Panagiotis Ganelis

Software Engineer | Blockchain | Basketball

[Panagiotis Ganelis @pan__gan]

@tekbog However to use it i would somehow like an audit/security guarantee.
Looks nice idea and architecture but I have trust issues recently 😅

[Panagiotis Ganelis @pan__gan]

@tekbog Old school star done, well deserved

[Rand @randhindi]

https://t.co/0sfSvzspcx

[Panagiotis Ganelis @pan__gan]

The end is so close 💥

[Aikido Security @AikidoSecurity]

Update 5:05 PT: The attack has now expanded well beyond @TanStack and @Mistral.

373 malicious package-version entries across 169 npm package names, including @uipath, @squawk, @tallyui, @beproduct, and more.

The malware propagates by stealing your CI credentials and using them to publish new compromised versions.

Full IOCs, affected package list, and detection steps: https://t.co/jWG9DUCu3x

[Ethereum Community Foundation @ethcforg]

https://t.co/oO2t8IfvYd

[Rand @randhindi]

Zama is now supported natively by the @OpenZeppelin relayer, making it easy for developer to start building confidential applications. Making confidentiality the new default onchain will require great tools and integrations across the ecosystem. This is our primary goal for 2026.

https://t.co/bBshnEnXDZ

[Rand @randhindi]

Since the beginning of the year, there has been one crypto kidnapping every 5 days in France.

This time they abducted a 10 year old kid and his mother.

French police forces are thankfully incredible, the problem is that everything else is dysfunctional so this wont stop anytime soon.

And yet, the government is now asking anyone with more than 5k in crypto to declare their wallets. Same government that had people in it SELL this data to criminals!

Encrypt your wallets

[OpenZeppelin @OpenZeppelin]

Our FHE library continues to evolve 🔐

v0.4 of OpenZeppelin x @zama Confidential Contracts is here.

This version ships BatcherConfidential: private, aggregate routing between confidential tokens and non-confidential swaps.

[Patrick Collins @PatrickAlphaC]

This changes the game when it comes to attack surface if true.

Meeting people in person used to be incredibly risky for hackers to do, but now it’s being used as a tool.

There are prevention steps one could have taken for each misstep, but the issue is now looking systemic.

[Panagiotis Ganelis @pan__gan]

👀

[Justin Drake @drakefjustin]

Today is a monumentous day for quantum computing and cryptography. Two breakthrough papers just landed (links in next tweet). Both papers improve Shor's algorithm, infamous for cracking RSA and elliptic curve cryptography. The two results compound, optimising separate layers of the quantum stack. The results are shocking. I expect a narrative shift and a further R&D boost toward post-quantum cryptography.

The first paper is by Google Quantum AI. They tackle the (logical) Shor algorithm, tailoring it to crack Bitcoin and Ethereum signatures. The algorithm runs on ~1K logical qubits for the 256-bit elliptic curve secp256k1. Due to the low circuit depth, a fast superconducting computer would recover private keys in minutes. I'm grateful to have joined as a late paper co-author, in large part for the chance to interact with experts and the alpha gleaned from internal discussions.

The second paper is by a stealthy startup called Oratomic, with ex-Google and prominent Caltech faculty. Their starting point is Google's improvements to the logical quantum circuit. They then apply improvements at the physical layer, with tricks specific to neutral atom quantum computers. The result estimates that 26,000 atomic qubits are sufficient to break 256-bit elliptic curve signatures. This would be roughly a 40x improvement in physical qubit count over previous state-of-the-art. On the flip side, a single Shor run would take ~10 days due to the relatively slow speed of neutral atoms.

Below are my key takeaways. As a disclaimer, I am not a quantum expert. Time is needed for the results to be properly vetted. Based on my interactions with the team, I have faith the Google Quantum AI results are conservative. The Oratomic paper is much harder for me to assess, especially because of the use of more exotic qLDPC codes. I will take it with a grain of salt until the dust settles.

