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1290 posts · Page 70 of 108. ← Blog
Go treats errors as ordinary values, not exceptions — which means everything you know about passing, comparing, and inspecting values applies. This is a working guide to sentinel errors, wrapping with %w, and the two verbs that make error chains navigable: errors.Is and errors.As.
Go treats errors as ordinary values, not exceptions — which means everything you know about passing, comparing, and inspecting values applies. This is a working guide to sentinel errors, wrapping with %w,...
How a custodian proves it holds what it owes, what the cryptography actually guarantees, and where the guarantee stops.
How a custodian proves it holds customer assets: Merkle tree of liabilities, on-chain reserve attestation, and the limits of PoR.
Modeling limit/market/stop and GTC/IOC/FOK semantics as a lifecycle instead of a pile of flags.
Model order-type and time-in-force semantics (limit/market/stop; GTC/IOC/FOK) as a lifecycle.
Handle a live market-data feed the way an engineer must: sequence checking, gap recovery, and snapshot-plus-delta order-book reconstruction.
Handle a market-data feed: sequence checking, gap recovery, and snapshot-plus-delta order-book reconstruction.
Enforce pre-trade risk limits and keep real-time positions and mark-to-market P&L without stalling the order path.
Enforce pre-trade risk limits and keep real-time positions and mark-to-market P&L.
How OpenTelemetry traces, structured logs, and token metrics turn an agent's event stream into something you can debug in production.
Seeing inside a running agent: OpenTelemetry tracing with spans for agent, model, and tool steps, structured logging, and exporting traces to debug latency and tool-call trajectories.
The one idea that makes everything else in LangGraph click: nodes don't pass messages, they update a shared state — and reducers decide how.
State is a typed dict of channels; each channel has an optional reducer. No reducer overwrites; a reducer (like add_messages or operator.add) combines. This is the single idea the rest of LangGraph is built on.
How a whole workflow binds as a single executor inside a larger workflow, so pipelines compose two levels deep.
inproc.BindSubworkflowAsExecutor binds a whole workflow as one node; an order pipeline nests Payment and FraudCheck two levels deep, and inner events still bubble up.
A guardrail that blocks a run before the model, chained ahead of a logger — and the upstream nil-update panic I fixed along the way.
A guardrail middleware that blocks an Microsoft Agent Framework Go run before the model, chained ahead of a logger — plus the tool-approval nil-update panic I fixed upstream in PR #472.
Machine learning models increasingly make decisions that affect people's lives — who gets a loan, a diagnosis, a job interview — and many of them are black boxes that can't explain why. Interpretability is the field dedicated to opening those boxes: understanding why a model made a prediction, in terms a human can grasp. As AI gets more powerful and more deployed, being able to explain it stops being a nicety and becomes a requirement. This series builds interpretability from first principles.
The most accurate models are often the least interpretable — black boxes that can't explain why. Why 'accurate but unexplainable' isn't enough (trust, debugging models that are right for the wrong reasons, fairness, accountability, regulation), and the questions interpretability actually asks (global vs local, model-specific vs agnostic).
The funnel has a hidden flaw as a mental model: it's a leaky bucket you must keep refilling from the top, forever. Growth marketing's key insight is to look for loops instead — mechanisms where the output of using the product feeds back into acquiring more users, so growth compounds rather than requiring ever-more input. Combined with an experimental, data-driven mindset that engineers take to naturally, this is how modern products grow systematically rather than by pouring money into the top of a funnel.
The funnel has a hidden flaw: it's a leaky bucket you must keep refilling from the top forever. Growth marketing's key insight is to look for loops instead — mechanisms where using the product feeds back into acquiring more users, so growth compounds. Combined with an experimental mindset engineers take to naturally, it's how modern products grow.
How type parameters and constraints actually work in Go 1.18+ — writing functions and data structures that are type-safe across many types, when the compiler can infer type arguments for you, and the harder question of when a plain interface is still the better tool.
How type parameters and constraints actually work in Go 1.18+ — writing functions and data structures that are type-safe across many types, when the compiler can infer type arguments for you, and the harder...