Hands-on build guides with free AI tools, the latest in AI, and Forward Deployed Engineer playbooks — written for engineers who ship.
Real forward deployed engineer salary levels.fyi data, equity ranges, and tactical negotiation strategies. Learn what Palantir, Scale AI, and startups actually pay FDEs.
Stop building toy apps. Learn what real Forward Deployed Engineer portfolios look like: customer-facing demos, integration hacks, and TAM models that land $200K+ offers.
A no-fluff playbook for the Forward Deployed Engineer interview loop. Covers technical screens, customer-scenario rounds, and comp negotiation with real scenarios and data.
A concrete engineer-to-engineer breakdown of how AI-native startups deploy Forward Deployed Engineers to close complex enterprise deals, from technical validation to production integration, with real workflows, comp context, and no hype.
A no-fluff, engineer-to-engineer comparison of Forward Deployed, Solutions, and Sales Engineers. Real workflow differences, compensation ranges, and which role fits your career goals.
Practical strategies for Forward Deployed Engineers to earn trust with non-technical stakeholders—through shared metrics, on-site rituals, and translating ambiguity into revenue.
A concrete playbook for debugging customer-prem software when you have zero access. Covers telemetry design, live trace patterns, secure artifact capture, and the career context that makes this an FDE superpower.
A concrete breakdown of a Forward Deployed Engineer's weekly workflow—real scenarios, decisions, code, and comp numbers. No fluff, just what the job actually is.
FableCut is a browser-native video editor with zero dependencies, designed from the ground up to be programmatically driven by AI agents. Here's how it works and why it matters.
Learn how to turn any web app into a programmable agent tool without an API. We break down the reverse-engineering approach, its practical implementation, and when to use it.
Meta released Muse Spark 1.1, a fast, steerable text-to-image model API. We break down the architecture, show code for instant integration, and explore the engineering possibilities beyond simple generation.
A developer got GLM 5.2 running on a slow machine using aggressive quantization and memory offloading. Here's how it works, why it matters, and how you can replicate it today.
OpenAI's reasoning model produced a novel proof of the Cycle Double Cover Conjecture. Here's what happened, why it changes the game for engineers, and how to use it today.
Build a hands-on lead enrichment agent that scrapes company websites from a CSV of domains, then enriches each with AI summaries and ICP scoring—all using free-tier tools.
Use Ollama, n8n, and Hugging Face’s free tier to build a scheduled AI pipeline that fetches RSS feeds, summarizes articles locally, and emails you a custom digest every morning.
Ship a GitHub App that classifies issues, applies labels, and routes bugs using Groq’s free LLM tier and Cloudflare Workers AI. Full step-by-step with code, no paid tools required.
Build an autonomous agent that scrapes competitor websites, diffs changes, and summarizes updates using Playwright and Groq's free Llama tier. Complete with Supabase storage.
Ship a free Gmail AI agent that labels, prioritizes, and drafts one-click-send replies using the Gmail API and Google Gemini free tier—hosted on Vercel. No credit card needed.
LLMs don't just generate code—they fundamentally change the economics of software rewrites. Here's what that means for your legacy systems, your team's velocity, and the very definition of technical debt.
Autonomous coding agents are about to shatter traditional Git workflows. Here's why commit-and-branch falls apart when bots write 10,000 lines an hour—and how engineers are rebuilding version control for the agent boom.
Databricks benchmarked coding agents on their real, multi-million-line monorepo. The results reveal where agents shine, where they fail, and what it means for engineers shipping production code.
Noma Security tricked GitHub's AI agent into leaking private repository contents via prompt injection. Here's the technical breakdown, why it matters for engineers, and how to defend your repos today.
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