Economic turbulence is not new. This startup playbook for economic uncertainty covers four mistakes founders make and what the ones who came out stronger did differently.
Agentic engineering startups are redefining what it means to ship software. Andrej Karpathy did not just coin a phrase.
AI agents don’t fail dramatically — they lie confidently. The real danger in production isn’t crashes, it’s silent plausible-sounding errors that compound before anyone catches them.
Most SaaS free trials end without converting — not because the product is bad, but because the trial experience fails the user. Here’s what’s actually going wrong and the top fixes.
Forward deployed engineers are the fastest-growing job in enterprise AI. That tells you self-serve SaaS is dead for anything that requires real behavior change.
The AI race is not going to the biggest models. It is going to the most specialized ones. Here is why vertical AI startups have a structural advantage that horizontal platforms cannot easily overcome.
Benchmarks say AI agents can do anything. Production says otherwise. Here are the specific failure modes and a framework for deciding when to trust an agent with real work.
OpenAI acquired Astral, the company behind uv, Ruff, and ty. This puts critical Python infrastructure under AI company control. Here is what developers need to know.
Also, meta reportedly delayed their next flagship AI model, codenamed “Avocado”, after sinking billions into training it. Indeed, the delay is framed as a technical setback.
Should you hire or automate? It is the most common decision early-stage founders get wrong. Here is a practical framework for knowing exactly when each answer is right and how to use automation to make every hire count.
At GTC 2026, Jensen Huang doubled Nvidia’s chip revenue forecast to $1 trillion. The bet is on AI inference, not training. Here is what that shift means for builders.
Also, AI replacing consultants is not a future scenario. It is already happening.