1046 posts · Page 61 of 88. ← Blog
How to pause a workflow to ask a human, checkpoint every super-step, then rewind the whole graph to a saved checkpoint and replay.
A RequestPort pauses to ask a human for a guess while every super-step is checkpointed, then RestoreCheckpoint rewinds the whole graph including tries state.
The graph model underneath every multi-agent app: executors as nodes, edges as data flow, and typed events streaming out as it runs.
The Microsoft Agent Framework workflow model in Python: executors as nodes, edges as data flow, switch-case routing, and typed streaming events - learned model-free.
The demo is where technical sales succeeds or fails — and where the most common, most fixable mistake happens. Given a chance to show the product, the enthusiastic builder gives the full tour: every feature, every capability, in order. The customer, who came with one specific problem, sees a wall of things that don't obviously address it, and disengages. A great demo does the opposite: it shows how the product solves this customer's problem, and almost nothing else. Getting demos and proofs of concept right is one of the highest-leverage skills in technical selling.
The demo is where technical sales succeeds or fails — and where the most common, fixable mistake happens: the enthusiastic builder gives the full feature tour, and the customer, who came with one problem, disengages. A great demo shows how the product solves *this customer's* problem, and almost nothing else. Demos and POCs are among the highest-leverage skills in technical selling.
Why Python draws a hard line between text and raw bytes, how the encode/decode boundary works, and the string-handling habits that keep that line from cutting you.
Why Python draws a hard line between text and raw bytes, how the encode/decode boundary works, and the string-handling habits that keep that line from cutting you.
Go's control flow is deliberately small — one loop keyword, a switch that doesn't fall through, an `if` that can scope its own variable — and then there's `defer`, the one construct that repays close reading. A tour of the whole surface, with the sharp edges labelled.
Go's control flow is deliberately small — one loop keyword, a switch that doesn't fall through, an `if` that can scope its own variable — and then there's `defer`, the one construct that repays close...
Why "authorize then capture" is a lie, and how to model a hold that grows, shrinks, expires, and reconciles against a moving available balance.
Pre-auth vs estimated vs incremental authorization (hotels, fuel, delivery), partial approvals, and reconciling holds against final capture.
The surface a store must expose when the buyer is an AI agent, not a browser — and why it is the fintech reliability playbook wearing a new hat.
What a store must expose to sell to agents: a machine-readable product feed/catalog, agentic checkout endpoints, acceptance of delegated payment tokens, idempotency keys for retried agent calls, webhooks for async status…
Typology rules, sliding-window aggregation, alert scoring, and case management that feeds STR/SAR filing — treated as a streaming systems problem, not a compliance checkbox.
Teaches how to build AML transaction monitoring: typology rules (structuring, rapid movement, layering), sliding-window aggregation, alert scoring and deduplication, and case management feeding STR/SAR filing.
How to exchange originator and beneficiary data between crypto services before a transfer settles: counterparty discovery, IVMS101 payloads, and pre-transfer verification that gates the on-chain send.
Teaches how to implement the FATF Travel Rule between VASPs: originator/beneficiary PII exchange protocols (IVMS101, TRP/OpenVASP), counterparty VASP discovery, and pre-transfer verification before on-chain send.
Model corporate ownership as a graph, propagate percentages through the chains, handle the cycles that break naive traversal, and surface every natural person who controls more than 25 percent — with the evidence path attached.
Teaches how to compute ultimate beneficial ownership: modeling ownership as a graph, percentage-through-chain calculation, control vs ownership thresholds, and cycle handling to surface >25% beneficial owners.
How one agent routes work to specialists — and why the description field is the most important string you write.
Agent hierarchies and LLM-driven delegation: sub_agents, how the description field drives auto-transfer, and coordinator/dispatcher patterns — contrasted with deterministic workflow agents.
How to snapshot a workflow after every super-step, then rewind the same live run to an earlier checkpoint and replay from it.
Same guess-the-number graph, but RestoreCheckpoint rewinds the live run to the 6th snapshot and replays forward — no fresh workflow instance needed.