Notes, comparisons and practical thinking on software, AI, products and digital systems. Built from things I study, test, build and learn along the way.
A forest-monitoring exercise shows how buffering, recovery targets and limited bandwidth turn software architecture into a series of explicit trade-offs.
software architecture · reliability dependability · 7 min
Choose development tools that make correct work easier. Balance formatting, linting, types and tests against setup friction, exceptions and maintenance.
Build predictable releases with validation, restricted credentials and manifest ownership. Examine the boundaries of this static site’s deployment pipeline.
Separate DNS delegation, hosting, TLS and HTTP redirects. Lessons from moving this static site from SiteGround toward its verified HostingPerTe deployment.
Clear commits preserve the reasoning behind software changes. Make history useful for review, debugging and recovery without burying behavior in noise.
Integration failures emerge from timing and conflicting assumptions. Design for retries, duplicate delivery, partial updates and evidence across boundaries.
A catalogue job can succeed while publishing incorrect prices or mappings. Add semantic checks, reviewable changes and recovery to the import boundary.
Treat supplier spreadsheets as versioned external interfaces. Make schemas, provenance, missing values and identity rules explicit before importing rows.
Limited time and operating capacity shape architecture. Use the static publishing workflow to examine fixed costs, reversibility and justified complexity.
Design experiments that can stop a weak idea as well as support it. Define decisions, measurement checks and stopping rules before interpreting results.
Use interviews to understand recent behavior, workarounds and constraints. Treat feature requests as clues to investigate before committing to a solution.
Scope a first product around the assumption you need to test. Choose evidence, participants and decision rules before turning a hypothesis into a backlog.
Make repeatable Python catalogue jobs with explicit inputs, rejected rows, dry runs and deterministic output, then define what a successful rerun means.
Design AI features around inputs, retrieval, evaluation and recovery. A model response needs a reliable product workflow before anyone can depend on it.
Useful AI context includes repository state, schemas, examples and tool results. Curate evidence and authority instead of polishing one instruction forever.
Make repository tasks verifiable with acceptance criteria, focused context, meaningful tests, visual review and clear boundaries for a production release.
Architecture decisions depend on assumptions that change. Record context, review triggers and migration costs so yesterday’s sensible choice stays visible.
Complexity grows when components, people and states must agree. A practical look at coupling, shared state and the coordination hidden inside architecture.
More apps can create more places for work to disappear. Design a productivity stack around clear ownership, fewer handoffs and recovery after interruption.
When a service becomes part of your infrastructure, migration and data access matter. Compare SaaS tools through boundaries, recovery and a tested exit plan.
Files, permissions, processes, ports and logs make infrastructure inspectable. Use a Linux investigation to narrow a failure without breaking more things.
Control can live in source, content and a portable build. A practical look at static hosting, independent recovery and the limits of infrastructure ownership.
Memory, storage, thermals and ergonomics shape daily development. Evaluate a laptop through a workflow and its constraints, rather than a specification contest.
Versioned articles, validation, static builds and search indexing form a publishing pipeline. Here is how this site connects editorial changes to delivery.
A stock number means little without ownership, reservations and freshness. Explore overselling, delayed updates and reconciliation across sales channels.
Scripts, publication gates and nearby documentation turn repeated project decisions into a predictable workflow that humans and coding agents can both follow.
Catalogue, prices, orders and stock overlap across commerce systems. Decide who owns each fact, how changes travel and how conflicts are detected and repaired.
A small visitor counter was pulling this portfolio toward a backend. Removing it made the hosting decision simpler without giving up the features that mattered.
The happy path is only the beginning. Design integrations around ownership, retries, idempotency, partial updates and reconciliation of uncertain outcomes.
WooCommerce can support commerce, while integrations and operating rules need their own design. Examine data ownership, extensions and recovery at the edges.
Multi-channel commerce is an integration problem: shared product facts meet different schemas, publication states and failure modes that need explicit handling.
Supplier files need an explicit boundary: preserve the input, detect its schema, normalize carefully and validate meaning before creating channel exports.
A roadmap can explain strategic choices without pretending uncertainty has disappeared. Make bets, dependencies and review points explicit before promises.
Supplier files become a systems problem when identifiers, variants, prices and stock disagree. A practical way to build a catalogue you can safely publish.
product information management · supplier data · 7 min
Reconsidering an all-in-one product can reveal a clearer entry point. Notes on FiscoBud, focused scope, educational support and a credible path to expansion.
Public updates can create conversations, but attention alone cannot validate a product. Define the learning goal, audience and evidence before sharing work.
Compliments cannot carry a product decision. Connect assumptions to recent behavior, existing alternatives and experiments that can genuinely change the plan.
Distribution, buying decisions and trust belong in product discovery. Trace the route from a customer problem to a first conversation and useful adoption.
The useful work begins before building: identify a risky assumption, choose evidence that could change a decision and design the smallest meaningful experiment.
Pricing shapes who a SaaS product serves and how customers experience its value. Explore packaging, usage measures and honest tests of willingness to pay.
Revisiting FiscoBud exposed a useful distinction: a coherent product concept can still rest on untested problems. Feature planning needs evidence underneath it.
Latency, cost, rate limits and recovery shape an AI feature long before a model benchmark settles the choice. Design the dependency around the actual user task.
A practical way to choose automation boundaries for catalogue work: stable transformations, inspectable inputs, visible exceptions and deliberate human review.
Visual workflows can coordinate useful work without owning each rule. Examine testing, recovery and the point where domain logic deserves its own boundary.
Better AI-assisted work starts with approved decisions, useful evidence and clear limits. A practical approach to context that survives real project changes.
prompting context engineering · llm workflows · 7 min
An LLM workflow needs a route for uncertainty, invalid output and exhausted retries. Design review queues and deterministic checks before automating decisions.
An impressive output is a starting point. Build an evaluation plan around realistic tasks, visible failures, human review and changes to prompts or models.
AI-assisted changes need inspectable evidence: repository context, meaningful tests, visual checks and diff review. Generation is the beginning of the workflow.
Building this website with a coding agent changed the unit of delegation: a bounded engineering task, with repository context, checks and a reviewable result.
Web systems accumulate complexity around state, URLs, caches and integrations. Follow a catalogue change across boundaries a polished interface can hide.
Removing a visitor counter simplified an entire operating model. A field note on maintenance cost, safe deletion and responsibilities hidden behind features.
Turn vague promises about reliability into measurable scenarios, with explicit failure conditions, recovery boundaries and evidence a test can actually collect.
requirements engineering · reliability dependability · 7 min
Fewer clicks can still mean more confusion. A practical argument for interfaces that expose state, explain choices and reduce the memory a task requires.
Reliability becomes visible when networks fail and work must recover. Explore buffering, bounded retries and requirements that describe useful failure behavior.
Tests earn trust by exposing mistakes. A practical look at boundaries, regressions and failure cases, using the verification workflow behind this static site.