15 posts found
OpenAI shipped GPT-6 Astra, the first model built to work alone for days at a time. I explain why this launch feels different from everything that came before — and where the marketing narrative already oversteps.
Meta named the problem: Behavioral State Decay. The instruction is there. The AI 'sees' it. But stops acting on it. The fix: a second AI agent — the 'shoulder tap' — that injects selective reminders. +8.3 points on Terminal-Bench. Without retraining the model.
The SaaS market is worth $140B. The labor market is worth $11.7T. When software starts DOING the work instead of organizing it, the TAM explodes 83x. Salesforce already earned $800M with Agentforce. Zendesk charges $2 per resolution. The per-seat model is dying.
A compiled 3B model beat the same 3B model with external orchestration on 4 of 5 metrics (p<0.001). 128-462x cheaper. 2.8x faster. 87-98% quality. The paper challenging LangGraph, CrewAI, and the entire orchestration industry.
Gartner predicts 40%+ of agentic AI projects will be scrapped by 2027. Anthropic says: 'don't build agents when workflows suffice.' And in 2026, the market conversation shifted from 'building agents' to 'orchestrating agents.' Start with the rails.
85% per-step accuracy sounds good. But in a 10-step workflow, that's 20% success. Gartner predicts 40%+ of agentic AI projects will be scrapped by 2027. The fix isn't a better model — it's engineering I wish I'd learned sooner.
Stanford proved that changing only the harness — without touching the model — creates up to 6x performance swings. Meta-Harness ranked #1 on TerminalBench-2, beating all human solutions. The problem was never the model.
On April 4, 2026, Anthropic cut OpenClaw usage via subscriptions. Thousands saw costs spike 50x. And a 512,000-line code leak revealed the real reason: Project Conway.
OpenClaw is the fastest-growing open source project in history. But with 9+ CVEs and 135,000 exposed instances, security was a nightmare. NVIDIA just fixed it with a single command.
I spent months thinking the secret was the perfect prompt. I was wrong. The shift from prompt engineering to context engineering transformed how I use AI — and how I communicate with humans too.
Kiro deleted an AWS production environment, causing a 13-hour outage. Then Amazon's checkout went down for 6 hours. The 'vibe coding' era has hit its limit.
Alexey Grigorev lost 2.5 years of production data when an AI agent executed terraform destroy. The real-world case every developer and company needs to know.
Did Claude Skills come to replace MCP? No. They're complementary layers of the same architecture. Here's why using both together is the right answer.
Summer Yue, Meta's AI alignment director, lost control of an AI agent that deleted her emails ignoring 3 stop commands. This is the dangerous side of autonomy.
The transition from language models to execution agents is redefining what we expect from technology in 2026.