Archive
24 articles published in this period.
EIP-4844 blobs look like cheap on-chain storage, but they vanish in 18 days. Here is why DA windows break AI training pipelines and what to use instead.
To borrow $100 in DeFi, you lock $125–167 in collateral. That gap is the price of trustlessness — and AI agents pay it the same as anyone. On-chain credit scoring is emerging to close it, but the signals that work for humans fail for agents that can spin up new addresses in milliseconds.
Any permissionless network that rewards the best gradient contribution faces a Nash equilibrium where every rational miner copies instead of computes — same reward, zero cost. Gauntlet's commit-reveal mechanism closes that trap, and already trained a 1.2B LLM on Bittensor with real token payouts.
Every ECDSA signature broadcasts the wallet's public key. A March 2026 Google/EF paper tightens the quantum break estimate to ~500k physical qubits — here's what that means for autonomous AI agent wallets.
On-chain AI agents face a circular oracle problem: you need inference to decide if inference is worth calling. Here's what the token cost distribution actually looks like — and how to build around it.
ZKLoRA lets a LoRA seller prove adapter compatibility with your base model without exposing the weights. The verifier checks in 1–2 s — but the prover bears 31–74 s per module, and the protocol is interactive, which puts trustless on-chain settlement just out of reach.
MORPH shows that a TPU v6e8 pod runs NTT at 40× CPU — 10× faster than an H100. The same silicon that accelerates AI inference now accelerates ZK proof generation, and the math that explains it is the same in both cases.
A new paper quantifies what everyone suspected: AI agent tokens trade at >10,000x the capital they actively manage. Here's the mechanics of why, and what it means for builders.
A flash loan gives an AI agent $1M with no collateral — and demands it back plus 0.05% before the block ends. The atomic callback constraint is both what makes flash loans safe and what forces an agent to solve its entire strategy before touching the chain.
Cross-chain bridges have lost $2.5B to hacks because receiving contracts accept messages they cannot cryptographically verify. AI agents operating across chains inherit this exact problem. Here are the four trust models, their real security parameters, and a principled agent policy.
Five builders now win 96.7% of Ethereum blocks. Their edge isn't compute — it's exclusive orderflow: 12% of transactions that generate 54.59% of block value. AI agents transacting in public have to understand where they sit in that hierarchy — and when a preconfirmation changes the math.
Probabilistic classifiers miss 30–40 % of policy violations. Lean 4 theorem provers and SMT solvers make certain guardrail tiers mathematically certain — here's how the four-layer policy stack works.