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Aug 20, 2026 Writing
A practical operating model for conversation: manage shared attention, lower the cost of joining and leaving, treat body language as uncertain evidence, and keep warmth from becoming manipulation.
Aug 11, 2026 Shared reading
Giles Edwards-Alexander gives refactoring an unusually concrete AI-era price tag. In a roughly 150,000-line, agent-written Rust application, a representative change initially pulled 159,564 input tokens into context.
My notes → Aug 11, 2026 Shared reading
This is a welcome reset for an argument too often conducted with demos and vibes. The authors separate code generation from software delivery, point out that developers spend only a fraction of their time typing code,...
My notes → Aug 11, 2026 Shared reading
This runnable tour makes Go 1.27 easier to evaluate than a release-note inventory. Generic methods and broader type inference get the headline, while smaller changes to allocations, goroutine diagnostics, JSON v2,...
My notes → Aug 11, 2026 Shared reading
Google's case for Go in agent-assisted development is strongest when it focuses on constraints. A strict compiler, one formatter, integrated tests and fuzzing, a substantial standard library, stable compatibility, and...
My notes → Aug 11, 2026 Shared reading
Ben Thompson examines Nvidia's attempt to turn AI factories into an investable infrastructure asset, including partnerships that reach beyond ordinary debt markets and as much as 25 percent residual-value financing from...
My notes → Aug 11, 2026 Shared reading
Nicolo argues that AI weakens one of SaaS's favorite properties: near-zero marginal cost. A conventional feature can be copied endlessly once built; an AI feature keeps consuming inference for each user and request.
My notes → Aug 11, 2026 Shared reading
Roge draws a needed line between a generated artifact and a product. AI can produce a convincing interface or feature demo in an afternoon, but a product has users, a market, and a problem important enough to solve...
My notes → Jul 29, 2026 Shared reading
This is a compact argument for returning build systems to first principles: name the inputs, name the outputs, then make the dependency graph and artifact boundaries explicit enough that the build can remain local,...
My notes → Jul 29, 2026 Shared reading
This is the ABI explainer to send to someone who knows that binary wheels are painful but has never seen the contract underneath them.
My notes → Jul 29, 2026 Shared reading
Mitchell Hashimoto gives SIMD the right entry point: recognize the common shape before reaching for cleverness. Broadcast a constant, process a vector-width chunk, reduce the result, and retain the scalar loop for the...
My notes → Jul 29, 2026 Shared reading
Jesús Espino makes Go profiling feel less like a magical command-line ritual and more like five concrete collection systems. The useful distinction is not just CPU versus heap: CPU samples arrive through a signal-driven...
My notes → Jul 29, 2026 Writing
A practical set of prompts for planning, implementation, review, PR repair, Codex Goals, scheduled triage, and skill mining without turning 'keep going until green' into an unbounded agent loop.
Jul 29, 2026 Shared reading
Alexander Belanger's guide is useful because it connects ordinary application decisions to the database behaviors they eventually expose: schemas, query shape, index ordering, connection pressure, autovacuum,...
My notes → Jul 29, 2026 Shared reading
Edward Yang offers a clarifying model for large-scale ML work: keep approachable PyTorch code as an executable reference, while specialized kernels and explicit forward-backward paths become the production...
My notes → Jul 29, 2026 Shared reading
Jovan Stojiljkovic runs the comparison that embedded-database conversations often skip: the same observability application, the same inexpensive machine, and disclosed load and read thresholds.
My notes → Jul 18, 2026 Writing
A public-source reference architecture showing where a private open model can reduce repeated API work without becoming the source of truth for acreage, identity, reconciliation, or submission.
Jul 18, 2026 Writing
A July 2026 field guide to choosing self-hosted open models by exact checkpoint, license, resident memory, usable context, workload quality, and production economics.
Jul 17, 2026 Writing
Why a $1.05 Cloud Run L4 hour can be cheaper or more expensive than hosted inference depending on utilization, throughput, fallback rate, and accepted business outcomes.
Jul 16, 2026 Writing
A production-oriented Cloud Run and vLLM design that keeps GPT-OSS private, separates routing from inference, and makes model loading, readiness, concurrency, and rollback explicit.
Jul 15, 2026 Shared reading
Alex Edwards turns the usual "use HTMX with server-rendered HTML" advice into a practical Go shape: a renderer that knows when to return a full page or a partial, embedded assets, explicit Vary: HX-Request handling, and...
My notes → Jul 15, 2026 Writing
Why adding a private open model beside hosted APIs fails unless routing, fallback, evaluation, and authority are designed as one production contract.
