Navigating the "Success Tax": How We’re Optimizing Around the Claude Surge On March 2nd, the AI landscape shifted. Claude hit #1 on the App Store—a massive win for Anthropic, but a "success tax" for those of us building on their infrastructure. Between the wave of users switching platforms for ethical reasons and the viral growth of Claude Code, the demand has reached a literal breaking point. If you’ve seen more 529 errors or "brain fog" than usual this week, you aren’t alone. As a builder, I can’t afford downtime. Here is how I’m shifting my workflow to maintain 100% quality of service: The "Golden Window" Strategy: Global traffic peaks when the US East Coast wakes up and Europe is mid-day. I’m shifting my high-token reasoning tasks to the "dead zones"—10:00 PM to 5:00 AM PST. Model Tiering & Failovers: I’m not just waiting for Opus 4.6 to respond. When high-level reasoning isn't the bottleneck, I’m failing over to Haiku 4.5. faster, more resilient to traffic spikes, and handles light tasks perfectly while the flagship cluster recovers. Cross-Collaboration (The Team Effort): I’m leaning even more into a multi-model approach. I’m using Gemini 3 Pro and the newly landed Pro 3.1 as my primary anchors for logic and long-context knowledge management. By utilizing Gemini 3 Thinking for complex architecture, I can save my Claude tokens for the specific precision-reasoning where it truly shines. Building in 2026 isn't just about code; it’s about Traffic Engineering. We’re not slowing down—we’re just working smarter. How is your team handling the rate limits this week? Are you shifting schedules or shifting models?

The brain is great for thinking, but it's terrible at storing things. As developers we try to keep too much in our heads: tasks, bugs, ideas, reminders, that little quirk the class you wrote 7 weeks ago has, what chats did you have ongoing with the AI tools. Well, something simple (and I love simple) that helps a lot: write things down on paper. Yes, on paper. Crazy, right? A notebook can save you a lot of stress, really. But, write what? -> a task you shouldn't forget to do -> an idea you had mid-work -> a bug to investigate later -> something weird you noticed in the code Just dump it there and keep working in what you need to do now. Then come back to it when you can focus on that. Bonus: if you're stuck on a problem at the end of the day (especially on Fridays), leave a few notes for your future self. What did you already try? What looked suspicious? What to try next? Then close it and rest, trusting that future-you will have the context to pick everything up later. Weekend-you is off duty.

One of our CRE clients was spending 15+ hours per week on a single research workflow. Manual browser searches. Cross-referencing government databases. Copy-pasting results into spreadsheets. Skip tracing contacts. Same process, every single week, eating half their work week alive. We killed the entire workflow in 4 weeks. Here is what nobody tells you about what real AI automation actually looks like. ━━━━━━━━━━━━━━━ It is not a chatbot and it is not connecting two apps with a Zap. It is an AI navigating government websites that look like they were built before the iPhone existed. No API. No structured data. The AI reads the page the same way the human used to. It is pulling from multiple paid data services at the same time, cross-referencing every result, and consolidating everything into one clean output that used to take someone an entire afternoon. It is running dozens of decision rules that only existed inside one person's head before we extracted them: "If this field is missing, check the secondary source." "If the data conflicts, flag it. Do not guess." "If the county is X, skip their records because they are always wrong." Nobody had ever documented these rules. We only found them by watching the person do the work on their screen. ━━━━━━━━━━━━━━━ Here is the part most AI companies will never admit. The system does not try to replace the human. When it hits something it cannot resolve, it stops. It flags the issue, shows what it found, and hands the decision to the person who actually has the judgment to make the call. That is the difference between a toy demo and a system you can trust to run your business. ━━━━━━━━━━━━━━━ One system running 24/7 without mistakes, without fatigue, and without forgetting the edge cases a human would miss at 4pm on a Friday. 15+ hours per week back. Every week. Permanently.

