22 posts tagged “llm”
Software architects and engineers who treat AI as simple autocomplete will watch their skills become obsolete in 12 to 36 months. How I built Cruvero as the production control plane for agent swarms that now outperform the top 1 percent of FAANG engineers. Includes my real production example of prepping data and fine-tuning my personal model on two RTX 5090 GPUs.
A practical, trust-first workflow for planning, prompting, executing, and reviewing LLM-assisted development.
An end-to-end example of migrating a procedural runbook to a durable Temporal workflow using reference implementations, phased prompts, and verification.
A production-grade, Temporal-native AI agent orchestration platform in Go: durable multi-agent workflows, governance, MCP integration, and an operational UI.
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.
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.
An example-heavy pattern for multi-week LLM-assisted work: phase specifications, implementation prompt documents, and strict execution gates.
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.
A trust-first, executable loop for LLM-assisted development: plan artifacts, prompt docs, work notes, verification, and commit discipline (with a worked example).
Budgets, quotas, and circuit breakers for LLM systems - because runaway cost is just an outage where the failure mode is billing.
Production-grade MCP servers in Go that expose iCloud, Todoist, and Notion as safe, typed tools for LLM agents.
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