Jul 15, 2026 Shared reading
Serge Zaitsev builds a compact tensor library in C from the representation upward: contiguous data, shapes and strides, broadcasting, kernels, SIMD, then enough layers and manual backward passes to train small models.
My notes → Jul 12, 2026 Writing
G# is exciting not because it replaces C#, but because it puts Go, Kotlin, and Swift-flavored ergonomics on the .NET platform and reminds us that a runtime can support more than one great way to think.
Jul 10, 2026 Shared reading
Gwern's proposal is useful because it asks a sharper question than "can agents write more code?" It asks what kind of software substrate would let code, proofs, docs, tests, and design intent scale together instead of...
My notes → Jul 10, 2026 Shared reading
Steve Krouse makes the case I still buy: learning to code is less a guaranteed career coupon now and more a literacy for thinking precisely with computers. The strongest angle is educational, not nostalgic.
My notes → Jul 10, 2026 Shared reading
This is a useful designer's notebook on software quality because it pushes quality out of the narrow "does it work" box and back into the felt experience of using a product.
My notes → Jul 10, 2026 Shared reading
This is a good practical explainer because it connects the usual "add an index" advice to the physical model underneath: pages, tuples, ctid, B-tree roots and leaves, and the way PostgreSQL can avoid dragging a query...
My notes → Jul 10, 2026 Shared reading
This is a good small-project reality check because it treats solo development as both a creative advantage and an operational liability.
My notes → Jul 6, 2026 Shared reading
This is more useful than another argument about vibe coding because it is a concrete trace: notes, mockups, data modeling, scaffolding, implementation transcripts, and maintenance around Diggit, a small git-history tool...
My notes → Jul 4, 2026 Shared reading
This is a generous first-principles walkthrough of software as layered abstraction: physical switches, bits, stored programs, compilers, operating systems, networks, and finally the applications people actually touch.
My notes → Jul 4, 2026 Shared reading
Velxio is interesting because it is not just an Arduino sketch runner in a browser. It tries to put the firmware, the circuit, and the instruments in the same feedback loop: AVR, RP2040, ESP32, RISC-V, and Raspberry Pi...
My notes → Jun 30, 2026 Writing
The archive retrospective made the Games & Sim gap visible: three public proof pieces in a 96-post archive. The fix is not a better tagline; it is an artifact-first devlog cadence.
Jun 29, 2026 Writing
A retrospective on the rewrite sprint that started when a 40-post archive audit found essay and case_study labels attached to note-depth drafts.
Jun 29, 2026 Writing
Why plausible synthetic customer behavior can turn an onboarding simulation into false evidence unless every journey claim has a trace and a real-world validation gate.
Jun 29, 2026 Shared reading
This piece is worth saving because it is less about whether AI can write code and more about what happens when the job shifts from making the thing to supervising the thing.
My notes → Jun 29, 2026 Shared reading
This is a wonderful tiny-hardware project: a Swift-flavored language environment for the Apple II, implemented through a bytecode VM instead of pretending full modern Swift can fit on a 1 MHz 6502 with tens of kilobytes...
My notes → Jun 20, 2026 Writing
A project note on JovaniPink/xstate-python: loading XState and Stately JSON in Python, executing with SCXML-style semantics, binding live Python handlers, and using actors without hiding workflow state in async glue.
Jun 18, 2026 Writing
A practical 2026 map of AI agent frameworks by infrastructure primitive: orchestration, tools, state, multi-agent delegation, approvals, observability, evaluation, and deployment.
Jun 16, 2026 Writing
A decision map for when Python teams should keep asyncio, use multiprocessing, try subinterpreters, or pilot free-threaded CPython without importing new race conditions.
Jun 16, 2026 Writing
A Python architecture map for AI, data, and backend teams that need notebooks, prompts, evaluations, services, repositories, and infrastructure to stop collapsing into one folder.
Jun 15, 2026 Writing
A Python performance playbook for choosing data structures, profiling tools, vectorized libraries, JIT experiments, and concurrency changes from evidence instead of taste.
Jun 15, 2026 Writing
A production Python project skeleton that prevents import confusion, dependency drift, and toolchain sprawl before the first API route or model workflow ships.
Jun 14, 2026 Writing
A practical Python 3.13+ operating standard for teams that need typed, readable, measurable systems without mistaking every new interpreter feature for a production default.
Jun 14, 2026 Writing
How to use modern Python typing, protocols, dataclasses, and payload types to stop raw dictionaries from becoming the hidden architecture of a production system.
