62 docs tagged with "Engineering"

Diagrams | Matrices | Thinkers

What happens to your AI coding setup when you switch agents?

When does a single prompt stop being enough — and how do you chain prompts without hiding behind a framework?

How do independent AI agents coordinate on the same codebase without vendor lock-in?

What changes when your product thinks?

The contract between specification and implementation — what the dream team writes, what engineering reads, how specs become passing tests

Diagrams | Matrices | Thinkers

The complexity of smart contracts can significantly impact performance, with larger dApps showing higher coupling between objects (CBO) and more complex contract structures. A comparison table of key metrics for building onchain applications includes:

Retrieval Augmented Generation.

Is our E2E testing sound — or are we bleeding silently?

What makes an AI agent productive — the model, or the context you give it?

Testing

How does Claude Code connect judgment to computation?

Run parallel Claude Code sessions with Git worktrees

Engineering disciplines that make bad code harder to write than good code — from pre-coding clarity through tested contracts.

What do you lose when your agent can't import shared context?

The infinite intern that never sleeps, but often hallucinates. Your job is to be the Architect; the AI is the Builder.

How do you ship features where the value proposition is validated before the first line of code?

How do you spec a product that never gives the same answer twice?

Cryptography plays the critical role in providing the foundations of trust in systems that are neutral and resistant to censorship or bribes.

The Easiest Way to Use Cursor to build apps.

What does the data engineering work chart look like?

ETL vs ELT.

How do you reach those who need what you offer?

What's silently degrading the codebase — and how do you find it before it compounds?

How do you know the codebase is healthy — not from reading the code, but from measuring it?

This standard provides basic functionality to transfer tokens, as well as allow tokens to be approved so they can be spent by another on-chain third party.

Standard building blocks for EVM compatible blockchains.

The Ethereum Virtual Machine (EVM) functions as a world computer that powers decentralized applications (dApps) running on the Ethereum blockchain.

How do you cut through bullshit to validate the truth, and apply force where it creates the greatest step improvement?

Diagrams | Matrices | Thinkers

What does a million-token context window make possible that 200k doesn't?

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LLM Engineering

What separates a factory that improves every cycle from one that manages chaos?

Utimately The Market decides, is the upside worth the effort?

What resources and minerals are in greatest demand to build the future?

Why abstract forms? Because browser defaults sabotage validation.

Blockchain interaction patterns for web developers — hooks, wallets, state management

A picture is worth 1,000 words, and much more when you understand what the symbols stand for.

Platform is the perceive that builds capital - the accumulated assets that power your moves

What does it take to keep a platform running — and how do you make it better every cycle?

Great products deliver great outcomes.

Three generations of pipe — information, value, intent. Coordination infrastructure for digital and physical agents.

The blockchain scalability trilemma refers to the challenge of achieving all three of the following properties simultaneously in a decentralized blockchain network:

Make things work then do it better, faster, cheaper with less effort to master.

The purpose of software is to help people to coodinate in meaningful endeavour. All things start as thought — an intention, a pattern, a class. Software is the discipline that turns thought into thing. Every thing creates a collision surface — the question is whether those collisions compound into meaningful endeavor or extract from it.

How does software go from someone's pain to proven value?

How do you know the engineering is getting better — not just busier?

Diagrams | Matrices | Thinkers

Clear and consistent focus on hardware integration to maximize performance.

From atoms to bits and back again, standards capture the best of what flows into a state that endures cycles. Each standard is a decision that passed selection and persisted — so the next generation starts higher. The building blocks of evolution are standards that stuck.

What does it feel like to onboard as a developer — and how does that compare to EVM and Solana?

How does Sui's object-centric architecture enable experiences that are practically impossible on other L1s?

How do you make the right testing decision structurally impossible to skip?

Where do your tests run — and what does that cost?

What is the cheapest test that gives sufficient confidence?

What is the cheapest test that proves your change works?

What happens when you scale complexity before you standardize interfaces?

Protocol for Commissioning PRD Expectation vs Results

Did you deliver what you said you would?

The open protocol and network for secure web3 messaging.