1290 posts · Page 76 of 108. ← Blog
Why an array is a value and a slice is a view — the three-word header, how `append` really grows, the aliasing trap that silently corrupts data, and the small habits (three-index slices, `copy`, pre-sizing) that keep it from biting you.
Why an array is a value and a slice is a view — the three-word header, how `append` really grows, the aliasing trap that silently corrupts data, and the small habits (three-index slices, `copy`, pre-sizing)...
How R2P flips the pull model into a request-and-approve flow, and the engineering behind mandates, consent, and reconciliation.
How Request to Pay (R2P) messaging works, the standing-mandate lifecycle, consent, and variable recurring payment authorization.
How to coordinate a multi-step payment as an orchestrated saga: compensating actions for partial failures, idempotent steps, and a guarantee that money is never left stranded.
Teaches how to coordinate a multi-step payment across services without distributed transactions: orchestrated saga steps, compensating actions for partial failures, and guaranteeing money is never stranded.
How to safely credit on-chain deposits and finalize settlement: confirmation-depth thresholds, mempool tracking, chain-reorg detection with balance rollback, and idempotent handling of replaced transactions.
Teaches how to safely credit crypto deposits and finalize settlement: confirmation-depth thresholds, mempool/pending tracking, chain-reorg detection and balance rollback, and idempotent handling of replaced transactions.
How to engineer a fiat-backed stablecoin: mint-on-deposit and burn-on-redeem flows tied to a reserve ledger, a 1:1 reserve invariant, and continuous reconciliation between on-chain supply and off-chain custody balances.
Teaches how to engineer a fiat-backed stablecoin: mint-on-deposit / burn-on-redeem flows tied to a reserve ledger, 1:1 reserve invariant checks, and reconciliation between on-chain supply and off-chain custody balances.
Session state is for small text and JSON. When your agent produces a PNG, a PDF, or a WAV, it belongs in the artifact store — binary-native, versioned, and out of the session record.
Artifacts are binary/file data agents produce or consume: ArtifactService saves and versions named artifacts, loaded and saved via context, keeping large blobs out of session state.
How a graph workflow forks: a predicate on each edge decides whether a message may pass, turning the graph into an if/else expressed as data flow.
The first 03-workflows lesson: AddDirectEdge attaches a func(any) bool to each edge so a spam-detection graph forks into send vs. handle-spam branches, offline.
Durable workflows in Python: checkpoint and resume, pause for a human with request_info, and package a workflow as an agent.
Durable Microsoft Agent Framework workflows in Python: checkpoint and resume every superstep, suspend on request_info for a human decision, and package a workflow as an agent.
Almost every time series, however complicated it looks, is a combination of a few simple components: a long-term trend, repeating seasonal cycles, and irregular noise. Decomposition is the act of pulling them apart — and it's the single most clarifying thing you can do with a time series, because once you see the components, both understanding and forecasting become far easier. This post is about the anatomy of a time series.
Almost every series is trend + seasonality + noise (or their product). Decomposition pulls them apart — the single most clarifying thing you can do — revealing what you're predicting, how predictable it is (signal-to-noise), how to transform it, and which method fits. The foundation under every forecasting method.
The most valuable thing sales produces isn't revenue — it's understanding. Every sales conversation is a direct line to what customers actually want, struggle with, and will pay for, and a company that treats sales as merely a revenue function while ignoring that understanding is throwing away its best source of truth. This closing post zooms out: how sales connects to product and the whole business, why the sales-product feedback loop matters, what founder-led selling teaches, and how the series' honest, understanding-based view of sales fits into building something real.
The most valuable thing sales produces isn't revenue — it's understanding. Every sales conversation is a direct line to what customers actually want, and a company that ignores that is throwing away its best source of truth. How sales connects to product, the whole business, and founder-led selling.
How Python decides what a name means — the LEGB lookup rule, what a closure actually captures, the late-binding loop trap and its fixes, and when you genuinely need `nonlocal` or `global`.
How Python decides what a name means — the LEGB lookup rule, what a closure actually captures, the late-binding loop trap and its fixes, and when you genuinely need `nonlocal` or `global`.
What a Go string actually is under the hood — an immutable read-only slice of bytes, not a sequence of characters — and how bytes, runes, and code points relate, so you stop shipping the classic multibyte bugs.
What a Go string actually is under the hood — an immutable read-only slice of bytes, not a sequence of characters — and how bytes, runes, and code points relate, so you stop shipping the classic multibyte bugs.