Jun 13, 2026 Writing
A modern Python style guide for choosing clear comprehensions, explicit None checks, pattern matching, t-strings, and domain exceptions where they improve system behavior.
May 16, 2026 Writing
A pilot plan for the claims app failure that usually arrives late: photos captured offline, model scores nobody trusts, sync queues with no proof, and evidence bundles that cannot defend chain of custody.
May 16, 2026 Writing
Why the May 2026 state-machine story is not finite automata becoming fashionable again, but durable execution becoming the reliability boundary for agents, workflow engines, and document-heavy product systems.
May 15, 2026 Writing
Why teams get stuck between tangled monoliths and premature microservices, and how to choose the next boundary with delivery metrics, ownership, and blast radius.
May 15, 2026 Writing
A de-duplicated taxonomy for system design papers: what to read first, what each paper teaches, and how to move from classic distributed systems into modern databases, observability, serverless, and AI infrastructure.
May 14, 2026 Writing
A dbt on BigQuery starter kit for the parts that usually fail after the demo: raw loads without partition filters, snapshots with weak change detection, and CI that lets expensive SQL promote.
May 8, 2026 Writing
Half the 2025 AI-governance recipes still in production cite documents that were rescinded, delayed, or replaced in the last twelve months. The current map: what got retired, what's still authoritative, and what an operating governance program actually has to cover in 2026.
May 3, 2026 Writing
Why custom LLM logging leaves you flying blind in production, and how OpenTelemetry's GenAI semantic conventions turn every model call, tool invocation, and agent step into a traceable, cost-accountable span.
May 2, 2026 Writing
Why standard code review misses capability escalation in skill manifests, and how to wire a pre-merge conftest policy gate and post-merge SLSA provenance chain that actually work — correcting three common mistakes in the recipes that circulate online.
May 2, 2026 Writing
Why a two-day debug session on a one-month-old AI-generated bug is not a debugging problem but a theory-building problem you skipped, and the operating discipline that makes the missing theory recoverable.
May 2, 2026 Shared reading
A senior data engineer's decade of candid career lessons — job mobility, technology stacks, management
dynamics, and data-engineering-specific realities — delivered in a deliberately irreverent tone.
My notes → May 2, 2026 Shared reading
A full account of building Fame Boy — a working Game Boy emulator in F# — covering CPU, PPU, and APU
implementation, optimization decisions, and what the project revealed about how computers actually work.
My notes → May 2, 2026 Shared reading
The connector shape on USB-C says nothing about what the cable can actually do, which is why the
situation is so confusing. This guide cuts through it: why manufacturers ship slower "charge cables"
alongside capable...
My notes → Apr 30, 2026 Writing
A pragmatic Python, TypeScript, Supabase, Stripe, and observability stack for shipping SaaS products with AI assistance without turning the architecture into tool soup.
Apr 30, 2026 Writing
When a SaaS product should graduate from a flexible Python-first backend into Go, gRPC, Cloud Run, and Google Cloud service boundaries.
Apr 29, 2026 Writing
How to use BigQuery primary and foreign key constraints from dbt without confusing optimizer metadata for enforced data integrity.
Apr 29, 2026 Shared reading
This is one of the cleanest public pieces on agent design because it separates workflows from agents and keeps repeating the uncomfortable production lesson: start simple, add autonomy only when the task needs it, and...
My notes → Apr 29, 2026 Writing
A critical guide to README.md, AGENTS.md, CLAUDE.md, SKILL.md, .agents, and .claude patterns for teams that want coding agents to follow repo rules without stuffing every workflow into one giant prompt.
Apr 28, 2026 Writing
Why an ADK 2.0 ToolConfirmation flow paired with VertexAiSessionService re-presented the same approval to a reviewer on Monday morning and ran the tool twice, and what the gap tells you about how to evaluate harness primitives at different maturity levels.
Apr 28, 2026 Shared reading
Chip Huyen's agent writeup is useful as a systems map rather than a hype post. It treats agents as planning, tool use, memory, feedback, and environment design, which is the level where most production mistakes actually...
My notes → Apr 28, 2026 Writing
What an oversized iOS binary, a Linux linker error, and a SQL boundary teach about embedding DuckDB as the Parquet reader for languages without a mature native library.
Apr 27, 2026 Shared reading
This is a good companion link for grounding the agent conversation in the reasoning-to-acting lineage instead of treating tool use as a brand-new product category.
My notes → Apr 27, 2026 Writing
Why a Go retry loop ran forever because the attempt counter lived on the loop instead of the state, and what the runtime guarantees of Elixir, Swift, and Zig change about which state-machine idioms are honest in each.
