Rick Blalock

🚨 Your business doesn’t break in the normal flow… it breaks in the exceptions. No-shows. Reschedules. Missing info. Scope creep. Failed payments. If exceptions aren’t contained, chaos replaces execution — and suddenly you’re “busy” but nothing is moving. 😩 Here’s the CEO truth: ✅ If it’s repeated, it’s not random. It’s a missing system. 🧾 Step 1: Track exceptions (systemically, not emotionally) Stop getting frustrated. Start collecting data. Create a simple Exception Log and tag issues the moment they happen: 🚫 No-shows 🔁 Reschedules 📎 Missing info/assets ➕ Scope creep 💳 Failed payments Every time it happens, log 4 things (quick, not perfect): Exception type Where it happened (stage/client/service) Cost (time, delayed days, or dollars) Root cause guess (no reminder, no gate, unclear policy, no owner) 🔥 Step 2: Weekly Exception Review (15 minutes) No blaming. No long meetings. One question: “What rule or automation prevents this next time?” Then: ✅ sort by frequency ✅ sort by cost ✅ fix the top 1–2 this week (not 10) Examples: • No-shows → 48h/24h/2h reminders + confirmation link • Missing info → Blocked: Missing Info stage + auto reminders • Scope creep → change order policy + tripwire phrase • Failed payments → auto-pause + dunning sequence ✅ Exceptions don’t need more effort. They need containment. Quick implementation (today) Open a spreadsheet called Exception Log: Type • Frequency • Root Cause • Fix If it happens twice → it becomes a system change, not a pep talk. 👇 If you want the full blueprint, I’d love to invite you to DRIFTLESS™ Flagship #01 📅 Tue, March 24 — 1pm CT / 2pm ET (or 9pm CT / 10pm ET) #OperationalRisk #ServiceBusiness #Operations #ProcessImprovement #Execution

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Every SaaS founder has heard it. "Don't build integrations - use our platform." "Don't build auth - use our service.". Sounds great in theory. In practice, it's been a disaster for us more often than not. We've tried three integration platforms. Each one promised to save months of dev time. Each one increased it by at least 3X. They solved 99 things we didn't need while making the 3 things we actually needed absurdly complicated. We ripped them out and switched to Inngest - a tool that makes our own code reliable rather than trying to replace it. When we built Aira.app, we figured auth was the obvious "buy" decision. Don't build authentication, right? Everybody says that. The first auth-as-a-service provider added unexpected complexity and had downtime twice in the first two weeks. Two outages. In fourteen days. For the one thing that literally can't go down. So we switched to the market leader. The biggest name in auth. 10X more complex than the first one. Not a typo. Enterprise pricing, byzantine configuration, documentation that contradicted itself. We spent more time fighting the auth tool than we would have spent building auth from scratch. We ended up on Supabase Auth. Implementation time: less than one hour. SSO, social logins, the stuff we actually need. Done. Here's what I've learned after 22 years of building Upsales: The tools that work as "buy" decisions share a pattern. Email delivery (we use SendGrid and Halon) - genuinely specialized, dangerous to DIY, invisible to users. Embedding Looker for BI - great bet. Payment processing - obvious. The tools that fail share a different pattern. They abstract things close to your core product. They solve problems with straightforward basic implementations. They create severe vendor lock-in. And they scale costs faster than value. The uncomfortable question: who is actually using all these tools successfully? My theory: overfunded VC-backed companies where the CTO is a non-founder who's never debugged a production system at 2am. During the zero-interest-rate era, companies were told to "move fast" and bought every shortcut available. They were running so fast, so eager to increase burn rate, that they never realized these "time savers" were slowing them down. When you have unlimited money, adding complexity is painless. When you're bootstrapped and profitable, you feel every abstraction layer that doesn't pull its weight. The real framework is simple: Buy infrastructure that is genuinely specialized and has nothing to do with your product. Build everything that touches your customer experience or core logic. And be deeply skeptical of any tool that promises you'll "never have to think about X again." You will - during outages, during pricing negotiations, during the migration when you rip it out. What's your experience?

