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.
MCP connects AI to tools. Orchestrators coordinate agents. Here's the real comparison, the security data, and why production systems need both plus governance.
AI made writing code cheap. Correctness is the expensive part now. Here's how to write specs that actually guide coding agents to build it right.
Omarchy's $18M backing and 192GB desktops make local AI a real alternative to cloud APIs. Here's the honest cost, privacy, and capability math.
Losing an AI coding vendor means losing sealed chat history and reasoning, not just code. Here's how to keep that context portable and owned.
Infinite-parameter LLMs turn live data into model weights instead of prompts. Here's how they work, and what they change for data engineering teams.
The best AI coding agents in 2026 don't autocomplete, they ship. A practitioner's guide to Claude Code, Cursor, Devin, and the local tools replacing SaaS.
A self-hosted AI development stack in 2026: Rails 8, Omarchy, and Ollama replace your PaaS, Redis, and API bills. The math, the 37signals case study, and the limits.
GPT-6 Astra ties Fable 5.1 on coding benchmarks at a fraction of the cost, but Fable 5.1 wins on cache economics and long runs. Here's how to pick.
How to build a mandatory security scanning gate into AI coding agent workflows, with SAST, SCA, human review, and logging for agents like GPT-6 Astra.
GPT-6 Astra costs 2.5x more than its predecessor and still isn't private by default. Here's the real cost and privacy math against local coding models.
Is it cheaper to buy GPUs or rent cloud AI for internal tools? The break-even is lower than you think. Here's the real math and a decision framework.
AI persistent memory is durable, external storage for facts and decisions outside the context window. Here's how it works and why internal tools need it.
SKILL.md skills files are plain-text onboarding guides for AI agents. Here's how progressive disclosure works, why sprawl and security risks are real, and how skills pair with MCP.
Anthropic cut Claude's cache-read price 75% without touching the sticker rate. Here's how token cache pricing works and why it decides your real AI bill.
Same list price, different bills. Compare GPT-6 Astra and Claude Fable 5.1 on cost-per-task, cache pricing, and benchmarks for internal AI agents.
Human review can't catch vibe-coded PRs anymore. Here's the mechanical pipeline, from mutation testing to canary releases, that tests AI code before it merges.
Five Apache-licensed local coding models that match GPT-4o on benchmarks, run on one GPU, and cost nothing per token. A practical buyer's guide.
AI writes microcontroller firmware, decodes undocumented chips, and now designs PCBs from prompts. What it can and can't do, with real numbers.
Learn how developers turn rotary phones, old laptops, Kindles, and spare phones into a subscription-free smart home using open-source local AI scripts.
Mac Studio TCO vs cloud API subscriptions for local AI agents: the three-year math, the 94/6 routing trick that cuts bills by 90%+, and the hardware catch.
From a hidden LibreOffice install inside ChatGPT to 5% GPU utilization, here's what's bloating your AI tooling stack and how LLM inference cost optimization fixes it.
Looped transformers reuse the same layers repeatedly to reason in hidden math, not words. Here's how they work, why OpenAI's Astra uses them, and the safety tradeoff.
Recurrent depth loops shared transformer layers instead of stacking new ones. Here's how it powers GPT-6 Astra and why it raises governance concerns.
Three independent studies show AI coding agents default to grep over LSP and embeddings. Here's the data and the layered toolchain that actually works.