Apr 27, 2026 Shared reading
A genuinely useful one-page reference for USB protocol versions, connector types, and what each combination actually supports. The kind of page I keep open in a tab for a week, then forget where I bookmarked it.
My notes → Apr 26, 2026 Shared reading
This is the DSPy link I would hand to someone who keeps saying "prompt engineering" when they really mean eval-driven optimization. The example is concrete, costed, and honest about train, validation, and holdout splits.
My notes → Apr 26, 2026 Writing
How a compact Python ML cheatsheet becomes useful when synthetic demos, metrics, pipelines, and version drift are tied to the model-review decisions they can actually defend.
Apr 25, 2026 Shared reading
Part one is the practical on-ramp: a transcript-search use case, a RAG-ish starting point, and the moment DSPy becomes more than a nicer prompt template.
My notes → Apr 25, 2026 Writing
AI coding agents are turning software work into management work: engineers now have to manage intent, context, agent output, teammate coordination, stakeholder evidence, and long-term maintenance.
Apr 24, 2026 Shared reading
The thesis is deliberately provocative, which makes it useful. RAG is not simply dead, but the old chunk-embed-rerank default is under pressure from larger contexts, agentic retrieval loops, and document-native...
My notes → Apr 24, 2026 Writing
Why a precompiled-NIF fall-through on a less-common Linux target adds quiet minutes to a deploy, and what the borrowed-runtime pattern actually looks like for Elixir and Mojo.
Apr 23, 2026 Writing
Why an agent harness re-fired a half-finished tool after a worker restart, the four Python libraries that solve different parts of the problem, and a concrete contribution roadmap for xstate-python.
Apr 22, 2026 Writing
A scikit-learn NPS ordinal classifier with SMOTE, probability calibration, utility-based thresholding, and PSI drift checks. The parts that make it useful to the retention team, not just accurate on a dashboard.
Apr 22, 2026 Shared reading
This is a good reminder that eval improvements do not always come from a larger model. Sometimes the gain comes from rewriting the task boundary so the model can actually see the job.
My notes → Apr 21, 2026 Writing
An Android-first operating pattern for using GitHub Copilot, Amazon Q Developer, Android CLI, and Android skills without letting coding assistants rewrite Gradle, manifests, architecture, and security posture by accident.
Apr 21, 2026 Shared reading
This is the runtime stack link for the gpt-oss moment: kernels from the Hub, MXFP4, tensor and expert parallelism, dynamic KV cache behavior, continuous batching, and faster loading.
My notes → Apr 21, 2026 Shared reading
Loose title, useful theme. Senior engineering is less about cleverness and more about judgment, communication, taste, scope control, and knowing where complexity will hurt later.
My notes → Apr 20, 2026 Shared reading
This is a docs link rather than an essay, but it belongs in the stream because it gives a practical path for experimenting with gpt-oss reinforcement learning workflows.
My notes → Apr 20, 2026 Writing
Why a default Go parquet.Read[T] call slurped a 1.4 GB file into 11 GB of resident memory, and the column-native Rust and Go patterns that replaced it.
Apr 19, 2026 Writing
Why a hand-rolled retry double-charged a Stripe customer because the cancel state was implicit, and what XState 5's setup-plus-actors model gives you that useReducer does not.
Apr 19, 2026 Shared reading
This forum post is useful because Agent Engine networking is exactly where cloud AI demos turn into platform engineering. Connectivity, controls, private access, and service boundaries are not side quests.
My notes → Apr 18, 2026 Writing
A repo-ready operating contract for agent skills that prevents prompt bundles from drifting into unsigned, over-permissioned, unreviewed production dependencies.
Apr 18, 2026 Shared reading
This is NVIDIA's enterprise agent argument for reasoning models: model size choices, test-time scaling, open deployment, and the operational need to turn reasoning on or off.
My notes → Apr 17, 2026 Writing
Why teams using Claude, GPT-style coding agents, Cursor, and Copilot often get unstable app work when requirements, versions, conventions, tests, and handoffs are implicit.
Apr 17, 2026 Shared reading
This follow-up is useful because it keeps the agent-model conversation tied to efficiency, not only capability. Smaller or better-routed reasoning models matter when an agent system has to run repeatedly, not just...
My notes → Apr 16, 2026 Shared reading
This is worth keeping because local and Windows-side inference are no longer edge cases for product teams. Hardware choices now shape who can prototype, test, and deploy models without waiting for a cloud GPU lane.
My notes → Apr 15, 2026 Shared reading
This belongs next to any local inference or training work because cross-platform ML is usually where clean notebooks meet real machines.
