Deep chand Sharma retweetledi
Deep chand Sharma
2.9K posts

Deep chand Sharma
@Deepcha28012035
I am self employed and social worker
Delhi, OH Katılım Ağustos 2020
851 Takip Edilen78 Takipçiler
Deep chand Sharma retweetledi
Deep chand Sharma retweetledi

In a Layer-1, it's easy to mistake patchwork for innovation.
After a decade of building, iterating, failing, rebuilding, I’ll tell you this: The alchemy lies in engineering that engine… To build an integration so seamless, it just feels inevitable.
But be deliberate.
I’ve been in the trenches rewriting how an Layer-1 should work. There’s a difference between making something work and building something that evolves and endures.
And trust me, that difference shows when you must scale.
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Deep chand Sharma retweetledi

We glorify “succinct proofs” while dodging the real issue:
Generating them is heavier than the computation itself. At TAN, we confront its overhead by compressing proofs, and scaling provers without burning holes in hardware.
Verification is cheap, but making proofs practical is hard.
We’ve bled in that trench so you don’t have to.
zk at TAN is hardened, efficient, and ready for scale.

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Deep chand Sharma retweetledi
Deep chand Sharma retweetledi

MetaMars is carving its name into the red dust by building a metaverse economy where play, ownership, and community aren’t bolted on! They’re baked in:
✓ Governance token ($MARS) integrated into staking
✓ NFTs that exist as functional primitives
✓ GameFi loops designed to reward engagement
And if a metaverse is going to thrive, it needs an infra that rewards ongoing activity, not one-off launches. That’s where TAN’s BPoS consensus mechanism aligns perfectly.
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Deep chand Sharma retweetledi

The metaverse has already passed its honeymoon phase.
Billions poured in. Visions of digital cities. Land rushes that looked more like speculation than settlement. And then? Silence. Because execution rarely matched expectation.
Our partnership with @MetaMars_Global hits different.
1/3

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Deep chand Sharma retweetledi

AGIX is building a multi-agent, heterarchical framework, a system where AI agents collaborate to complete complex, multi-step workflows across apps, browsers, and APIs.
In other words, Text-to-Action.
You don’t click buttons, you delegate tasks.
AI becomes an executor.
They’ve proven it with deployments across TON, Metis, Magic Store, and hundreds of enterprises, with 200k+ users, and backing from Amazon, Microsoft, and Intel.
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Deep chand Sharma retweetledi

When chains say “zk,” what they mean is outsourcing trust. Rollups produce proofs but the base chain remains blind. It only verifies outcomes that are bridged back.
That’s useful, but it’s not sovereignty.
We integrated zkEVM at the Layer-1. This means zero-knowledge proofs are not an optional service layered on top, they are natively embedded into consensus.
In practice:
→ Consensus is reinforced by cryptographic proofs
→ Execution is verifiable by anyone
→ Finality is cryptographic, not probabilistic
This is not a “feature release.” It’s a fundamental redesign.
By integrating zkEVM directly at Layer-1, TAN creates an environment where trust assumptions shrink and security is elevated from economic guarantees to certainty.
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Deep chand Sharma retweetledi
Deep chand Sharma retweetledi

🎰 LET’S TALK ODDS 🎰
☺️ Your odds of winning 10 TON from us just by dropping “Ambassador” in the comments = 6.25%
🎰 Your odds of winning the equivalent $30 in Mega Millions Lottery = 0.0069%
That means BabyDoge PAWS giveaways are literally 900 TIMES more winnable than the lottery.
900 TIMES!!
This wasn’t the last such giveaway 🐾🔥

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Deep chand Sharma retweetledi
Deep chand Sharma retweetledi

Someone came by asking about the economic logic behind TAN’s consensus, and instead of diving straight into BPoS mechanics, we simply asked them:
“How would you build a rewards system from scratch?"
What followed was a collaborative jam session:
→ Ideas around dynamic validator caps
→ Mechanisms to discourage validator cartel behavior
→ Concepts for real-time penalty calibration
At one point, a neighboring booth rep leaned over with a grin and joked, “You guys aren’t doing a product pitch: you’re running a full-on DAO workshop over here.”
They weren’t wrong.

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Deep chand Sharma retweetledi

Simplicity at what cost? Good systems aren’t simple.
We’ve seen too many “simple” systems buckle under adversarial pressure. The early DeFi builders also believed in simplicity until governance forced their hands.
Good systems make complexity survivable.
What we call complexity is often a response to complexity in the world itself. Robust designs aren’t the cleanest. It’s the one that anticipates how incentives mutate over time.

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Deep chand Sharma retweetledi

Think about all successful projects: Ethereum, Uniswap…
What did they have in common?
→ Great storytelling
→ Shared vision
→ Clear roles
That’s “coordination design” in action.
You can build a token. But if your contributors don’t “feel” aligned, they won’t stick around. That culture is built by “designing rituals, feedback loops, and shared identity.”
As a founder building in Web3, ask yourself:
→ Am I designing my project for humans?
→ How easy is it for people to align and grow with us?
→ How do we stay on the same page?
Code can run smart contracts.
But humans run DAOs, communities, and token networks.
Because in Web3, “the hardest problems are social”.

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Inflation isn’t evil. But it’s lazy when left unchecked.
Most chains print until the market just stops caring. They subsidize early adopters, overpay validators, and call it “bootstrapping.” Then they quietly let supply outrun utility.
But the thing about time?
It notices everything.
L1s crumble just because they lacked restraint.
Monetary policy is governance in disguise. And without a hard stance, you’re not building a protocol. TAN didn’t chase short-term yield. It asked the harder question.
The answer is baked into TAN’s design:
→ Block-per-reward emissions tied to real usage
→ Inflation Protection Model that resists decay
→ Validators who earn by contributing
Because in the long run, the real flex is sustainability.
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