Connor @ CodeStrap

[Codestrap @Codestrap_ai]

Most Companies Aren’t Actually Ready for AI

This week on Code x Connor, we’re joined by Lee McCabe of Claymore Partners to discuss the convergence of AI and private equity, why firms are struggling to create operational value, and the growing disconnect between AI hype and real-world business fundamentals.

Lee is a partner at Claymore Partners, a digital-first growth advisory firm helping private equity and their portfolio companies drive operational improvement through technology, data, and digital transformation. Prior to Claymore, Lee held leadership roles at Expedia, Meta, and Alibaba, and has spent over 25 years working across growth, operations, and digital strategy.

In this episode, we discuss:

→ Why private equity can no longer rely on financial engineering alone
→ The operational changes PE firms need to survive the current market
→ Why most companies still lack the data foundations required for AI
→ How AI amplifies both strong and broken business processes
→ The growing risks around enterprise AI costs, token usage, and infrastructure constraints
→ OpenAI and Anthropic’s partnerships with private equity firms
→ The disconnect between AI deployment headlines and actual business readiness
→ Where AI is already creating measurable enterprise value
→ How PE firms could use AI for pattern recognition, deal sourcing, and operational analysis
→ What private equity can learn from venture capital branding and media strategies
→ The rise of digital-first PE firms focused on operational transformation

Be sure to follow us to get the latest information, and schedule a meeting with us through our website!

[Codestrap @Codestrap_ai]

Episode 32 is live! Codestrap’s CxC Ep32: “Private Equity’s AI Reality Check” with Lee McCabe, Partner at Claymore Partners.

Lee is a private equity advisor, board member, investor and growth leader with 25 years of experience across big tech, marketplaces, and PE-backed portfolios. Prior to Claymore, he served as Operating Partner at AEA Investors across a 45-company portfolio, and held GM-level roles at Alibaba, Meta, and Expedia.

Claymore Partners is a digital-first growth advisory firm helping private equity portfolio companies unlock value by embedding seasoned operators and specialists across digital marketing, data, and technology.

https://t.co/IzgmUkUdRE

[Dorian Smiley @dsmiley411]

If I am a COO reading this, I think, “OK, cool. We can hopefully get through more support issues, but at what cost?”

If I am the CFO reading this, I think, “WTF are you trying to do to my P&L?”

If I am the CEO, I am thinking, “I just shit the bed.”

Every CEO who just went out there and said AI is replacing PhD-level jobs (Ken Griffin I am looking at you) is going to have to reconcile their commitment to FTE reduction with the fact that their PhD replacement can only resolve 15–35% of customer support issues.

Here’s a towel to wipe that egg off your face.

Like I have said many times before, we are entering the finding-out phase of AI. In 2027, two questions will dominate the discussion: What does it cost, and what is the error rate?
https://t.co/ZKPJmKHgWe

[Codestrap @Codestrap_ai]

If Token Burn is the Metric, What Does ROI Look Like?

Check out Code x Connor Episode 31 with guest Umesh Unnikrishnan, Head of Developer Experiences at Snowflake.

Umesh’s work focuses on scaling Cortex Code, Snowflake’s data-native AI coding agent, helping builders go from idea to production faster. Snowflake is powering the shift to the agentic enterprise with tools like Snowflake Intelligence for business users and Cortex Code for builders, helping enterprises bring data, AI, and governance together in a single platform.

In this episode, we discuss:

→ The shift from vibe coding prototypes to production-ready agentic engineering
→ How Cortex Code helps developers build and manage complex data pipelines faster
→ Why governance, auditability, and security matter for enterprise AI systems
→ The growing importance of context engineering and AI-native developer workflows
→ How Snowflake is positioning itself as the control plane for the agentic enterprise
→ Why APIs, markdown documentation, and command-line tooling are critical for AI agents
→ The rise of agent-first developer experience and AI-native software design
→ Why enterprises are rethinking token usage, ROI, and AI infrastructure costs
→ How AI is accelerating migrations from legacy systems like Oracle and SQL Server
→ Why the future of software development requires broader “full stack builder” skill sets
→ The role of monorepos, platform engineering, and scalable developer systems in the AI era

Be sure to follow us to get the latest information, and schedule a meeting with us through our website!

[Codestrap @Codestrap_ai]

AI that Actually Supports an Organization’s Talent Development Pipeline

Umesh Unnikrishnan of Snowflake joined us on Code x Connor this week to discuss the evolution from vibe coding to agentic engineering, how AI is reshaping developer workflows, and why trusted data platforms are becoming the control plane for the agentic enterprise.

Umesh is the Head of Developer Experiences at Snowflake, where he's focused on building and scaling Cortex Code, Snowflake’s data-native AI coding agent, helping builders go from idea to production faster. Prior to Snowflake, he held leadership positions at Google, Microsoft, and Pinterest making complex data and AI systems intuitive for developers. He has also been an investor and operator in high-growth startups.