My notes → Apr 15, 2026 Writing
Why a React form with seven boolean flags shipped a flicker bug that statecharts would have surfaced before the first render, and the decision rule that says when this discipline earns its place.
Apr 14, 2026 Shared reading
This is a strong local-inference link because it shows the gap between framework support and hardware-specific performance work. Apple Silicon can be serious, but the path often goes through kernels, not just...
My notes → Apr 14, 2026 Writing
A short, honest read on what AI researchers actually do day to day, written from outside the role by an applied engineer who reads papers when the work demands it.
Apr 13, 2026 Shared reading
This is reference-quality material for anyone trying to reason about accelerator performance without hand-waving. It explains GPUs as machines with memory, bandwidth, communication, and parallelism constraints.
My notes → Apr 13, 2026 Writing
Why design systems, component libraries, monorepos, and architecture boundaries become product tools when teams need to learn faster.
Apr 12, 2026 Shared reading
This is a useful bridge for software developers who can build with LLM APIs but want to understand the math vocabulary underneath attention, embeddings, optimization, and probabilities.
My notes → Apr 11, 2026 Shared reading
This is the kind of long historical synthesis that helps engineers stop treating transformers as a sudden miracle. It traces the ideas through distributed representations, language modeling, attention, transformers, and...
My notes → Apr 10, 2026 Shared reading
This is a good visual refresher for the linear algebra that shows up everywhere in ML systems: vectors, matrices, transformations, projections, and the geometry behind model representations.
My notes → Apr 9, 2026 Writing
Why roadmap churn becomes expensive when feedback, analytics, MVP evidence, and decision history are not connected.
Apr 9, 2026 Shared reading
Evan Miller's statistics pages are useful because they speak to programmers who need decision math, not notation theater. This one is especially good as a quick reference for formulas that show up in experiments and...
My notes → Apr 8, 2026 Shared reading
This is worth keeping because good code reading starts before opening the first file. Git history can show what changed, where the pressure points are, and which parts of the system have been touched recently.
My notes → Apr 8, 2026 Shared reading
This is an older link, but the basics age well: understand the question, inspect the data, be skeptical of easy patterns, and communicate the analysis so someone can use it.
My notes → Apr 7, 2026 Shared reading
This is a softer link than the GPU and agent material, but it fits the site because visual thinking changes how technical ideas become explainable.
My notes → Apr 6, 2026 Shared reading
This is a beginner resource, but it is worth keeping because feature, label, target, and ground truth confusion still causes real project mistakes.
My notes → Apr 5, 2026 Shared reading
This is a practical reference link for the part of data science that happens before the model: selecting, filtering, grouping, reshaping, and checking tabular data.
My notes → Apr 5, 2026 Writing
Why product work fails when the team chases domain complexity before the MVP has created real learning from users.
Apr 4, 2026 Shared reading
PCA is one of those concepts that gets overused and under-explained. This is a useful reference for the intuition, terminology, and tradeoffs around dimensionality reduction.
My notes → Apr 3, 2026 Shared reading
This is one of the better engineering-process essays because it grounds motivation in visible progress. Break a large project into pieces that can produce real feedback, then sprint toward demos instead of disappearing...
My notes → Apr 1, 2026 Writing
A practical reading path through software design, architecture, system design interviews, data-intensive applications, and systems analysis for engineers who want to grow beyond implementation.
Mar 31, 2026 Shared reading
This overlaps with the coding-assistant posts on the site, but it is still worth keeping as an outside practitioner account: small steps, screenshots, AGENTS.md, undo discipline, and refactoring agent-generated blobs.
My notes → Mar 29, 2026 Shared reading
This is the primary source behind the memory-optimization link in the saved list. Sakana's Neural Attention Memory Models are interesting because they try to learn what a transformer should remember or forget rather...
My notes → Mar 28, 2026 Writing
Why design thinking fails when teams treat it as a workshop template instead of a human-centered way to make better product decisions under uncertainty.
Mar 28, 2026 Shared reading
This is useful because the semantic layer keeps coming back under different names: metrics layer, business logic layer, AI query interface, governed data contract.
My notes → Mar 27, 2026 Shared reading
This is a good counterweight to traditional semantic-layer thinking because it asks whether AI-assisted query discovery changes where modeling work belongs.
My notes → Mar 26, 2026 Shared reading
This belongs in the queue because fine-tuning and inference decisions increasingly depend on numerical formats, not only model architecture.
My notes → Mar 25, 2026 Shared reading
This is a useful framing link because it shifts the work from clever prompts to the operational discipline of selecting, shaping, and evaluating context.
