1046 posts · Page 60 of 88. ← Blog
A `Session` is the conversation; `state` is the key-value bag agents and tools read and write — and the prefix on a key decides how long it lives.
A Session holds a conversation; state is a scoped key-value store (session/user/app/temp) read and written by tools, injected into instructions via {state} templating, and persisted by SessionService.
How to broadcast one input to several executors in parallel and join their answers with a barrier — the core workflow graph primitives, with no LLM in the way.
A start executor broadcasts a question to two experts via a fan-out edge; a fan-in barrier edge joins both answers before the aggregator yields output.
Agents as graph nodes: switch-case routing, fan-out/fan-in, and mixing plain functions with agent steps in one workflow.
Agents are just workflow executors: switch-case routing, fan-out/fan-in concurrency, and mixing plain function nodes with agent nodes in one graph.
An objection feels like a rejection — the customer pushing back, resisting, saying no. The mental shift that transforms selling is realizing an objection is usually the opposite: a sign of engagement, a real concern surfaced, an invitation to address the thing standing between them and yes. Handled with the pushy-sales playbook (overcome it, pressure through it), objections end deals. Handled with genuine understanding, they're how deals get closed — by resolving the real concerns that were always going to decide the outcome.
An objection feels like a rejection — the customer pushing back. The mental shift that transforms selling is realizing it's usually the opposite: a sign of engagement, a real concern surfaced, an invitation to address the thing standing between them and yes. Handled with genuine understanding, objections are how deals get closed.
How Python decides what runs next — conditionals and the ternary, for-each iteration done idiomatically, while loops, break/continue and the surprising loop-else, structural pattern matching with match/case, and where truthiness and comprehensions fit in.
How Python decides what runs next — conditionals and the ternary, for-each iteration done idiomatically, while loops, break/continue and the surprising loop-else, structural pattern matching with...
How Go treats functions as ordinary values — and what that buys you: the (result, error) idiom, variadic APIs, closures over shared state, and the decorator/middleware/option patterns that fall out of passing functions around.
How Go treats functions as ordinary values — and what that buys you: the (result, error) idiom, variadic APIs, closures over shared state, and the decorator/middleware/option patterns that fall out of...
How Visa Account Updater and Mastercard Automatic Billing Updater keep stored credentials alive when cards get reissued, expire, or change numbers.
How VAU/ABU keep stored credentials current, credential-on-file mandates, and reducing involuntary churn from expired/reissued cards.
Four protocols, four jobs: how tools, agent-to-agent messaging, and payment rails compose into one buying flow.
How the layers compose: MCP gives an agent tools and context; A2A lets agents talk to each other; AP2/ACP/x402 are the payment rails those agents call when money must move.
How to build PSD2-grade open-banking APIs — strong customer authentication and its exemptions, the consent grant and its revocation, and the hard boundary between account-information and payment-initiation scopes.
Teaches how to build open-banking APIs: strong customer authentication and exemptions, consent grant/lifecycle, account-information vs payment-initiation scopes, and TPP authorization with token/consent revocation.
How to turn a book of exposures into risk-weighted assets and a capital ratio with a deterministic, auditable pipeline
Teaches the engineering of a risk-weighted-asset calculator: exposure classification, risk-weight lookup (standardized approach), credit-conversion factors for off-balance items, and capital-ratio aggregation for regulatory reporting.
Building low-latency sliding-window counters, entity-keyed aggregates, and an online feature store that stays consistent with its batch-computed twin.
Teaches how to build low-latency velocity checks: sliding-window counters and aggregates in an online feature store, entity keys (card/device/IP), and consistency between real-time and batch-computed features.
How a plain function becomes a callable tool, how ToolContext reaches session state, and how long-running tools pause a run for a human.
Tools give agents capabilities: a plain function becomes a tool with its signature as the schema, plus ToolContext, built-in tools, and long-running/human-in-the-loop tools across Python and Go.