1290 posts · Page 81 of 108. ← Blog
When software holds the card and clicks "buy," the old questions — was this the cardholder, did they mean to, who pays if not — all get harder to answer.
The new fraud surface: prompt injection turning a shopping agent into an attacker's buyer, hijacked delegated credentials (Visa saw ~450% more dark-web 'AI Agent' chatter in H1 2026), and disputes when an agent acted on…
Model days-past-due transitions, SMA/NPA classification, provisioning triggers, and cure logic as one deterministic engine driven by time and repayment events.
Teaches how to model delinquency as a state machine: days-past-due bucket transitions, SMA/NPA classification rules, provisioning triggers, and cure/roll-forward/roll-back logic driven by repayment events.
How to assemble features from bureau, bank, and alt data, serve a scorecard or model, apply policy cutoffs, and emit adverse-action reason codes with a full audit trail.
Teaches how to build a decisioning engine: feature assembly from bureau/bank/alt data, scorecard vs ML model serving, policy rules and cutoffs, and adverse-action reason-code generation with an audit trail.
How to ingest watchlists, match names across scripts and spellings, and turn a fuzzy score into an auditable clear, alert, or block.
Teaches how to build sanctions/watchlist screening: list ingestion (OFAC/UN/EU), transliteration and fuzzy name matching, scoring thresholds, whitelisting, and rescreening on list deltas to control false positives.
When you want fixed control flow, don't ask the model — wire it yourself.
Sequential, Parallel, and Loop agents compose sub-agents in fixed patterns — deterministic orchestration where you, not the model, decide control flow, with state flowing between steps.
How to snapshot a running workflow at every super-step, then throw the instance away and rebuild a fresh workflow that resumes from a saved checkpoint.
A cyclic guess-the-number workflow snapshots state each super-step, then a brand-new workflow instance is rehydrated from a checkpoint via ResumeStreaming.
Wrapping an agent run with async seams that log, time, guard, and short-circuit — without touching the agent's logic.
Wrapping an Microsoft Agent Framework agent run in Python with async middleware seams — timing, logging, and a guardrail that short-circuits a tool call before it runs.
Classifying a whole image as "cat" is only the beginning of computer vision. Real applications need to know where the cat is, how many objects there are, and sometimes exactly which pixels belong to each one. Object detection and segmentation answer those harder questions, and they power self-driving cars, medical imaging, and photo editing. This post covers the main vision tasks beyond classification and how they build on the CNN foundation.
Real vision needs more than 'what is this?' — the task hierarchy runs classification → detection (bounding boxes) → semantic segmentation (per-pixel) → instance segmentation. How one-stage (YOLO) vs two-stage detectors and encoder-decoders (U-Net) build on the CNN backbone, powering self-driving and medical imaging.
The instinct of every enthusiastic builder in a sales conversation is to talk — to explain the product, demo the features, make the case. It's almost always the wrong move. The best salespeople do the opposite: they ask, and they listen. Discovery (understanding the customer's actual problem) and qualification (determining whether they're even a real fit) are the unglamorous early stages where good selling is truly won or lost — and where an engineer's diagnostic instincts, properly aimed, are a genuine advantage.
The instinct of every enthusiastic builder in a sales conversation is to talk. It's almost always the wrong move. The best salespeople ask and listen. Discovery (understanding the customer's actual problem) and qualification (whether they're even a real fit) are where good selling is truly won — and where an engineer's diagnostic instincts are an advantage.
The single mental model that explains most of Python's surprises — everything is an object with an identity, a type, and a value; a name is a reference bound to an object, not a box that holds one; and assignment binds, it never copies.
The single mental model that explains most of Python's surprises — everything is an object with an identity, a type, and a value; a name is a reference bound to an object, not a box that holds one; and...
How Go's type system actually behaves — predeclared types, the zero-value guarantee that removes a whole class of null bugs, the "no implicit conversions" rule and why it exists, and the difference between a named type and a mere alias.
How Go's type system actually behaves — predeclared types, the zero-value guarantee that removes a whole class of null bugs, the "no implicit conversions" rule and why it exists, and the difference between...
How a chip card proves it is genuine on every single transaction — and why a cloned magstripe never could.
How the chip generates an ARQC, the issuer validates it and returns an ARPC, plus offline data authentication (SDA/DDA/CDA) and terminal risk management.