→ q-day: My confidence in q-day by 2032 has shot up significantly. IMO there's at least a 10% chance that by 2032 a quantum computer recovers a secp256k1 ECDSA private key from an exposed public key. While a cryptographically-relevant quantum computer (CRQC) before 2030 still feels unlikely, now is undoubtedly the time to start preparing.
→ censorship: The Google paper uses a zero-knowledge (ZK) proof to demonstrate the algorithm's existence without leaking actual optimisations. From now on, assume state-of-the-art algorithms will be censored. There may be self-censorship for moral or commercial reasons, or because of government pressure. A blackout in academic publications would be a tell-tale sign.
→ cracking time: A superconducting quantum computer, the type Google is building, could crack keys in minutes. This is because the optimised quantum circuit is just 100M Toffoli gates, which is surprisingly shallow. (Toffoli gates are hard because they require production of so-called "magic states".) Toffoli gates would consume ~10 microseconds on a superconducting platform, totalling ~1,000 sec of Shor runtime.
→ latency optimisations: Two latency optimisations bring key cracking time to single-digit minutes. The first parallelises computation across quantum devices. The second involves feeding the pubkey to the quantum computer mid-flight, after a generic setup phase.
→ fast- and slow-clock: At first approximation there are two families of quantum computers. The fast-clock flavour, which includes superconducting and photonic architectures, runs at roughly 100 kHz. The slow-clock flavour, which includes trapped ion and neutral atom architectures, runs roughly 1,000x slower (~100 Hz, or ~1 week to crack a single key).
→ qubit count: The size-optimised variant of the algorithm runs on 1,200 logical qubits. On a superconducting computer with surface code error correction that's roughly 500K physical qubits, a 400:1 physical-to-logical ratio. The surface code is conservative, assuming only four-way nearest-neighbour grid connectivity. It was demonstrated last year by Google on a real quantum computer.
→ future gains: Low-hanging fruit is still being picked, with at least one of the Google optimisations resulting from a surprisingly simple observation. Interestingly, AI was not (yet!) tasked to find optimisations. This was also the first time authors such as Craig Gidney attacked elliptic curves (as opposed to RSA). Shor logical qubit count could plausibly go under 1K soonish.
→ error correction: The physical-to-logical ratio for superconducting computers could go under 100:1. For superconducting computers that would be mean ~100K physical qubits for a CRQC, two orders of magnitude away from state of the art. Neutral atoms quantum computers are amenable to error correcting codes other than the surface code. While much slower to run, they can bring down the physical to logical qubit ratio closer to 10:1.
→ Bitcoin PoW: Commercially-viable Bitcoin PoW via Grover's algorithm is not happening any time soon. We're talking decades, possibly centuries away. This observation should help focus the discussion on ECDSA and Schnorr. (Side note: as unofficial Bitcoin security researcher, I still believe Bitcoin PoW is cooked due to the dwindling security budget.)
→ team quality: The folks at Google Quantum AI are the real deal. Craig Gidney (@CraigGidney) is arguably the world's top quantum circuit optimisooor. Just last year he squeezed 10x out of Shor for RSA, bringing the physical qubit count down from 10M to 1M. Special thanks to the Google team for patiently answering all my newb questions with detailed, fact-based answers. I was expecting some hype, but found none.

[Zama @zama]

BREAKING

Zama becomes the native confidentiality layer for T-REX Ledger, the RWA infrastructure backed by Apex Group (servicing $3.5T in assets) and targeting $100B in tokenized assets by June 2027.

[Zama @zama]

$ZAMA is going live. Years in the making. Today is another foundational step toward Zama becoming the HTTPS layer for blockchain.

[Suraj Sharma @suraj_sharma14]

If I Had to Start Web3 Again in 2026, I’d Do This

Not more tutorials.
Not more chains.
Not more tools.

I’d optimize for leverage + signal + compounding from Day 1.

