Startup Hakk

Spencer Thomason
  • 0.0 (0)
  • Entrepreneurship
  • Updated weekly

Welcome to StartupHakk. My name is Spencer Thomason. I am the CEO and Co-founder of CleanRouter, as well as many other products. Here are some lessons that I've learned building a successful business while challenging startup norms. My challenge is to push you to rethink startup success.

  1. 1 day ago

    Is the AI Bubble Bursting? Here is how to survive!

    The AI boom is starting to show the same pattern every major tech cycle shows eventually: the hype gets loud, the money gets reckless, and then the real value has to prove itself. Today we go over whether the AI bubble is starting to crack and what actually survives if the market cools down. AI valuations are running far ahead of fundamentals, hyperscalers are spending enormous amounts on infrastructure, and companies are discovering that AI budgets can disappear quickly when there are no guardrails. The important point is not that AI is fake. It is that not every AI business model makes sense. A useful technology can still be surrounded by bad economics, overbuilt infrastructure, weak ROI, and companies chasing a trend without understanding what they are really paying for. We look at the warning signs: disconnected valuation math, infrastructure spending that may be running ahead of demand, falling compute prices, upside-down unit economics, and enterprises spending heavily without clear results. Then we look at the part of the AI cycle that may actually last: local-first tools that give developers and companies more control. OpenMonoAgent.ai is built around that idea. It runs locally, avoids API costs, keeps data inside your environment, and gives developers an open-source AI coding agent they can actually own. The future of AI will not belong to whoever spends the most on hype. It will belong to the teams that build useful systems with clear economics, privacy, control, and real engineering behind them. Links: https://StartupHakk.com/Spencer https://OpenMonoAgent.ai https://OpenMonoAgent.ai/landing-free https://github.com/StartupHakk/OpenMonoAgent.ai #AI #coding #programming #education #codeyourfuture

    13 min

  2. 2 days ago

    IS THE BUBBLE BURSTING?

    The AI industry has spent massive amounts of money chasing growth, but the real economics are starting to show through.Today we go over why AI costs are becoming a serious problem for companies, developers, and executives trying to build around these tools. Usage caps, rising token bills, enterprise spending limits, and public comments from AI leaders all point to the same thing: the cheap AI era was never as stable as it looked.For years, many companies built workflows around tools that felt inexpensive because the true cost was hidden, subsidized, or pushed into the future. Now the bill is starting to arrive, and businesses are asking the question they should have asked earlier: what does this actually cost when it scales?We look at why the AI bubble conversation is not just about hype. It is about business models, infrastructure costs, vendor lock-in, data control, and whether companies can keep paying for intelligence by the token forever.This is also why local AI matters. OpenMonoAgent.ai gives developers a different option: run the agent locally, use your own hardware, protect your own data, avoid surprise API bills, and keep control over the workflow instead of depending completely on a cloud provider.The future of AI will not belong to the companies that spend the most blindly. It will belong to the teams that understand the economics, control their infrastructure, and build systems that still make sense when the hype cools down.

    16 min

  3. 3 days ago

    Where We Are At With AI — Current State of LLMs

    Where We Are At With AI — Current State of LLMsLLMs are powerful, useful, and already changing how people build software, but the story being sold around them is starting to look very different from what the technology can actually deliver. Today we go over why the AI industry may be running into limits that more GPUs and bigger models cannot automatically solve. Billions have been announced in AI drug discovery partnerships, but the real results have not matched the promise. Infrastructure spending is exploding, model training is getting more expensive, and the assumption that bigger models will naturally lead to real intelligence is becoming harder to defend. The point is not that LLMs are useless. They are not. The point is that they are being marketed as something much bigger than what they actually are. These systems are extremely good at pattern matching, language generation, code assistance, and workflow acceleration, but they still struggle with truth, causality, world models, and knowing when they are wrong. We look at why hallucinations are not just a small inconvenience, why “jagged intelligence” makes AI difficult to trust in production, and why the gap between an impressive demo and a reliable system is where so much AI spending disappears. We also go over why real engineering is making a comeback. The companies that win with AI will not be the ones chasing the loudest AGI narrative. They will be the ones building focused systems around specific business problems, clean architecture, human verification, and workflows that actually survive contact with the real world. AI is not magic, and it is not a dead end. The advantage belongs to the people who understand what it can do, where it breaks, and how to build around those limits.

    15 min

  4. 4 days ago

    Anthropic IPOs to lock in AI at the peak

    Anthropic’s IPO may become one of the biggest warning signs of this AI cycle. Today we go over why the company’s reported valuation is getting so much attention, why the comparison to Walmart is useful, and why revenue, profit, infrastructure costs, and market timing matter just as much as product quality. The key question is simple: if Anthropic’s future is as strong as the hype suggests, why rush to go public now? We look at what an IPO really means for early investors, why public markets can become an exit window, and why AI companies are racing to turn paper valuations into real liquidity before the market starts asking harder questions. This also connects to the bigger issue in AI right now: compute costs, GPU access, data center deals, usage-based pricing, and the growing pressure on companies that rely heavily on cloud AI providers. AI is real, Claude is useful, and Anthropic is a serious company. But a serious company can still be overpriced if the valuation assumes everything goes perfectly. We also cover why more developers and companies are looking at local AI as the economics of cloud AI get more expensive. OpenMonoAgent.ai gives developers a way to run AI locally, keep their data inside their own environment, and reduce dependency on metered cloud infrastructure.

