▸ Tag · #ai-engineering
AI engineering.
AI engineering as its own discipline: evaluation, retrieval, cost control, and the operational work separating a working demo from a product.
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AIOpenAI Dots for Solo Founders: An Always-On Agent in Slack and Teams, on Your Rules
One always-on ChatGPT agent keeps working on its own cloud computer after you close the laptop. Custom Rules, Slack and Teams, and the Pro price as of 28 October 2026.
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AIGrok Bot for Solo Founders: Named AI Teammates on One Shared Computer
Named AI teammates share one cloud computer and keep working after you close the laptop. Parallel work, approvals, and The X Subscription price as of 27 October 2026.
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AIClaude Duet: a proactive agent that waits for your ok
Claude Duet briefs you in the morning and waits before send, pay, or delete. What Anthropic has published, and why a solo founder might join the US Pro and Max waitlist.
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AIAI writes the code. Your job is the gates.
AI made code cheap. The engineer's job is the gate stack bad code cannot pass: tests, mutation testing, PHPStan, required CI checks, monitoring and rollback.
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AI · Updated Oct 29, 2026Claude Duet vs Grok Bot vs OpenAI Dots vs Meta Muse: pick by control and access
Four personal agents each keep a cloud computer working after you close the laptop. Pick by who says yes before a send or a payment, and whether your plan and country can get in.
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AIRun your business with one AI assistant per area
A simple setup for running any business with AI assistants: one hub, one bot per area of work, strict scopes, drafts before sends, and routines that stay quiet.
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AITraining vs inference: scaling AI systems
How training and inference differ in compute, cost, and hardware, and how to architect each phase so your AI app stays fast and affordable at scale.
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AIRAG architectures: traditional, agentic, corrective
Compare traditional, agentic, and corrective RAG architectures, with the latency, cost, and accuracy trade-offs that decide which fits your AI app.
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DevOpsDevOps vs MLOps: key technical differences for 2026
The critical differences between DevOps and MLOps. How to automate software delivery and manage machine learning lifecycles for production.
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AIContext window vs memory: building AI that remembers
Stop context-stuffing your LLM prompts. The difference between the context window and persistent memory, and how RAG + pgvector scale AI agents affordably.
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AIMachine learning vs generative AI
Machine Learning predicts; Generative AI creates. The discriminative-vs-generative split decides your architecture, infra, and monthly cloud bill.
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