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Your MVP is costing you time. Too many founders keep adding features while the market waits. Build the first clean version. Test it fast. Learn before you spend more. Ksoft helps you move from idea to MVP to launch with clear scope, senior engineers, and privacy-first execution under NDA. If your startup needs a clear MVP path, start here: https://lnkd.in/gSQ_QsmE

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Don't believe the BS that you can use Claude Code for free. Ollama recently made their API compatible with Claude Code. Many creators quickly jumped on the opportunity to farm engagement with the hook: "You can now use Claude Code for free!" My thought? Claude Code without Opus 4.5 is not Claude Code. Period. But this is exciting news. Not because I can use Claude Code for free, but because I see an opportunity to optimize costs by delegating easier tasks to local LLMs. The key question is: what tasks can local LLMs handle? I tested out 7 local LLMs. In this post, I will explain the BS and share my 1st experiment. -- Why the BS? Claude Code has been praised as one of the best AI tools by its users, not only for coding but for many other tasks. But the price feels steep to many. The $20/month plan is not enough for any serious work. You need to at least subscribe to Max 5x ($100/month). Many heavy users, including me, subscribe to Max 20x ($200/month). It’s a steal. But still, many were eager to try it but aren't ready to pay. Ollama's recent announcement means you can buy a Mac, a Strix Halo, or a GPU and use Claude Code for "free" with local LLMs. It’s appealing, as it is a one-time investment, and you can use the machine for other purposes. Creators are leveraging this opportunity to farm engagement. But the reality? Claude Code without Opus 4.5 is not the same Claude Code we praised. Local LLMs are far less intelligent. -- But for those who understand the difference, we see an opportunity to optimize costs by delegating some easier tasks to local LLMs. I'm interested in finding out what tasks local LLMs can handle. This is my typical flow when using Claude Code. This is for coding, but I have similar flows for marketing and content creation. 1. Research and planning 2. Create PRD and implementation plan 3. Break plan into bite-sized tasks 4. Implement + review with reflection pattern 5. Final review with agents 6. Final review and QA by me Based on my quick tests, we can forget about asking local LLMs to do research and planning. All of them failed at a simple instruction: "Visit https://learnparrot.ai/ and tell me about the website." So, I think the most viable use cases would only be (4) — implementation + review loops. While it looks like a very narrow use case, it is where we burn a lot of tokens. So I think it is worth a try. The main selection criteria for this will be instruction-following capability. One very common task is to refer to code samples or templates to code a new feature or page. This is a good test of instruction-following. So, I crafted my first test: - Used Opus to create HTML that I can screenshot as a LinkedIn carousel to display info for each model. - Turned one of the pages into a template and deleted the rest. - Asked each LLM to refer to the template to code its own page, given its specs. Swipe the carousel to see the results. Who would you hire? #LocalLLM #ClaudeCode #VibeCoding

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Most contractors are small shops that don't have time to learn a robust estimating software. One of our goals when building Makeoff was to support non-traditional software users. So users can just pick this up on Day 1 and use it.

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Why would a true A-player decide to work with a founder? I can only think of 5 reasons 1. They don’t know they’re an A-player 2. You significantly overpay them on cash comp (you probably shouldn’t) 3. They believe in you as a founder (they probably shouldn’t unless you’ve actually demonstrated exceptional skill at something hugely useful in startup land) 4. They believe in the company (they probably shouldn’t at early stage) 5. They are addicted to solving the problem (there’s likely a lot of sheer dumb luck in this one) Could be a mix to a certain extent As the age of AI dawns, I believe the gap in output of an A-minus player and an A-player is similar to the gap between an A-player and a C player 5 years ago. The leverage is crazy and it cuts both ways. Late stage likely increasing plays reason 2 Early stage likely has to play 1, 3 and 5. This will further increase the gap between first time founders and second + time founders who’ve already had a win. 3 should be pretty rare on first time founders. Interesting times P.S. Almost added 6 - truly satisfying work and work environment. But I’m not 100% convinced this can be sufficient on its own. It probably should be. Hapiness at work is deeply underrated. #ai #team #shipsandshipping

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