Building automations that hold up in production — agents, orchestration, retrieval, and the cost of running them.
10 articles
This is the implementation category. Everything filed here starts from the same assumption: you have decided that some part of your work should be handled by an AI system, and the interesting problem is no longer whether that is possible but what it takes to make it reliable. That means agent design, tool and retrieval plumbing, the orchestration layer that decides which model handles which step, and the unglamorous parts — retries, observability, and what happens when a model returns confident nonsense.
The articles lean concrete. Where a design choice has a price attached we put the number in, because the gap between a demo and a production automation is usually measured in tokens per task rather than in capability. Where a pattern has a failure mode we describe it, since the failure modes are what you will actually spend your time on. A guide that could not help a real team ship a real automation does not belong in this category.
If you are earlier than that — still deciding what to automate first — the readiness assessment and the ROI calculator in the tools section are the better starting point, and the articles here will make more sense once you know which process you are targeting.
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MPP gives AI agents and apps a standard way to pay for APIs and digital services over HTTP. Here is what it solves, how it works, and where it fits.
LAXIMA Team
Anthropic's new dynamic workflows let Claude Code write its own custom harness on the fly - spinning up coordinated subagents to tackle migrations, deep research, triage, verification, and more. LAXIMA shares the patterns, failure modes, and field-tested tips for getting the most out of them.
LAXIMA Team
A field guide to everything LAXIMA ships for free - six AI tools, the four-hour Signal brief, and the GEO/AEO-shaped blog engine behind them.
LAXIMA Team
Anthropic vs OpenAI in 2026 is no longer a chatbot debate. This guide compares Claude Opus 4.8 and Fable 5 against OpenAI's GPT-5.6 (Sol, Terra, Luna) across reasoning, 1M-token recall, security, deployment ecosystems, pricing, and enterprise ROI.
LAXIMA Team
Sora shut down on April 26 with $2.1 million in lifetime revenue against inference costs of $1–15 million per day. Six days later, Gemini Omni leaked - a native video model wired directly into Google's reasoning stack. That sequence is not coincidence. It's the standalone gen-AI business model dying in public, and the integration layer being crowned as the next site of defensible value.
LAXIMA Team
Unlock the power of RAG. Learn the architecture, business benefits, and step-by-step strategy for building accurate, secure, and real-time AI systems.
LAXIMA Team
Claude Design is Anthropic's new conversational design tool from Anthropic Labs — build prototypes, slide decks, landing pages, and mockups by chatting with Claude on a live canvas. Powered by Claude Opus 4.7 and available in research preview to Pro, Max, Team, and Enterprise subscribers, it turns your brand's codebase and assets into a reusable design system that every project inherits automatically. This guide covers setup, prompting, iteration, exports, admin rollout, and pricing.
LAXIMA Team
Claude's 2026 lineup spans Fable 5, Opus 4.8, Sonnet 4.6, and Haiku 4.5 — frontier reasoning down to high-volume throughput. But the models are only part of the story: Claude Code runs agents in your terminal, plugins add skills, and Excel connects to live data via MCP. This is the unified technical manual — model comparison, CLI install, plugin marketplace, prompt engineering, and enterprise workflow integration.
LAXIMA Team
Stop treating Cursor like a smarter autocomplete. Updated for Cursor 3 (2026): the Agents Window, Composer 2.5, cloud agents, and the modern .cursor/rules format — plus Privacy Mode, codebase indexing, and running Claude Sonnet 4.6 (with Opus 4.8 on tap) as your agent.
LAXIMA Team
How AI agents differ from chatbots by autonomously executing tasks across business systems, and provides a 7-step implementation roadmap covering architecture, orchestration patterns, and real-world use cases showing 70% automation rates in customer service and 50% reduction in operational workloads.
LAXIMA Team