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NFTs and Digital Art in 2026
NFTApr 10, 2026

NFTs and Digital Art in 2026: From Hype to Utility and Long-Term Collecting

NFTs and Digital Art have shifted from 2021 hype to a utility-focused market in 2026, with stronger provenance, curated galleries, and rising collector adoption.

Michael Willson
Tips to Save Bitcoin Transaction Fees
InfographicsApr 10, 2026

Tips to Save Bitcoin Transaction Fees

Learn practical tips to reduce Bitcoin transaction fees and optimize your crypto transfers. Discover smart strategies like choosing the right timing, using SegWit wallets, and adjusting fee rates to save money on every transaction.

Michael Willson
15 Practical Hacks to Cut Claude Token Usage Without Losing Answer Quality
Claude AiApr 9, 2026

15 Practical Hacks to Cut Claude Token Usage Without Losing Answer Quality

Learn 15 practical hacks to cut Claude token usage without losing quality, including context hygiene, tool-output filtering, MCP audits, and model routing.

Michael Willson
System Prompt Slimming for Claude: What to Remove, What to Keep, and Why It Saves Tokens
Claude AiApr 9, 2026

System Prompt Slimming for Claude: What to Remove, What to Keep, and Why It Saves Tokens

Learn how system prompt slimming for Claude cuts token waste by trimming CLAUDE.md, compacting history, batching prompts, and ignoring irrelevant files.

Michael Willson
Few-Shot vs. Zero-Shot in Claude: Token Cost Tradeoffs and Best Practices
Claude AiApr 9, 2026

Few-Shot vs. Zero-Shot in Claude: Token Cost Tradeoffs and Best Practices

Learn few-shot vs. zero-shot in Claude, how token costs scale with examples, where accuracy plateaus, and best practices like adaptive exemplar selection.

Michael Willson
Claude Output Control: How to Cap Length, Reduce Verbosity, and Minimize Tokens
Claude AiApr 9, 2026

Claude Output Control: How to Cap Length, Reduce Verbosity, and Minimize Tokens

Learn Claude output control techniques to cap length with max_tokens, reduce verbosity using system prompts, and minimize tokens with structured JSON outputs and strict tool use.

Michael Willson
RAG for Claude on a Budget: Retrieval Strategies That Reduce Context Tokens
Claude AiApr 9, 2026

RAG for Claude on a Budget: Retrieval Strategies That Reduce Context Tokens

Learn budget-friendly RAG for Claude: semantic chunking, hybrid retrieval, reranking, compression, and local search to cut context tokens by 60-80% without losing quality.

Michael Willson
Token-Efficient Prompt Templates for Claude: Reusable Formats for Common Workflows
Claude AiApr 9, 2026

Token-Efficient Prompt Templates for Claude: Reusable Formats for Common Workflows

Learn how to build token-efficient prompt templates for Claude with reusable formats for coding, debugging, and feature delivery that reduce context bloat and improve output consistency.

Suyash Raizada
On-Chain vs Off-Chain AI: Architecture Patterns for Scalable Blockchain + AI Systems
BlockchainApr 9, 2026

On-Chain vs Off-Chain AI: Architecture Patterns for Scalable Blockchain + AI Systems

Learn on-chain vs off-chain AI trade-offs and hybrid architecture patterns for scalable blockchain + AI systems, including rollups, AVS inference, and provenance design.

Suyash Raizada
Verifiable AI Inference: Using Blockchain to Prove Model Outputs and Prevent Tampering
BlockchainApr 9, 2026

Verifiable AI Inference: Using Blockchain to Prove Model Outputs and Prevent Tampering

Verifiable AI inference uses blockchain, ZK proofs, and staking to prove model outputs, prevent tampering, and create audit-ready AI logs for Web3 and enterprises.

Suyash Raizada
Sentiment Analysis for Crypto Markets: Using NLP on News, Twitter, and On-Chain Signals
CryptocurrencyApr 9, 2026

Sentiment Analysis for Crypto Markets: Using NLP on News, Twitter, and On-Chain Signals

Learn how sentiment analysis for crypto markets uses NLP on news, Twitter, and on-chain signals to track fear, FUD, and narrative shifts in 2026.

Suyash Raizada
Adversarial Examples in Computer Vision: How Attacks Work and How to Build Robust Models
BlockchainApr 9, 2026

Adversarial Examples in Computer Vision: How Attacks Work and How to Build Robust Models

Learn how adversarial examples in computer vision fool models, from FGSM and PGD to physical patches and LVLM attacks, plus practical defenses for robust training.

Blockchain Council

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