My notes → Mar 24, 2026 Shared reading
This is a Google-side reference for the embedding layer behind retrieval and context engineering. It is worth keeping because the site is already leaning into Vertex AI, Gemini, and production-grade AI systems, where...
My notes → Mar 24, 2026 Writing
Why generic software developer job descriptions over-index on writing code and under-specify the ownership, testing, maintenance, communication, and judgment that make software engineering work.
Mar 23, 2026 Shared reading
This visual guide is useful because embeddings become easier to reason about when they stop being abstract vectors and start feeling geometric.
My notes → Mar 22, 2026 Shared reading
This is worth keeping because reasoning models change product expectations and evaluation shape. The important question is not only whether a model can think longer, but whether the extra compute improves the user's...
My notes → Mar 21, 2026 Shared reading
This is one of the foundational agent explainers: planning, memory, tool use, reflection, and the early patterns that still show up in current products.
My notes → Mar 20, 2026 Writing
A practical MLX-first recipe for experimenting with openai/gpt-oss-20b on a 64GB Apple Silicon Mac without confusing local LoRA work for CUDA-scale training.
Mar 20, 2026 Shared reading
This is the kind of platform link that turns model serving into an operations conversation. NIM, GKE, and operators are not glamorous pieces, but they are the difference between "we can run a model" and "we can run the...
My notes → Mar 19, 2026 Shared reading
This is useful because it connects agent adoption to inference architecture. Agents do not make one call; they fan out across planning, retrieval, tool use, retries, and evaluation, which changes the serving math...
My notes → Mar 18, 2026 Shared reading
This is a durable architecture reference because it gives teams a simple way to choose the right level of diagram: context, containers, components, and code. Good diagrams reduce argument cost.
My notes → Mar 17, 2026 Shared reading
This is worth keeping because bronze, silver, and gold layers remain a common language for data platform design. Even when the exact stack changes, the idea of progressive refinement is still useful.
My notes → Mar 16, 2026 Writing
Why Apple Silicon is useful for local LLM prototyping and LoRA experiments, but still has sharp boundaries compared with CUDA-scale NeMo or Hugging Face training.
Mar 16, 2026 Shared reading
This is a classic reference for understanding PostgreSQL below the SQL surface. Query processing, storage, concurrency, and transaction behavior become much less mysterious when the internals are visible.
My notes → Mar 15, 2026 Shared reading
This is a small but useful data-team link because SQL style is a collaboration tool. A query that is easy to review, modify, and debug is a data product maintenance win.
My notes → Mar 14, 2026 Shared reading
This belongs in the queue because database performance is often where application assumptions meet physical reality. Indexes, query plans, and access patterns are product concerns when latency becomes user-visible.
My notes → Mar 13, 2026 Shared reading
This is useful because data modeling is still one of the quiet foundations of analytics, ML, and application design. Good models make downstream work boring in the best way.
My notes → Mar 12, 2026 Writing
Why Hugging Face's faster Transformers work matters beyond GPT-OSS, and how kernels, MXFP4, parallelism, KV cache, batching, and model loading change practical LLM runtime decisions.
Mar 12, 2026 Shared reading
This is a good systems explanation for software developers who use databases every day but have not built a mental model of parsing, planning, storage, indexes, and execution.
My notes → Mar 10, 2026 Shared reading
This is an evergreen frontend architecture link because URL state is not just routing trivia. It affects sharing, refresh behavior, deep links, browser history, analytics, support, and whether a product feels native to...
My notes → Mar 9, 2026 Shared reading
This older workflow/state-machine link is worth keeping because the lesson keeps repeating: protocols, product flows, and background jobs become easier to reason about when states and transitions are explicit.
My notes → Mar 8, 2026 Shared reading
This is a useful architecture link because CQRS is powerful and easy to overapply. Separating reads from writes can clarify a system, but it can also introduce synchronization, consistency, and mental overhead.
My notes → Mar 8, 2026 Writing
Why LLM fine-tuning projects fail when teams jump to NeMo or Hugging Face training commands before deciding the model, data, evaluation, serving, and governance loop.
Mar 8, 2026 Writing
A data platform failure pattern where tool replacement looked like the fix, but the real problem was ownership, release discipline, metric mismatch, and governance outside the workflow.
Mar 7, 2026 Writing
A practical AI evaluation essay showing how locally strong retrieval, reasoning, and tool-use components can interact into globally weak product behavior.
Mar 7, 2026 Shared reading
This belongs in the queue because "event-driven" can mean several different things, and teams get into trouble when they use the same phrase for different architectures.