In this episode, we discuss:

→ The shift from vibe coding prototypes to production-ready agentic engineering
→ How Cortex Code helps developers build and manage complex data pipelines faster
→ Why governance, auditability, and security matter for enterprise AI systems
→ The growing importance of context engineering and AI-native developer workflows
→ How Snowflake is positioning itself as the control plane for the agentic enterprise
→ Why APIs, markdown documentation, and command-line tooling are critical for AI agents
→ The rise of agent-first developer experience and AI-native software design
→ Why enterprises are rethinking token usage, ROI, and AI infrastructure costs
→ How AI is accelerating migrations from legacy systems like Oracle and SQL Server
→ Why the future of software development requires broader “full stack builder” skill sets
→ The role of monorepos, platform engineering, and scalable developer systems in the AI era

Be sure to follow us to get the latest information, and schedule a meeting with us through our website!

[Dorian Smiley @dsmiley411]

AI may destroy a SaaS company’s seat based economics but replace it with agent interface economics which are far more lucrative.

The new revenue model for SaaS might be:
Revenue =
human seats
+ workflow execution fees
+ data transfer fees
+ concurrency fees
+ data/governance add-ons
+ outcome-based pricing

Nothing here leads me to believe sticky enterprise SaaS platforms that will do anything but make a lot more money in the future. A SaaS company is a strong candidate if the have:

- Regulatory / compliance moat
- Data asset moat
- Is a system of record or a system of action
- Has high switching costs
- Has broad integration surface
- Has pricing power (Required to complete automated workflows)
- Is building an AI-native interface

Not investment advise. Is a thesis I am developing. CRM earnings will be something to test.

[Connor @ CodeStrap @connor_deeks]

I see it in Corporate America too. Let’s solve this! Let’s build solutions that cultivate human capital. Anthropic and OpenAI’s message is so atrocious, but let’s not complain, let’s solve it and build a counterbalance.

If you’re a strong software or data engineer and you feel you’ve lost purpose, freaking HIT US UP at Codestrap.

[Codestrap @Codestrap_ai]

The risks of deploying probabilistic AI in systems that depend on reliability

Check out Code x Connor Episode 30 with guest Brian Fornelli, Senior Director of Data Solutions and Engineering at Conagra Brands.

Brian’s work focuses on building production-grade decision systems that drive real business outcomes at scale. Conagra Brands is a leading North American packaged foods company with a strong portfolio of iconic and emerging brands focused on driving growth through innovation, data, and operational excellence. Brian, welcome to Code and Connor.

In this episode, we discuss:

→ Why cross-functional teams outperform traditional enterprise org structures for AI
→ The risks of deploying probabilistic AI into real-world operations
→ Why most enterprise problems don’t need advanced AI
→ The importance of observability, governance, and traceability in AI systems
→ How enterprises balance platforms like Palantir, Databricks, and Snowflake
→ Why AI-generated software may matter more than AI-powered operations
→ The coming pricing, supply, and GPU challenges facing enterprise AI
→ Why organizations need better ways to measure AI ROI and productivity
→ The risks of unbounded “vibe coded” enterprise applications
→ Why deterministic systems and traditional ML still matter alongside LLMs

Be sure to follow us to get the latest information, and schedule a meeting with us through our website!

[Dorian Smiley @dsmiley411]

I am so proud of what our team has created! Total breakthrough on every level: cost, continued talent development, and understanding the impact of AI on the organization. Hats off to the entire CodeStrap team! Learn more at https://t.co/m03kf0Nq3f. Book a time to speak with us about X-Dev!

[Dorian Smiley @dsmiley411]

The absolute favorite part of my job is seeing demos from the team. Today's demos were just stellar. I got to see our new commercial platform engineered by Igor Kopach which is ready to scale to millions of users. I got to see our code generators cutting token costs by 50% in Claude and Codex. Hats off to Przemysław Nowak for engineering what I believe is a patentable code generation process and API architecture. And I got to see our alternative to the Claude CLI and Codex CLI engineered by Andrzej Fricze which includes a stellar UI and developer experience. This is a major milestone for @Codestrap_ai !

[Laura Bratton @LauraBratton5]

“Companies are being pushed to use AI at unsustainable rates…The risks will become unsustainable and translate to financial losses.” — @Codestrap_ai CEO @connor_deeks

[Laura Bratton @LauraBratton5]

Exclusive for @theinformation: States are approving initial moves from big insurers to cut AI coverage from some corporate insurance policies.

Corgi COO @emily_yuan_ said the insurers are “very spooked by AI.” And that could seriously slow enterprise AI adoption.

[Connor @ CodeStrap @connor_deeks]

Every part of this post assumes usage and output is a positive signal. It’s not. More code is a liability, having AI review AI is fucking stupid, and of course engineers incentivized to have something do their job for them are gonna pull the “go to the beach” lever.

