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Back to AI for the Fortune 2000: How Tenex Builds an AI-Native SDLC — Alex Lieberman & CJ Hess, with Alex Lieberman & CJ Hess.

Why Won't Large Companies Rip Out Salesforce and SAP?

Alex Lieberman says ripping a system out and rebuilding it gets harder as a company moves up market, and he does not agree that Salesforce or SAP is really at risk. Those products stay because so much money is at stake. Getting the replacement wrong can mean hundreds of millions or billions of dollars, so the company stays risk averse.

For a mid-tier tool that costs a few million dollars a year, the question is whether that spend will ever move the needle enough to put engineers on a rebuild. Tenex built its own CRM and its own operating system, then ran into the other half of what software is worth: the maintenance and improvement you do not have to think about when the tool is not the core business. The prize has to justify that load. Shawn Wang is testing a smaller case, a mid-tier tool of about $40,000 a year rebuilt for about $1,000, including a better experience and changes in minutes rather than months. Startups and fast-growing mid-sized companies can move that way. An enterprise already dug into a capability rarely sets out to build a much better version of the SaaS it uses and spin that version out.

Transcript

AI for the Fortune 2000: How Tenex Builds an AI-Native SDLC — Alex Lieberman & CJ Hess ·

Latent Space: The AI Engineer Podcast

More from this episode

  1. What Does Paying Engineers for Outcomes Mean?CJ Hess says paying engineers for outcomes means rewarding output instead of hours, because hourly client work paid him less as his output got better and…
  2. What Do Fortune 2000 Companies Ask Tenex to Do?Alex Lieberman says Tenex started as an AI-powered dev shop about 18 months before this conversation, because engineering looked like the canary for AI.
  3. What Is Tenex's Meta-harness?CJ Hess describes Tenex's meta-harness, the engineering workflow used for long-running tasks.
  4. How Much Do Companies Spend on AI Tokens Per Employee?Shawn Wang says most companies spend about $10 to $200 per employee on AI tokens. AI-native companies turn the comparison into a percentage, roughly 10%.
  5. Why Do Most Enterprises Lack an AI Agent Outside Engineering?Alex Lieberman says enterprise adoption of AI looks like milestones in a race, and the drop-off is steep.
  6. Why Do AI Agents Need a Standard Process First?Alex Lieberman says you can't automate a process that does not exist.

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