My notes → Mar 6, 2026 Shared reading
This is a broad reference, but it is still worth keeping because system design vocabulary helps developers talk across product, infrastructure, and data boundaries.
My notes → Mar 5, 2026 Writing
How Abuela's Unity gameplay loop and supporting web surfaces can share progression state, event contracts, reward rules, and iteration hooks without duplicating game logic.
Mar 5, 2026 Shared reading
This is one of the React links that still earns a place because it explains the runtime model instead of another surface API. Understanding React as a way to describe, schedule, and reconcile UI work ages better than...
My notes → Mar 4, 2026 Shared reading
This is an evergreen frontend architecture piece because it names the hard parts of UI work: state, latency, consistency, environment, and synchronization. Those problems do not disappear when the framework changes.
My notes → Mar 4, 2026 Writing
A grounded read of NVIDIA's NVFP4 training post and why 4-bit pretraining matters for model quality, token throughput, cost, and AI infrastructure strategy.
Mar 3, 2026 Shared reading
This is a small but practical product-engineering link. Browser-native form behavior is often ignored while teams rebuild validation, accessibility, and UX affordances from scratch.
My notes → Mar 2, 2026 Shared reading
This is worth keeping because it questions the default assumption that app-like experiences require a full client-side framework. That is a healthy pressure test for product architecture.
My notes → Mar 1, 2026 Writing
A game economy design essay for Hippi Kingdom covering currency loops, sinks and sources, telemetry, a rejected progression model, and the balancing mistake that made hoarding look like engagement.
Mar 1, 2026 Shared reading
This is a useful frontend architecture link because it pushes beyond taste and asks what tradeoffs teams inherit when React becomes the default answer.
My notes → Feb 28, 2026 Writing
A practical synthesis of Drew Breunig, Simon Willison, and Anthropic on how long contexts fail, how to fix them, and why multi-agent systems need context discipline.
Feb 24, 2026 Writing
A practical map from algorithmic complexity to software engineering, data pipelines, machine learning systems, and modern LLM architecture decisions.
Feb 24, 2026 Writing
How to turn DSPy and RAG evaluation into a production release loop with golden sets, retrieval checks, generation rubrics, regression thresholds, and versioned prompt programs.
Feb 20, 2026 Writing
A practical enterprise data governance glossary that turns business intelligence, stewardship, metadata, security, privacy, quality, and lifecycle terms into usable review language.
Feb 16, 2026 Writing
A data governance operating model for assigning owners, stewards, custodians, and SMEs without leaving quality rules, access decisions, retention, source-of-truth choices, and incident closure ambiguous.
Feb 12, 2026 Writing
A practical look at Principle Stacks as a decision mechanism for teams, products, and personal priorities when important values collide.
Feb 10, 2026 Writing
A practical evaluation loop for multi-agent workflows that catches demo-friendly failures in task handoff, tool use, permissions, latency, and completion criteria before release.
Feb 8, 2026 Writing
A practical view of product planning through Shape Up, user flow, business logic, mockups, architecture, discovery, timelines, and technical debt.
Feb 4, 2026 Writing
A practical ML terminology guide for model reviews where feature definitions, data splits, task type, optimization behavior, overfitting risk, regularization, ensembles, and embeddings need to be discussed precisely.
Jan 31, 2026 Writing
A production-friendly pattern for pairing scikit-learn preprocessing graphs with PyTorch models so training and inference use the same feature contract.
Jan 28, 2026 Writing
A Dataform and BigQuery case study for turning data contracts, release lanes, validation gates, rollback behavior, and cost checks into one governed promotion path.
Jan 27, 2026 Writing
A practical guide to running MCP servers locally, choosing affordable clients, and deploying private open models with Cloud Run, Ollama, and Open WebUI.
Jan 23, 2026 Writing
A dashboard-before/dashboard-after operating pattern for turning lead measures into weekly commitments instead of passive reporting.
Jan 19, 2026 Writing
A Confluence-ready guide for designing durable HTTP APIs and wrapping them safely as Model Context Protocol servers.
Jan 15, 2026 Writing
How imbalanced classifiers can keep a strong AUC while producing probabilities that break thresholds, alerts, and cost-sensitive decisions in production.
Jan 12, 2026 Writing
A sanitized GCP platform case study where compliance, analytics delivery, and ML feature access had to be designed as one release path instead of three disconnected workstreams.
Jan 11, 2026 Writing
Why tabular models drift between notebooks and production when preprocessing, sample metadata, hyperparameter search, and persistence are not treated as one scikit-learn pipeline contract.
