethlabs: a non-profit R&D lab for Ethereum and ETH

Our mission is to make Ethereum the settlement layer of the global economy.

The internet became global because shared protocols created a common language between networks. Private systems remained useful, but bounded. Finance is approaching a similar moment. As value, assets, and markets become digital, the world needs shared settlement infrastructure.

Ethereum is uniquely positioned to become that shared base layer, the neutral foundation on which users, institutions, and agents can transact without intermediation.

What we believe:

• We believe credible neutrality matters. Ten years of uptime and the lowest counterparty risk. Ground that cannot be pulled away by any one country, institution, company, or person.

• We believe ETH matters. The most valuable, programmable store of value. A decade of broad distribution, deep liquidity in onchain markets, and maximally trustless asset on Ethereum.

• We believe DeFi matters. Markets, liquidity, credit, exchange, and coordination, open to anyone.

• We believe adoption matters. Principles do not change the world until people benefit from them.

We sit between two worlds: real usage from the builders at the frontier, and the protocol that has to support it. We work with users, applications, wallets, L2s, infrastructure teams, institutions, ETH holders, core devs and researchers, then turn what they actually need into protocol work, shared standards, infrastructure, and shipped products.

Ethlabs is independent but Ethereum is a shared project. We are one node in a much larger network of stewards. This is the multi-node future.

We have spent the better part of the past decade contributing to Ethereum core research and development.

We are opinionated and transparent. We move with urgency, learn in public, and course-correct when we’re wrong.

We are building a lean, talent-dense team for people who want to do the most important work of their careers: [email protected]

[Arpit Bhayani @arpit_bhayani]

AI has made it easier to write optimized code on day 0, but it is creating a new problem...

Ask an LLM to write some code, and it will often reach for the most "correct" version - caching, batching, async, configurable strategies. Code that looks staff-level from the first commit.

If you keep probing it to optimize further, it will come up with such absurd optimizations that you may not have even heard of.

Most of these optimizations solve a problem you do not have yet. A function handling 50 records a day does not need a connection pool, a retry queue, and a pluggable backend. It needs to work and be readable.

To be honest, we engineers have always over-engineered, but AI has lowered the cost of writing the complex version to nearly zero, so the lazy default (write the simple thing first) no longer feels lazy. It feels like leaving performance on the table.

The result is codebases full of abstractions nobody asked for. Interfaces with a single implementation. Generic configs for cases that will never change. Vector operations and macros no one asked for.

The skill that matters now is not writing optimized code. It is knowing when to stop optimizing. Premature optimization used to be expensive enough that most people avoided it by default. Now it is one prompt away.

Good engineering judgement is about knowing which optimizations the problem in front of you actually needs.

Hope this helps.

[Ethereum Daily @ETH_Daily]

🔥 Tom Lee made a point about Ethereum that most people are not paying enough attention to.

The Ethereum Foundation used to hold 17% of the ETH supply.

Today, it holds only 100,000 ETH, or about 0.1% of supply.

That is a huge shift.

And according to Lee, it means the old funding model is no longer enough.

Under a traditional foundation model, he estimates the Ethereum Foundation could support only around $10 million in grants.

For a network trying to become the future of finance, that is tiny.

But this is where the story gets interesting.

BitMine, SharpLink, and other public Ethereum treasuries now own around 7% of the ETH supply.

And because that $ETH can generate staking yield, Lee says these treasuries are producing about $500 million a year in rewards.

That completely changes the game.

Ethereum no longer has to depend on one foundation to fund everything.

A wider network of public companies, treasury vehicles, staking rewards, ecosystem grants, L2 builders, and private-sector teams can now help support Ethereum’s growth.

This is why Lee believes Ethereum is entering a new phase.

Not a single foundation carrying the whole ecosystem.

But an entire capital network forming around ETH.

[L2BEAT 💗 @l2beat]

We recently launched our Privacy page, featuring support for three major privacy pools. While these protocols promise to decouple deposits from withdrawals, your activity could still be linked if you don't follow basic privacy pool hygiene.

Based on the article we published, here are 6 core practices 👇

[Sreeram Kannan @sreeramkannan]

https://t.co/2PNyFNV6Oi

[Shiven👨🏾‍💻(d/acc) @0xShiven]

@dmhardoi pls get the road fixed at Manna Purwa. As you can see, traffic is getting jammed, ppl are getting wet by the water logging. No action has been taken for YEARS now! We request your attention.

[Veilnyx @veilnyx_hq]

Privacy infrastructure only matters if people actually use it.

So far on Veilnyx testnet:

1,000+ test users
6,066 transactions
5 integrated protocols
240 wallets
5 supported chains
Private DeFi infrastructure is starting to look real.

Powered by @palliora

[Shiven👨🏾‍💻(d/acc) @0xShiven]

Bangalore: India's Silicon Valley, a city straining under pressure • FRA... https://t.co/a0BgtibpFo via @YouTube

[Veilnyx @veilnyx_hq]

The smartest DeFi users are going dark.
Not because they have something to hide, but because they have everything to protect.

Veilnyx delivers complete confidentiality for every swap, lend, yield, payment, and dApp move with selective disclosure only when you choose.

Privacy without compromises.
Compliance without friction.

Testnet live → https://t.co/31vSy5WdG8
Powered by @palliora

[Anuradha Tiwari @talk2anuradha]

My appeal to PM Modi-

In order to save petrol & diesel, please make it mandatory for bureaucrats, MLAs & MPs to use public buses and metro instead of large convoys.

It will also be a good opportunity for them to experience world-class infrastructure they are building for us.

[Patrick Collins @PatrickAlphaC]

Incredibly proud to be part of the clear signing working group, and help get clear signing to be normalized for everyone in crypto!

[Shiven👨🏾‍💻(d/acc) @0xShiven]

@BJP4UK toh kab bana rahe hai hum Kaichi dham bypass??

[Shiven👨🏾‍💻(d/acc) @0xShiven]

@JioCare @reliancejio why does your 5G suck? Switching to Airtel tomorrow!

[Shiven👨🏾‍💻(d/acc) @0xShiven]

@RonConway Sending out prayers.. get well soon 🙏

[Arpit Bhayani @arpit_bhayani]

Coding agents like Claude Code and others love Git worktrees. So, if you are using one or trying to build one, knowing about them is important, and here is what they are all about.

A Git worktree lets you check out multiple branches of the same repository at the same time, each in its own directory. Not multiple clones. So essentially, one repo, many working directories, all sharing the same Git history and objects on disk.

The problem they solve is context switching. Normally, if you are midway through work on one branch and need to jump to another, you stash, switch, do the work, switch back, and pop the stash. That context gets destroyed. With worktrees, you just open the other directory. Both branches stay live simultaneously.

For coding agents, this is a 'godsend' :) It is how they run tasks in parallel without interfering with each other. An agent can be running tests on one branch in one worktree while writing new code in another. No waiting required, and things can move in parallel.

Also, each worktree gets its own working tree and index, but they share the object store. So you are not actually duplicating gigabytes of history every time you spin one up. It is fast to create and cheap to maintain.

You create one with `git worktree add ../feature-branch feature-branch`. That is it. The directory is ready, the branch is checked out, and your original workspace is untouched.

Coding agents also get isolation guarantees. If one task crashes or corrupts its working tree, the others are unaffected. This makes Git worktrees a pretty natural fit for any system that needs to run concurrent, independent operations on the same codebase - aka coding agents :)

Hope this helps.