Thoughts on software engineering, LLM-assisted development, and building production systems.
A trust-first, executable loop for LLM-assisted development: plan artifacts, prompt docs, work notes, verification, and commit discipline (with a worked example).
An end-to-end example of migrating a procedural runbook to a durable Temporal workflow using reference implementations, phased prompts, and verification.
An end-to-end example of the workflow: plan, prompt docs, work notes, execution loop, and verification to create a new Helm chart from a known-good reference.
How to build and maintain a team prompt library that stays useful: structure, templates, contribution rules, and governance.
Minimal templates for plans, prompts, work notes, and checklists. Copy, adapt, and keep the workflow consistent.
How to make LLM-assisted development work on a team: handoff artifacts, shared prompt libraries, and review discipline.
How to measure whether LLM-assisted development is actually helping: practical metrics, baselines, and lightweight reporting.
A production-first comparison of Go and Java Spring Boot for enterprise APIs—focused on real operational cost drivers: memory, startup, deployment surface area, and observability.
Concrete stop rules for LLM-assisted development, plus common pitfalls and a recovery checklist when things go sideways.
A production-first guide to running Model Context Protocol servers safely: threat modeling, input validation, budgets, rate limits, and telemetry—implemented with Go patterns.
Practical data-handling rules for LLM-assisted development: what never to paste, how to sanitize, and how to verify you didn't leak secrets.
Model choice is an engineering decision: match capability to task complexity, upgrade when stuck, and avoid stale vendor claims.
How to scale LLM-assisted development from a 1-day task to multi-week work: sub-phasing, parallelization, and repo hygiene.
A repeatable execution loop for LLM-assisted work: implement small units, update notes, verify, and commit (without batching).
How to preserve state across LLM sessions with work notes: decisions, assumptions, open questions, session logs, and commit links.
Turn your plan into reusable prompt docs: phase-aligned prompts with constraints, deliverables, session management, and verification.
How to turn vague work into a phased plan that an LLM can execute safely: goals, constraints, references, verification, and stop rules.
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