Topiax Learning
13 free guides on launching AI-built apps and keeping AI agents reliable. Start with the launch checklist for vibe-coded apps.
13 articles · 15 resources
LatestEvaluation12 min read
A model can win a benchmark and still be terrible inside your production system. Measure the full agent chain: accuracy, evidence, tools, concurrency, latency, cost, false actions, escalation, caching, and routing.
Showing all 13 articles
Architecture
Full autonomy makes a great demo. Controlled autonomy makes a great product. Build agents that reason where ambiguity exists, follow bounded workflows, stop at hard limits, and earn more freedom through evidence.
10 min read
Production
Built your app with Lovable, Cursor, Claude Code or Codex? Use this practical launch checklist to catch UI, Supabase, auth, permissions, SEO, mobile, performance and production failures before users do.
12 min read
Security
Prompt injection matters. The bigger production question is what a manipulated agent can actually do when tools, identities, data, and rollback paths are poorly bounded.
11 min read
Architecture
AI agents need deterministic controls around consequential writes: stable idempotency keys, explicit state machines, and reconciliation loops for ambiguous failures.
12 min read
Production
Seven production failure modes: duplicate actions, hallucinated parameters, runaway loops, permission creep, semantic drift, context poisoning, and memory leaks. Plus the guardrails that keep agents recoverable.
9 min read
Production
A demo proves that something can work. Production proves that it keeps working when everything gets messy.
8 min read
Production
Demos prove the happy path. Production fails on retrieval, tools, state, silent wrong actions, and missing release gates. Here is the failure map and what to check first.
11 min read
Evaluation
Traces tell you what happened in production. Evaluations tell you whether a change is safe to ship. Confusing the two leaves teams either blind or overconfident.
9 min read
Security
Production guardrails are not a content filter bolted on the side. They are permissions, validation, fallbacks, approvals, and stop conditions tied to the actions that can actually hurt.
12 min read
Production
A clear price and deliverable map for AI reliability work: what a fixed sprint should include, what it should not, and when freelance or in-house is the better buy.
10 min read
Architecture
Agent reliability engineering is the discipline of making AI workflows fail in known ways, with evidence, controls, and owners, not the art of demos that only work on stage.
10 min read
Evaluation
The failure modes, evaluation flywheel, and release gates that separate a convincing demo from an AI workflow your team can safely operate.
14 min read
From first demo to launch checklist.
Why “it worked in the demo” is the most expensive lie in AI8 min read
The admin access trap: prompt injection is only half the problem11 min read
The god agent trap: full autonomy is a great demo, controlled autonomy ships10 min read
The benchmark trap: your model can win and your product can still fail12 min read
Your vibe-coded app works. Is it actually ready to launch?12 min read
Resources
Carousel
An 11-page visual framework for approval screens that show the action, impact, evidence, reversibility and owner.
Access PDF: Approval UX: Human-in-the-loop is not magicCarousel
An 11-page visual framework for scoping agent tools and keeping destructive actions behind human approval.
Access PDF: Agent permissions carouselChecklist
A one-page check for every tool before an agent can use it: action, data scope, owner, logging, limits, approval and kill path.
Access PDF: AI tool + data permission checklistField note
A one-page review that compares an agent’s day-one access with what it has now, so you can narrow or remove permissions.
Access PDF: Permission drift field noteField note
A one-page worksheet for requests to give an agent more freedom, and how to choose the safest response.
Download PDF: Boundary pressure field notesField note
A weekly scorecard that turns evidence, failures, owners and open risks into a repeatable ship decision.
Access PDF: Weekly production readiness scorecardCarousel
A 10-page visual explainer on why production readiness is a loop of evidence, controls, real users and feedback.
Access PDF: Production readiness is a loopCarousel
A 10-page carousel for testing what survives when the network drops, requests repeat and state is uncertain.
Access PDF: Turn the internet offField note
Interrupt a real AI workflow on purpose and check recovery, duplicate actions and whether operators understand what happened.
Access PDF: AI field test cardField note
A visual guide to tracing the failures hidden behind a successful response.
Access PDF: AI silent failure traceCarousel
A visual field note on the gap between a convincing demo and a system people can trust.
Access PDF: Demo-ready is not production-readyField note
25 representative test cases to check an AI workflow does its job before launch.
Access PDF: Starter AI eval sheetField note
A template for running one real AI workflow through nine checks that show the gap between demo and production.
Access PDF: 30-day production reality checkOpen-source repository
Open-source code and documentation on GitHub.
View repository: Vibe Scanner (opens in a new tab)Open-source repository
Open-source code and documentation on GitHub.
View repository: LangGraph State Validator (opens in a new tab)Search Topiax offers and proof by the situation you are in.
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