Here’s the exact path 👇

1.) I’d start by reading how systems fail (not how they work)
Most builders learn happy paths.
Real learning comes from failures.

What I’d use instead:
- Protocol post-mortems
- Incident analyses
- Design write-ups after things broke

Hidden gems:
1. Paradigm research write-ups → https://t.co/1Rj7vRUHUv

2. Flashbots research → https://t.co/C4ah1cjS9g

3. L2Beat risk analyses → https://t.co/n0UMNqLTM7

Why this matters:
You start thinking in assumptions, incentives and edge cases early.

That mindset compounds.

2.) I’d pick ONE narrow problem, not an ecosystem
Instead of:
“I’m learning Ethereum / Solana / zk / AI”

I’d pick:
- Indexing pain
- Wallet UX
- Governance tooling
- Developer experience gaps
- Then live there for months.

Underused places to spot problems:
- GitHub issues of infra projects
- Forum threads in protocol governance
- Open RFCs that never shipped

This is where real project ideas come from.

3.) I’d read protocol code for architecture not syntax
You don’t need to understand every line.

You need to understand:
- What’s modular
- What’s intentionally hard-coded
- Where flexibility was sacrificed

Repos I’d read slowly:
1. Uniswap v4 hooks → https://t.co/8yUN9RiimX

2. Compound governance contracts → https://t.co/zNhXKVgFir

3. ERC-4337 reference implementation → https://t.co/AnVDbKg3eN

Why this matters:
You learn design trade-offs not just Solidity.

4.) I’d build “boring” infra before flashy apps
Infra teaches you:
- Constraints
- Performance limits
- Real user behavior

Examples of underrated starter builds:
- A small custom indexer (even if subgraphs exist)
- A transaction simulator
- A governance proposal analyzer
- A gas + execution cost explorer

Most devs skip this.
That’s why it’s valuable.

5.) I’d learn to explain systems in plain English
If you can’t explain:
- Why something exists
- What problem it solves
- What trade-offs it makes
- You don’t understand it yet.

What helped me most:
- Writing short public notes
- Diagrams instead of code snippets
- Explaining failures not wins

Builders who write clearly get:
- Faster feedback
- Better collaborators
- More trust

6.) I’d join ecosystems before applying to anything
Not applications first.
Presence first.

What that actually means:
- Commenting on proposals
- Reviewing docs PRs
- Sharing small experiments
- Helping others debug

Most fellowships, residencies and grants favor:
“I’ve seen this person around”

Over:
“Great resume, zero context”

7.) I’d measure progress by signal not hype
Bad metrics:
- Number of tools learned
- Chains touched
- Tweets posted

Good metrics:
- One repo people actually use
- One write-up people reference
- One problem people DM you about

That’s how careers compound quietly.

>> The biggest mindset shift

Web3 rewards:
- Patience over speed
- Depth over breadth
- Systems over syntax

If I were starting again,
I’d stop trying to look “early” & start trying to look useful.

Save this. Come back to it later.

[Panagiotis Ganelis @pan__gan]

🚀 Just released Cursor Token Saver — a VS Code extension that helps you send smarter, token-efficient context to Cursor AI!
•Compress code
•Use git diffs only
•Live token estimates

💻 Open-source & ready to try: https://t.co/o9TxqLeeqq

#VSCode #CursorAI #OpenSource

[Panagiotis Ganelis @pan__gan]

@gakonst @tempo No replies on applications unfortunately

[terminally onλine εngineer @tekbog]

*man with no idea how to build software nor experience in building software nor experience in maintaining software*
wow building software is so easy

[Panagiotis Ganelis @pan__gan]

@SumitM_X First release a version with deprecation warning. Then remove functionality with an error in next major release.

[Panagiotis Ganelis @pan__gan]

@SumitM_X Do you really need microservices?😅

[terminally onλine εngineer @tekbog]

Microsoft after hearing people were running self hosted github runners for free

[Artem Chystiakov @Arvolear]

What problem do L2s solve now?