Vickson

Agentic system design concepts I'd master if I wanted to build AI that doesn't blow up in prod. Bookmark this. 1. Agent Circuit Breaker 2. Blast Radius Limiter 3. Orchestrator vs Choreography 4. Tool Invocation Timeout 5. Confidence Threshold Gate 6. Context Window Checkpointing 7. Idempotent Tool Calls 8. Dead Letter Queue for Agents 9. LLM Gateway Pattern 10. Semantic Caching 11. Human Escalation Protocol 12. Multi-Agent State Sync 13. Replanning Loop 14. Canary Agent Deployment 15. Agentic Observability Tracing

economists just mathematically proved that ai layoffs are going to bankrupt the exact companies doing the firing.. 💀 a new paper called "the ai layoff trap" just dropped and it’s terrifying. we all know replacing humans with ai cuts costs. but this task-based macro model exposes a fatal flaw: "demand externalities." if you fire workers to save cash, you capture 100% of the savings, but you only feel a tiny fraction of the lost consumer demand. the rest of the pain falls on your competitors. so what happens? a literal prisoner's dilemma. every rational ceo is forced into an automation arms race. they fire workers to stay competitive, which aggressively nukes aggregate purchasing power. the unemployed humans are the exact same consumers buying the products. at the limit, the economy hollows out and the resulting demand destruction mathematically harms both the workers and the firm owners. the craziest part? the paper proves that foresight changes nothing. even if every ceo knows they are driving the economy off a cliff, market competition traps them into doing it anyway. and here is the brutal reality check.. the researchers tested all of our favorite tech-utopian "fixes" in the model: - cuniversal basic income (ubi)? fails. - upskilling? fails. - giving workers equity? fails. - capital income taxes? fails. the math shows only one policy actually stops the death spiral: a direct pigouvian automation tax. we literally have to tax the competitive incentive of replacing a human with an ai agent. the "agentic era" just got a massive reality check.

dflash-mlx: DFlash speculative decoding, ported to Apple Silicon. Qwen3-4B at 186 tok/s on a MacBook. 4.6× faster than plain MLX-LM. Exact greedy decoding: output matches plain target decoding.

The 80/20 of multi-agent teams for non-technical people: Stop making one AI agent do everything. Build a team of 4: 1. Orchestrator: plans the work, routes tasks, synthesizes results 2. Researcher: gathers sources, verifies claims, flags uncertainty 3. Writer: turns raw findings into clear content 4. Builder: implements, debugs, tests The setup takes under an hour: - Clone your working agent 3 times (hermes profile create [name] --clone) - Give each one a SOUL.md that defines its role, tone, and priorities - Keep shared project context in AGENTS.md - Run each one separately (hermes -p [name]) Keep in mind: specialization only works when memory stays separated. If all 4 agents share the same context, you'll have one confused agent with 4 names.

Google DeepMind winning again -- just dropped TurboQuant, reducing AI memory usage by 6x and attention computation by 8x without any accuracy loss. Cheaper AI = more AI experiments = faster iteration = better models = cheaper AI. It's a compounding loop... And we're entering the acceleration phase.

I had a look and here is my 2cent regarding this announcement I run a 24/7 agent (hermes) on a mac mini. my crons and skills reads and writes to disk, talks to me on telegram. fully self-hosted. I think that managed agents solves a different problem. it's for teams who want agent infrastructure without building the infrastructure. no server management, no sandbox engineering, no error handling plumbing. ---- if you're a solo builder who wants full control over memory, file access, and cron scheduling, self-hosted still wins. I couldn't run my setup on someone else's cloud without losing the disk-level context that makes it work. however, if you're shipping agents for clients or internal tools where you need sandboxing, approval flows, and zero ops overhead, then yes this is the play. spin up, define permissions, deploy. done.

> Claude limits gone in 6 hours > $100 budget. Tuesday morning. Gone by lunch > Not a big project. Not a heavy pipeline > Claude explaining itself costs more than the answer > "Of course, I'd be happy to help!" - you pay for that > 180 tokens of politeness. Every Single Call > One caveman prompt fixed it overnight > 10,000 upvotes in 48 hours > 45 tokens. Same answer. Four times cheaper > 14,000 GitHub stars in one week > Large models rambled. Small models won > Brevity improved accuracy by 26 points > One prompt. $5,800 saved per year Read this article. My limits stopped disappearing before lunch.

Claude Code is used by developers at Microsoft, Google, and OpenAI. Anthropic's own team built Cowork almost entirely with Claude Code in a week and a half. Meanwhile, most developers are still using AI like a fancy autocomplete. The gap between "uses Claude Code" and "orchestrates Claude Code" is the biggest productivity divide in software right now. This article closes it in 15 minutes.

$1M+ in volume. 100,000+ transactions. Just 2 months in. Slowly, then all at once. ⚔️

Personally I don’t see the point of Cowork. I don’t even see the point of chatgpt or Claude anymore. I either want to talk to a claw (agent with all my skills running on a persistent computer with NO guardrails in iMessage or telegram) or i want to use Claude Code or Codex app for coding.

New item in my SOUL md tonight

forget SaaS. an AI agent is selling $48k pool installations on autopilot. this is where AI prints money. boring industries with high-ticket services and zero tech competition. look where others aren’t.

Jimmy Carr said something that should reframe how you think about the next twenty years of AI. Carr: “Life has never been objectively better and subjectively worse. Because the nature of humanity is our desires are mimetic.” One line. And it explains everything about what’s coming. Carr: “No one had a hot shower until 50 years ago. So when you stand in a hot shower, just for a moment, just go, ‘Well, no one that you admire from a hundred years ago had this simple pleasure in life.’” A Roman emperor couldn’t access what you use every morning without thinking. Newton defined the laws of light. Never flipped a switch. Lincoln ran a country by candlelight. Einstein never made a video call. The average middle-class life today would be incomprehensible to the richest person alive in 1900. And nobody feels wealthy. Carr: “There’s been a hundred billion people ever. We are in the top, top percentile in terms of the luck that we have had.” The child survival rates. The medicine. The food supply. The sheer volume of comfort surrounding every ordinary Tuesday. By every measurable standard, this is the best time to be alive in the history of the species. It doesn’t feel like it. It never will. That’s not a flaw in the world. That’s the wiring. Every gain gets absorbed into a new baseline. What felt extraordinary last year feels ordinary now. What felt like luxury becomes expectation. The goalpost moves without your permission. Every single time. This is the part nobody is factoring into the AI conversation. AI is already compressing the cost of intelligence toward zero. Within a decade, medical diagnosis that once cost thousands will be instant and free. Legal guidance that required a retainer will be available to anyone with a phone. Education that demanded six figures will be personalized and free. The abundance will be real. And most people won’t feel it. The generation that grows up with AI tutors won’t marvel at the technology. They’ll complain about the interface. The generation that gets instant medical screening won’t appreciate the miracle. They’ll be frustrated it takes ten seconds instead of two. Abundance doesn’t produce gratitude. It produces a new floor. And from that new floor, people will find new things to want they couldn’t have imagined before. You don’t build the next thing because you’re content. You build it because the current thing already feels normal. Mimetic desire is the engine of civilization and the thief of satisfaction. Simultaneously. AI will give the species more than it has ever had. The species will absorb it, recalibrate, and reach for more. That’s not a failure of the technology. That’s the loop that built everything we already take for granted. The question was never whether abundance would arrive. It was always whether the hardware would let us feel it.