Marketing Engineer: Build a Growth OS With AI Agents
Greg Isenberg explains the marketing engineer role through a Growth OS, agent job specs, six learning systems, an HVAC example, and a 30-day plan.
Search blog posts, case studies, GitHub repo roundups, agent architecture notes, and practical AI automation guides.
Greg Isenberg explains the marketing engineer role through a Growth OS, agent job specs, six learning systems, an HVAC example, and a 30-day plan.
Andrew Warner and Adam review ten GitHub repositories for diagrams, agent context, Linux, tiny local models, knowledge graphs, model routing, video creation, public APIs, and security research, plus seven community builds.
Andrew Warner and Adam review ten trending repositories plus Investment Council and DAA. Here is what each project owns, what it replaces, and the maintenance or security boundary you inherit.
Andrew Warner and Corey Ganim review VoiceOS, Grok Bot, OmniWork, Scrimba Explain, Annotate, creator-built apps, and an AI operations service. The common thread is better interfaces around agents.
Tristan Harris connects AI race incentives, agent misalignment, labor displacement, and the intelligence curse. Here is what the evidence supports.
Alexandr Wang explains Scale AI's pivot, conviction before consensus, Meta's frontier-lab rebuild, cheap models, and agent feedback loops.
Andrew Warner and Corey Ganim review Zinley, Pandroid, SKI, Noah, AgentSky, AppLlama, Channels SDK, GenOffice, FLUX.3, and one tiny Wi-Fi utility. Here is what each launch actually is and what to test.
Jensen Huang explains how NVIDIA survived a wrong technical bet, learned new domains, rebuilt its full stack, and applies systems thinking to AI and robotics.
Cody Schneider and Greg Isenberg build a signal-based outbound agent and a transcript-driven content agent. Here is the architecture, cost boundary, platform risk, and safer implementation.
Bijan Bowen pairs Fable 5 with local Qwen3.6 27B in Traycer. Here is what improved, failed, and the solo baseline revealed about multi-agent orchestration.
Wes Roth's Qwen3.8 Max roundup rebuilt as an evidence audit: long-horizon agent results, benchmark limits, the confirmed COLDCARD RNG flaw, and the unproven AI-attribution claim.
Kacper Rutkiewicz tests Scrapling across targeted web extraction, prospect research, and design synthesis. Here is the source-checked setup, the real token math, the fetcher decision tree, and the legal and security boundaries his workflows need.
More than 1,300 frontier-lab employees asked the US government to build an international option for pacing automated AI R&D. The statement is not an immediate pause, and its hardest questions remain unanswered.
Theo argues that Kimi K3 has frontier labs and Washington panicking. Here is the evidence: released open weights, competitive benchmarks, distillation allegations, cyber testing, policy risk, and what builders should do next.
Why DeepSeek, Qwen, GLM, and Kimi are spreading so quickly, what the OpenRouter adoption data really says, how export controls changed the race, and what "free" costs in production.
Naval Ravikant deleted his calendar. Greg Isenberg and Jonathan Courtney debate why. Here is a practical founder system for deep work, meetings, async decisions, and reliable commitments.
A source-checked review of OpenMontage, Ideogram, Voicebox, Nemotron 3 Ultra, OmniRoute, Meetily, Easy Diffusion, Open Generative AI, Palmier Pro, and HyperFrames.
Nate Herk and Nate B. Jones explain why paid AI tools still stall inside companies. Here is the practical fix: sell a business outcome, redesign one workflow, add verification, and create executive ownership.
Andrew Warner and Corey Ganim review Knockoff, HeyClicky, JustVibe, social, Cowart, SceneRoll, Printing Press, Maker Skills, PlugThis, Osaurus, and Screenpipe. Here is what to test and what to protect.
A practical 15 July 2026 snapshot of GitHub Trending Developers: the people behind open notebooks, background coding agents, browser agents, terminal tools, local-first apps, Rust infrastructure, and useful developer resources.
Nate Herk argues that a valuable AI career may be created from inside your current company. Here is the source-checked four-step path from low-risk workflow wins to an in-house AI operator role.
Vaibhav Sisinty explains why token consumption is becoming a business cost problem. Here is the source-checked playbook: measure cost per successful task, route models, cache correctly, trim context, set limits, and decide when local inference pays.
Grok 4.5 for coding and agentic work: benchmarks, pricing, token efficiency, Grok Build, Cursor support, EU availability, and when it beats Fable, Opus or GLM.
Calum Johnson interviews John Hu of Stan on building an audience that buys, creator monetization, Stanley AI, digital products, and the practical path from posting consistently to making the first online sale.
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