    21 min

  5. 5 days ago

    Big Tech Is Betting $715 Billion On AI — And Developers Are Paying The Price

    The AI infrastructure race is getting bigger, more expensive, and harder to ignore. Today we go over the economics behind Big Tech’s massive AI spending and why developers should be paying attention. Microsoft, Google, Amazon, Meta, OpenAI, and Anthropic are all pushing deeper into centralized AI infrastructure, but the cost of that strategy is starting to show up in pricing, subscriptions, usage limits, and platform dependency. For developers, the risk is simple: the more your workflow depends on a vendor’s cloud endpoint, the less control you have when that vendor changes pricing, removes a feature, adjusts access, or shifts its roadmap toward enterprise customers. We look at why subsidized AI pricing was never guaranteed to last, why centralized inference costs are still tied to real physical limits like power and data centers, and why smart teams are starting to think differently about how AI should fit into their stack. The answer is not to stop using AI. The answer is to stop treating rented infrastructure as if it belongs to you. OpenMonoAgent.ai was built around that idea. It is open-source, local-first, and designed for developers who want AI coding support without handing their workflow completely over to a cloud provider. The developers who win are going to be the ones who understand both sides of AI: the technology and the economics behind it.

    11 min

  6. 30 May

    The AI Coding Tool War - We Found The Winner!

    The AI Coding Tool War - We Found The Winner!The AI coding tool market has turned into a full-on race for developer attention.Today we go over what is really happening behind the growth of tools like Cursor, GitHub Copilot, Claude Code, OpenAI Codex, Windsurf, Kiro, and Google Antigravity. Each tool is fighting to become part of the developer workflow, but the bigger issue is what developers and companies give up in exchange for convenience.Faster code is not automatically better code. If AI-generated work needs production debugging, creates security issues, or exposes sensitive code to cloud systems, then the real cost is much bigger than the subscription price.We look at the security risks, the trust gap, the rising subscription stack, the problem with free tiers, and why vendor lock-in matters when your coding workflow depends on a provider that can change pricing, policies, or availability at any time.We also go over why local-first tools are becoming a serious alternative. http://OpenMonoAgent.ai is open-source, terminal-native, and built to run on local LLMs so developers can keep their code on their own machine and stay in control of their stack.The future of AI coding is not only about which tool is the smartest. It is about which workflow lets developers move faster without giving up ownership of their code, data, and infrastructure.

    15 min

  7. 29 May

    AI is Getting More Expensive — We Have the Fix

    The real cost of AI coding tools is starting to show up. Today we go over why the cheap AI subscription era was never as stable as it looked. For years, venture funding and subsidized compute made powerful tools feel inexpensive, but usage-based pricing is changing that fast. Teams that built workflows around low monthly costs are now being forced to deal with token bills, budget overruns, and pricing models they do not control. The bigger problem is not just that AI is getting more expensive. It is that companies are building critical systems on top of providers that can change the rules overnight. We look at how AI costs can spiral, why token usage needs to be tracked like any other business metric, and why smart teams are starting to separate high-volume routine work from tasks that actually require expensive frontier models. We also cover why local AI is no longer a fringe option. For coding, refactoring, documentation, boilerplate, and everyday developer workflows, local models can give teams more control, better privacy, and predictable costs. That is why OpenMonoAgent.ai exists. It is an open-source, terminal-native AI coding agent built to run locally with no API costs, no cloud dependency, and no telemetry. The future of AI coding is not just about using better tools. It is about owning the infrastructure those tools depend on. Links: https://StartupHakk.com/Spencer https://OpenMonoAgent.ai https://OpenMonoAgent.ai/landing-free https://github.com/StartupHakk/OpenMonoAgent.ai #AI #coding #programming #education #codeyourfuture

    18 min

  8. 28 May

    89% of Leaders Say AI Did Nothing - Here's What They're Doing Wrong.

    https://openmonoagent.ai/?v=MQK1QRStu1gCompanies are spending more than ever on AI, but many still are not seeing the results they expected.Today we go over why so many AI projects look impressive in a demo but fall apart once they touch real operations. Starbucks pulling back its AI inventory system is one example, but the bigger issue is happening everywhere: pilots stall, productivity gains never show up, and businesses are left wondering where the money went.The problem usually goes deeper than the model. Messy data, disconnected systems, weak testing, unclear ownership, and poor workflow design can turn a promising AI rollout into an expensive failure.We look at what actually breaks when AI is deployed without the right foundation, why human review still matters, and why serious AI work needs people who understand systems instead of vendors selling quick automation.We also go over why controlled infrastructure matters. For companies that care about security, reliability, predictable costs, and ownership, local AI is becoming harder to ignore. OpenMonoAgent.ai was built for that reason: an open-source, terminal-native AI coding agent that runs locally, avoids API costs, avoids telemetry, and keeps control inside your own environment.AI is not failing because it has no value. It fails when companies treat it like a shortcut instead of infrastructure.

    14 min
See All (220)

About

Welcome to StartupHakk. My name is Spencer Thomason. I am the CEO and Co-founder of CleanRouter, as well as many other products. Here are some lessons that I've learned building a successful business while challenging startup norms. My challenge is to push you to rethink startup success.

Information

  • Creator
    Spencer Thomason
  • Years Active
    2021 - 2026
  • Episodes
    220
  • Rating
    Clean
  • Copyright
    © Spencer Thomason
  • Show Website
    Startup Hakk
  • Provider