I was tired of spending 2 hours a day just managing my work, so I built an AI that does it for me. I combined the reasoning power of Claude with an "Antigravity" engine I’ve been tinkering with. The result? A daily routine that actually feels weightless. Here’s why... We spend 40% of our day just managing the "gravity" of our tasks. Switching tabs. Updating trackers. Drafting those "per my last email" responses. I wanted a system that deletes the friction. Now, my morning starts with a single voice note. No structure. Just a raw brain dump while I make my coffee. I talk about the meetings I’m dreading, the grocery list I forgot, and the three big goals for the day. Claude doesn’t just transcribe it. It understands the intent. The Antigravity engine then kicks in and starts "lifting" the load. It drafts the follow-ups in my tone. It reschedules my calendar to protect my deep-work blocks. It even populates my grocery cart and waits for me to hit "buy." The crazy part? The UI is almost invisible. I’m not clicking buttons; I’m just speaking my day into existence. We are moving from "Software as a Service" to "Service as a Result." The tech should be the one doing the heavy lifting, not you. Is the traditional dashboard finally dead? What do you think?

Last week, Claude went down temporarily (only for a bit). 😵 And it made me think about something bigger than one outage: A lot of teams are building workflows where AI is not a “nice to have,” but a dependency with support flows, internal knowledge retrieval, content production, analysis, routing, summarising. So what’s the plan when that dependency is unavailable? 🤔 Not for 15 minutes, but if it goes down for 15 hours, or even more? I’m not pretending to have some big framework for this. It just feels like one of those reminders that tech is fickle, and it always will be. Sometimes it exposes weak systems, sometimes it shows us something more uncomfortable: how quickly we can feel stuck without the tool. I see you my fellow marketer friends. And on a personal level, I kind of like the reminder that your gray matter still matters. (I was pretty proud of coming up with this one 😂) Curious: what would break first in your org (or your own workflow) if your primary model was down for a full day?

𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰 𝗶𝘀 𝗾𝘂𝗶𝗲𝘁𝗹𝘆 𝗴𝗶𝘃𝗶𝗻𝗴 𝗲𝘃𝗲𝗿𝘆 𝗖𝗹𝗮𝘂𝗱𝗲 𝘂𝘀𝗲𝗿 (𝗶𝗻𝗰𝗹𝘂𝗱����𝗻𝗴 𝗠𝗮𝘅/𝗧𝗲𝗮𝗺 𝗽𝗹𝗮𝗻𝘀) 𝟮× 𝘂𝘀𝗮𝗴𝗲 𝗹𝗶𝗺𝗶𝘁𝘀 — 𝗯𝘂𝘁 𝗼𝗻𝗹𝘆 𝗼𝗳𝗳-𝗽𝗲𝗮𝗸, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝘄𝗶𝗻𝗱𝗼𝘄 𝘀𝗹𝗮𝗺𝘀 𝘀𝗵𝘂𝘁 𝗠𝗮𝗿𝗰𝗵 𝟮𝟴. From March 13 through March 28, 2026 (11:59 PM PT), Anthropic automatically doubles the rolling 5-hour message limits outside weekday peak hours (8 AM–2 PM ET / 5–11 AM PT) — and all day on weekends. No promo code, no toggle, no extra cost. It applies across web, desktop, mobile, Cowork, Claude Code, Excel, PowerPoint integrations — and bonus usage doesn't even count against your weekly caps. This isn't random generosity. It's classic demand-shaping + habit formation in the AI arms race: Off-peak compute is cheaper and underutilized → Anthropic flattens load spikes without raising prices. Developers get massive extra runway for agentic sessions (big refactors, multi-agent builds, overnight runs). Teams build deeper dependency on Claude Code workflows before limits snap back. Nuance that cuts through the headlines: the doubling only hits outside peak hours (when most US/EU offices aren't grinding anyway), and it's a short 2-week sprint — not a permanent change. Still, for heavy users on $200 Max plans already burning serious compute (as we discussed last time), shifting big Claude Code marathons to evenings/weekends is effectively free multiplier right now. For engineering leads and builders: Schedule your heaviest Claude Code tasks (autonomous feature branches, large-scale migrations, full codebase audits) for after 2 PM ET or weekends — you're getting 2× the shots without friction. Use this last week to push prototypes or stress-test agents that normally hit caps fast. Are your teams already shifting Claude Code sessions to "evening mode" and shipping faster? Or waiting to see if Anthropic makes off-peak boosts permanent? What's one big thing you've shipped (or plan to) with the extra limits this week? Drop it below 👇 #ClaudeCode #Anthropic #AICoding #AgenticAI #DeveloperTools #AIPromotions #AIEconomics