Jan 7, 2026 Writing
A software-developer guide to the statistics that actually change data-science decisions: samples, estimates, uncertainty, effect size, bias, probability, distributions, and model metrics.
Dec 30, 2025 Writing
A production-focused Vertex AI post on turning raw data, BigQuery features, online feature serving, model endpoints, monitoring, and retraining into one governed ML loop instead of another platform checklist.
Dec 26, 2025 Writing
A Vertex AI architecture map for teams that need to decide which Google Cloud AI services belong in the ML lifecycle, where ownership changes hands, and which older assumptions are now unsafe.
Dec 22, 2025 Writing
A long-form feature-screening workflow that uses correlation for quick linear checks, then adds redundancy clustering, mutual information, chi-squared tests, L1 models, tree importances, permutation importance, and domain review.
Dec 2, 2025 Writing
A practical TypeScript and React guide to the event loop, hoisting, throttling, debouncing, timers, closures, callbacks, IIFEs, promises, async, and await through code patterns that show up in real components.
Nov 20, 2025 Writing
A practical look at Google ADK memory, Vertex AI Memory Bank, session state, retrieval, retention, access control, and why durable agent memory needs production discipline.
Nov 16, 2025 Writing
Capability is no longer the hard question about AI agents. What the agent is permitted to do, and whether it will do it successfully, are. Here is why that distinction matters architecturally.
Nov 12, 2025 Writing
Why Codex plugins point toward a different software design mindset: fewer UI extensions, more safe agent capabilities, system access points, and operational boundaries.
Nov 8, 2025 Writing
OpenAI's April 2026 Agents SDK update matters because sandboxed execution, manifests, resumable state, and memory move agents closer to real production automation.
Nov 4, 2025 Writing
A practical AI strategy framework with a worked example that connects business levers, data readiness, pilots, evaluation, governance, deployment, and operating metrics.
Oct 31, 2025 Writing
A practical deployment guide for running Ollama behind Open WebUI on Cloud Run GPUs without mixing service specs, model storage modes, sidecar startup order, or auth assumptions.
Oct 27, 2025 Writing
A practical runbook for scoring changed rows close to the data using Snowflake Streams and Tasks or BigQuery scheduled queries and remote models.
Oct 23, 2025 Writing
A practical view of data strategy as the operating discipline that connects business goals, governance, KPIs, platforms, analytics, ML, and AI delivery.
Oct 19, 2025 Writing
How to add coverage-guaranteed prediction sets, temperature scaling calibration, and risk-coverage curves to a classifier using MAPIE — the pieces that make uncertainty quantification operationally useful rather than decorative.
Oct 15, 2025 Writing
A practical map of NVIDIA NeMo for teams that want to curate data, fine-tune open-source LLMs, evaluate them, and move from research checkpoints to production inference.
Oct 11, 2025 Writing
A practical explanation of ML metrics with decision tables for regression tolerance, rare-event classification, threshold tradeoffs, and the failure case where accuracy looked good but the decision failed.
Oct 7, 2025 Writing
A practical playbook for turning classifier scores into reliable probabilities that can support ranking, thresholds, SLAs, and cost-sensitive decisions.
Oct 3, 2025 Writing
A repeatable triage routine — the three-run baseline, DataLoader diagnosis, five profiler signatures, and a copy-paste scaffold — for finding where training time actually goes before touching the model.
Sep 29, 2025 Writing
torch.compile, mixed precision, gradient accumulation, DDP vs FSDP, and the profiler — the five levers I reach for before rethinking the model architecture.
Sep 25, 2025 Writing
A production-friendly scikit-learn pattern for mixed tabular data, class imbalance, calibrated probabilities, threshold selection, and model persistence.
Sep 21, 2025 Writing
A practical way to use algorithm complexity in product engineering, from choosing data structures to designing recommendation features that do not collapse as data grows.
Sep 17, 2025 Writing
The four reasons goal execution breaks down, the 4DX framework that addresses them, and why the apparent tension between goal-thinking and systems-thinking resolves the moment you understand lead measures.
Sep 13, 2025 Writing
Data architecture is a function, not a credential. The paths into it are genuinely varied, and that variety reflects something real about what the role actually demands.
Sep 9, 2025 Writing
A practical set of reflections on thinking quality, decision-making, analogies, conflict, expertise, and the invisible assumptions that shape product and career outcomes.
Sep 5, 2025 Writing
A design-review scenario showing why communication, facilitation, visual thinking, feedback, and critical judgment are part of engineering delivery.