Hands-on build guides with free AI tools, the latest in AI, and Forward Deployed Engineer playbooks — written for engineers who ship.
OpenAI quietly reduced the Codex model's context window from 372k to 272k tokens. We dissect the pull request, explain why this matters for engineering workloads, and how to adapt your agents.
A security researcher used GPT-5.6 and $25 in API credits to find a WordPress RCE worth $500k on exploit markets. Here's what happened, why it changes the game for engineers, and how to start.
The economics of AI are inverting. Agent swarms prove that a router directing tasks to specialized, smaller models often beats a single giant LLM on cost, latency, and accuracy.
We stress-tested Fable 5 and GPT-5.6 Sol on the NP-hard Traveling Salesman Problem. Here's the raw data, why the /goal command didn't magically solve intractability, and what it means for engineers building AI tooling.
A new study shows AI advice suppresses critical thinking, making engineers 3x less accurate but 2x more confident. Here's the raw data, why it matters for FDEs, and how to build guardrails.
Claude Code's move to a Rust-compiled Bun runtime isn't just a trivia footnote—it's a signal about where the agentic coding toolchain is heading. Here's the engineering breakdown.
An LLM auditing zero-knowledge proof code found genuine cryptographic flaws. Here’s exactly what happened, why it changes the game for engineers and FDEs, and how to start using AI for security review today.
Capital One open-sourced VulnHunter, an agentic AI tool that hunts code vulnerabilities. We break down the multi-agent architecture, why it matters for FDEs, and how to run it today.
Turn a spare Mac into a headless AI coding agent. A step-by-step engineering guide to remote SSH access, VNC fallback, and security hardening for Claude Code.
StackOverflow's traffic graph tells a brutal story about AI coding assistants. We analyze the data, explain why Forward Deployed Engineers must adapt, and show you how to survive the shift.
GPT-5.6 didn't just compute—it reasoned about a 30-year-old convex optimization conjecture and closed it with a clever prompt. Here's what happened, why it matters for engineers building real systems, and how to apply this pattern today.
Claude Code shipped a file permission dialog that trained users to click 'Yes' without reading. Here's the engineering anatomy of that misfeature, why it matters for Forward Deployed Engineers, and how to fix it.
Kimi K3 just hit #1 in the Frontend Code Arena with 1679 points. Here's what the score means, how the Elo system works for AI agents, and why it matters for engineers building production-grade frontend automation.
Explore how to bridge LLMs and MikroTik RouterOS to build, validate, and deploy network configs using plain English. A practical guide for engineers and FDEs.
Forget the A100 cluster. Using latent diffusion and clever memory optimizations, you can train a generative kick drum model on a dusty GTX 1060. Here's the audio engineering breakdown.
A security researcher tricked Claude into leaking its 'deepest, darkest secrets' via prompt injection. We break down the attack, why persistent memory is a juicy target for engineers, and how to think about LLM security.
The German AI consortium's Soofi S is a 30B open model topping English and German benchmarks. We break down the architecture, why it matters for engineers, and how to run it today.
Schema Harness cracked Arc-AGI-3 with near-perfect accuracy using structured reasoning, not massive models. Learn the architecture, why it matters for engineers, and how to run it locally.
A solo engineer built a meta-reinforcement learning agent that trains child models, all for ~$1.3K in compute. Here's the architecture, why it matters for FDEs, and how to run it today.
Deja Vu gives coding agents persistent memory by syncing a SQLite database over SSH. Here's how it works, why it matters for self-hosted AI workflows, and how to wire it up today.
Forget the AI detector snake oil. We break down a practical approach using classical machine learning to catch LLM-generated text, why it outperforms neural networks, and how to build your own.
LM Studio Bionic lets you build and run AI agents entirely on local, open-weight models. No cloud APIs, no data leakage. Here's how it works, why it matters for forward-deployed engineers, and a hands-on guide to getting started.
Moonshot AI's Kimi K3 hits the open-source scene with frontier-level reasoning. We dissect its RL scaling recipe, multimodal MoE architecture, and what it means for engineers shipping real products.
Thinking Machines just dropped Inkling, an open-weights model built for reasoning. We cut through the noise to show engineers what actually changed, how to run it locally, and where it fits in your stack.
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