
How to Run Distilled AI Models Locally (DeepSeek-R1, Ollama)
Learn how to pick, quantize, and run distilled models like DeepSeek-R1 locally with Ollama or llama.cpp, and when self-hosting beats API costs.
How engineers use AI, how to do it well, and what it means for your job. Written for people who ship and run the software, not people who build models.

Learn how to pick, quantize, and run distilled models like DeepSeek-R1 locally with Ollama or llama.cpp, and when self-hosting beats API costs.

Omarchy is DHH's Arch and Hyprland desktop with built-in AI coding agents. See review scores, security issues, costs vs Codespaces, and who should switch.

Learn how to set hard, pre-call spend caps on AI APIs, provider by provider, plus loop guards and rate limits that stop a runaway agent's bill.

Compare Ollama, LM Studio, llama.cpp, Open WebUI, AnythingLLM, and vLLM across runtime, interface, and server layers, plus VRAM needs and cost.

Codex Ultrafast requires the $500 Pro plan and burns allowance at 6-8x the standard rate. See the cost math against Claude Sonnet 5.5, Claude Max and DeepSeek.

Learn how to run Claude Code, Copilot, Cursor, and Codex together with a secrets vault, git worktrees, task routing, human review gates, and audit trails.

Compare Llama, Qwen, Mistral, DeepSeek, gpt-oss, and small models by license, hardware needs, and self-hosting break-even to pick one for internal tools.

Set up a free local AI coding agent with Ollama, Qwen2.5-Coder or Devstral, and Aider or Cline. Covers hardware, benchmarks, costs vs Copilot, and tradeoffs.

Real examples of AI agents running business workflows in labs, support, legal review, coding, and scheduling, plus where SaaS seats still win.

Compare the total cost of self-hosting open-weight LLMs vs. ChatGPT Enterprise and Microsoft Copilot, with per-seat pricing, break-even points, and hidden costs.

Klarna's AI assistant did the work of 700 agents, yet the company rebuilt a human support layer in 2025. See what changed, why, and how its hybrid model works.

Learn how to cut LLM API costs with prompt caching, batching, model routing, context trimming, and self-hosting, plus the pricing math behind each method.

Compare AI coding agent token costs with flat IDE subscriptions like Cursor and Copilot, including real budget data from Uber, DX, and Vantage.

Learn how to review AI-generated pull requests with automated security gates, slopsquatting defenses, and a human checklist built for how AI agents fail.

Build a self-hosted AI router with LiteLLM, open-weight models, and a vector database. Includes AT&T's 56% cost cut, setup steps, and per-seat cost comparison.

Learn how to run several AI coding agents on one repo without merge conflicts, using git worktrees, ownership-based task splits, serial merges, and CODEOWNERS.

Set up a CI gate with secrets scanning, dependency checks for hallucinated packages, and blocking SAST, enforced by branch protection on every pull request.

Build a local AI second brain with markdown notes, Ollama, a local vector store for RAG, and automation. Covers hardware needs, tradeoffs, and maintenance.

Claude Haiku 5.5 vs. local models for coding, compared on API token prices, electricity, and the engineering time each takes to run and maintain for a team.

Can AI solve complex math problems? Top models reached gold-medal scores at the 2025 IMO but still miss basic word problems. Here is where AI math works and where it breaks.

AI decision models vs. LLMs compared on how they work, cost, latency, and benchmark results, with guidance on when to use each for routing and classification.

Compare GPT-6 Astra, Claude Opus 5.5, and open-weight models like DeepSeek V4.1 Flash for internal tools, with pricing, benchmarks, and self-hosting costs.

Compare a $1,000-$2,500 local AI rig with ChatGPT Plus or Claude Pro: break-even in 11-24 months, electricity costs, and open-model quality tradeoffs.

Learn how local vector databases, AST indexes, and semantic tool routers can cut LLM token spend 40-90% by sending only the context each query needs.