You’re perpetuating a false narrative

[Connor @ CodeStrap @connor_deeks]

Couple bad outcomes (like losing money) with bad sentiment (from AI labs saying everyone loses their jobs while they get rich, growing risk vectors, and next to no capability outcomes that have moved the needle and what you have is a bubble that’s gonna pop.

Then the grown ups take over

[Connor @ CodeStrap @connor_deeks]

Maybe if Dario and Sam didn’t continue to paint a dystopian future, things would be different. Oh AND they are entirely unlikable people, they have nothing inspiring to offer, no charisma, no endearing qualities. They’re arrogant in the worst ways, and when you couple that with horrendous visions of the future, reap what they sow.

[Codestrap @Codestrap_ai]

The future impact of AI: employee independence

CodeStrap's "Code and Connor" Episode 26 releases this week with our friend Jeff Hollan, Former Head of Cortex AI Agents and Snowflake Intelligence. Jeff led the product strategy for Snowflake Intelligence, Cortex Agents, Cortex Analyst, and Cortex Search. These core components of Snowflake Cortex AI empower developers, engineers, and data scientists to build powerful AI apps and agents alongside the world’s data and unlock insights with natural language. Prior to Snowflake, Jeff was Head of Product for Microsoft Azure’s PaaS and Serverless portfolio, where he was responsible for some of the most used and highest growth services in Azure, such as Azure Functions, Container Apps, App Services, and Static Web Apps.

Our 26th episode focuses on:

→ Snowflake’s goal to democratize AI for the enterprise
→ Should everyone be building AI solutions?
→ Snowflake Intelligence is GA - what is it, how is it different from traditional BI or copilots
→ Who is the operational user in the future for Snowflake
→ What it’s like to lead development of Snowflake Intelligence and Jeff’s learnings
→ Snowflake’s incorporation of AI into their own products
→ Snowflake recently announced $200 million partnership expansion with Anthropic.
→ The Arctic research team at Snowflake and their involvement with SLMs
→ Multimodal AI, interoperable agents and the future of enterprise AI
→ Snowflake vs. Databricks

Be sure to follow us for the latest updates, and feel free to reach out to the team at Codestrap.

[Dorian Smiley @dsmiley411]

We are saving at least 50% on Claude costs by using our generators. In this demo, the cost savings are closer to 90%. Gemini Flash Lite 3 actually wrote all the code you see in the demo, while Claude orchestrated the process using the tool-runner agent harness we built. You cannot use the harness with all-you-can-eat subscriptions, but that will not matter because Claude only sees a very small number of input tokens, and there are zero output tokens for the generated code.

Our generators are free to use and rely on a proprietary generation process. We combine deterministic elements using TS-Morph with Gemini Flash Lite and a template-based in-context learning pattern. This allows us to achieve a 97% cost reduction for specific code paths. We are launching a private beta next week, and it will open to the public after that.

[Dorian Smiley @dsmiley411]

You have to be a VC to believe crap like this. There is zero data backing the claim that millions of jobs are being lost, and there is countervailing evidence against it. More importantly, here are three foundational limits of LLMs that directly refute AGI claims:

1. LLMs have weights, not memories. That makes it hard to teach them new facts.
2. LLMs can't reliably retrieve facts. The inference layer is non-deterministic, so the same input can produce very different outputs. "Reasoning" models often make this worse.
3. LLMs can't check their own work. Today's models have no reliable way to know whether an answer is actually correct.

Any employee that can't learn new facts, can't reliably retrieve facts, and can't check their own work is, by definition, unemployable. Firms like Sequoia have been trying to smuggle a monumental claim—AGI is here, or soon will be—through an investor posture that treats reliability, economics, and defensibility as solved enough to invest. This is a prime example, made worse by lying about the data.

[Dorian Smiley @dsmiley411]

Codestrap Memorandum from the Office of the CTO: The State of AI Coding

[Codestrap @Codestrap_ai]

Where do we go from here with audio AI? What’s on @ElevenLabs roadmap

Codestrap's "Code and Connor" Episode 25 releases this week with our friend Jack Smith. Jack leads global channel partnerships and strategic alliances at ElevenLabs. Previously, he was the Employee Experience and Consumer Bank Operations tech strategy lead at JPMorgan Chase, overseeing emerging technology initiatives and leading engagement with the tech ecosystem.

Our 25th episode focuses on:

→ ElevenLabs’ recent partnerships (e.g., Square, Mastercard)
→ Evolution of voice-first AI agents
→ Will voice become the primary interface for AI agents?
→ ElevenLabs’ Agents platform and the competitive landscape
→ ElevenLabs focus on DevEx in their platforms and recent enhancements
→ Research teams inside ElevenLabs four walls
→ From pilot to production and the scaling challenges
→ Natural language interface wrapping the global API economy
→ What does the ‘voice of technology’ become in five years?

Be sure to follow us to get the latest information, and reach out to anyone directly at Codestrap!