Anthropic just gave 2x usage on Claude. No upgrade. No extra cost. Just... off-peak hours. Here's the deal they announced: From now through March 27, you get 2x more usage during: → Weekends (all day) → Weekdays before 5am PT / after 11am PT → Weekdays before 6pm GMT / after 12pm GMT I opened Claude this morning and saw it sitting right there in the banner. Didn't need to do anything. Just... more. Here's what I'm actually doing with this: Most of my deep work already happens outside 9-5. Weekend sessions stress-testing pipelines. Early mornings working through agentic workflows before the day starts. Turns out I've been accidentally living inside Anthropic's "off-peak" window this whole time. If you're a dev, data scientist, or builder who does your best work when everyone else is offline - this is basically free compute. The bigger thing worth noticing: Anthropic isn't just adding features. They're shaping when you use the tool. That's a different kind of product thinking. Demand-side load balancing wrapped in a user benefit. Smart. If you use Claude heavily for coding, RAG pipelines, or agentic workflows - shift your heavy sessions to off-peak windows from end of this month. You get more. It costs the same.

STOP GIVING VAGUE PROMPTS TO LLM. Bad prompts = Bad results. Use these 12 prompting techniques instead & see the magic: 1 Zero-Shot Prompting 2 Few-Shot Prompting 3 Role Prompting 4 Instruction Prompting 5 Format Prompting 6 Retrieval-Augmented Generation (RAG) 7 Prompt Chaining 8 Reflection Prompting 9 Chain-of-Thought (CoT) 10 Self-Consistency 11 Tree of Thoughts (ToT) 12 Meta Prompting What else should make this list? —— 👋 PS - Want my System Design Playbook for FREE? Join my newsletter with 200K+ software engineers: → https://lnkd.in/ehTrcyak ——— 💾 Save this for later & repost to help others learn AI prompting. 👤 Follow Neo Kim + turn on notifications.

I have been inside revenue stacks at companies of every size. The tool changes. The manual layer does not. That is the one thing I keep seeing repeat itself. A new platform lands, the process gets documented, and six months later, someone is still catching the gaps by hand before payroll. Not because the tool failed. Because the design was never fixed in the first place. That is what I am bringing to this conversation on Thursday. This session is built around a real conversation, not a prepared script. @Zoë McKenzie from @Checkr has spent the last year running real AI experiments inside this problem. We will be getting into what actually shifted, what held up under pressure, and where the manual layer finally breaks. No keynote. No pitch. Two people who have lived inside this problem talking honestly about what it actually takes to end it. See you in two days. Register here: https://lnkd.in/eRQkdX6t

I've spent the last few months trying to get multiple AI agents to build software together without me babysitting every step. Turns out the hard part has nothing to do with the model. I looked at five different frameworks for multi-agent coordination: Gas Town, GSD, SWE-AF, OpenSpec, and BMad. Each one takes a totally different bet on how agents should work together. Some let 30 agents swarm a codebase in parallel. Others are obsessed with keeping the context window clean. A couple of them won't let an agent touch code until there's a 50-page spec in place. I've been pulling the best ideas from all of them into my own Claude Code workflow at Whimsey Labs. Sunday I'm publishing a deep dive on what I found, what actually works, and where I think this is all going. The short version: the model matters way less than the arena you build around it. More on that Sunday. https://lnkd.in/giCjWgF2