Codestrap

Own your own AI future

[Codestrap @Codestrap_ai]

Do we still need traditional engineering teams?

In the latest episode of Code x Connor, Andrew Boyagi of Atlassian joined us to discuss why AI is accelerating software development without necessarily accelerating business outcomes, the organizational bottlenecks holding enterprises back, and what it actually takes to build an AI-ready company.

Andrew is Atlassian’s Customer CTO and Head of DevOps Evangelism, where he helps some of the world’s largest organizations optimize their developer experience and productivity. Atlassian is a recognized leader in software development, work management, and enterprise service management software, enabling enterprises to connect their business and technology teams with an AI-powered system of work that unlocks productivity at scale.

In this episode, we discuss:

→ Why developers saving hours with AI are still losing time to organizational friction
→ Why coding was never the primary bottleneck in software delivery
→ The four flows of enterprise productivity: purpose, workflow, knowledge, and intelligence
→ Why successful AI adoption requires organizational change, not just better tooling
→ The evolution of team structures across engineering and business functions
→ The growing importance of enterprise knowledge graphs and contextual AI systems
→ How companies can break down information silos and remove context boundaries
→ Why documentation quality has become a critical competitive advantage in the AI era
→ Jira as an orchestration layer in an AI-native world
→ How AI is changing the relationship between developers and the business

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

[Codestrap @Codestrap_ai]

If you want AI to work, stop locking information behind permissions

Andrew Boyagi of Atlassian joined us on Code x Connor this week to discuss why AI is accelerating software development without necessarily accelerating business outcomes, the organizational bottlenecks holding enterprises back, and what it actually takes to build an AI-ready company.

Andrew is Atlassian’s Customer CTO and Head of DevOps Evangelism, where he helps some of the world’s largest organizations optimize their developer experience and productivity. Atlassian is a recognized leader in software development, work management, and enterprise service management software, enabling enterprises to connect their business and technology teams with an AI-powered system of work that unlocks productivity at scale.

In this episode, we discuss:

→ Why developers saving hours with AI are still losing time to organizational friction
→ Why coding was never the primary bottleneck in software delivery
→ The four flows of enterprise productivity: purpose, workflow, knowledge, and intelligence
→ Why successful AI adoption requires organizational change, not just better tooling
→ The evolution of team structures across engineering and business functions
→ The growing importance of enterprise knowledge graphs and contextual AI systems
→ How companies can break down information silos and remove context boundaries
→ Why documentation quality has become a critical competitive advantage in the AI era
→ Jira as an orchestration layer in an AI-native world
→ How AI is changing the relationship between developers and the business

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

[Codestrap @Codestrap_ai]

Why AI adoption will fail without organizational readiness

Check out Code x Connor Episode 33 with guest Andrew Boyagi, Customer CTO and Head of DevOps Evangelism at Atlassian.

Atlassian is a recognized leader in software development, work management, and enterprise service management software, enabling enterprises to connect their business and technology teams with an AI-powered system of work that unlocks productivity at scale.

In this episode, we discuss:

→ Why developers saving hours with AI are still losing time to organizational friction
→ Why coding was never the primary bottleneck in software delivery
→ The four flows of enterprise productivity: purpose, workflow, knowledge, and intelligence
→ Why successful AI adoption requires organizational change, not just better tooling
→ The evolution of team structures across engineering and business functions
→ The growing importance of enterprise knowledge graphs and contextual AI systems
→ How companies can break down information silos and remove context boundaries
→ Why documentation quality has become a critical competitive advantage in the AI era
→ Jira as an orchestration layer in an AI-native world
→ How AI is changing the relationship between developers and the business

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

[Codestrap @Codestrap_ai]

AI makes coding faster, so why aren’t outcomes improving?

This week on Code x Connor, we’re joined by Andrew Boyagi of Atlassian to discuss why AI is accelerating software development without necessarily accelerating business outcomes, the organizational bottlenecks holding enterprises back, and what it actually takes to build an AI-ready company.

Andrew is Atlassian’s Customer CTO and Head of DevOps Evangelism, where he helps some of the world’s largest organizations optimize their developer experience and productivity. Atlassian is a recognized leader in software development, work management, and enterprise service management software, enabling enterprises to connect their business and technology teams with an AI-powered system of work that unlocks productivity at scale.

In this episode, we discuss:

→ Why developers saving hours with AI are still losing time to organizational friction
→ Why coding was never the primary bottleneck in software delivery
→ The four flows of enterprise productivity: purpose, workflow, knowledge, and intelligence
→ Why successful AI adoption requires organizational change, not just better tooling
→ The evolution of team structures across engineering and business functions
→ The growing importance of enterprise knowledge graphs and contextual AI systems
→ How companies can break down information silos and remove context boundaries
→ Why documentation quality has become a critical competitive advantage in the AI era
→ Jira as an orchestration layer in an AI-native world
→ How AI is changing the relationship between developers and the business

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

[Codestrap @Codestrap_ai]

AI can help companies move faster, but it can’t fix everything

Out now: Codestrap’s "Code x Connor" Episode 33 with guest Andrew Boyagi, Customer CTO and Head of DevOps Evangelism at Atlassian.

Atlassian is a recognized leader in software development, work management, and enterprise service management software, enabling enterprises to connect their business and technology teams with an AI-powered system of work that unlocks productivity at scale.

In this episode, we discuss:

→ Why developers saving hours with AI are still losing time to organizational friction
→ Why coding was never the primary bottleneck in software delivery
→ The four flows of enterprise productivity: purpose, workflow, knowledge, and intelligence
→ Why successful AI adoption requires organizational change, not just better tooling
→ The evolution of team structures across engineering and business functions
→ The growing importance of enterprise knowledge graphs and contextual AI systems
→ How companies can break down information silos and remove context boundaries
→ Why documentation quality has become a critical competitive advantage in the AI era
→ Jira as an orchestration layer in an AI-native world
→ How AI is changing the relationship between developers and the business

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

[Codestrap @Codestrap_ai]

Episode 33 is live! Codestrap’s CxC Ep33: “AI Coding’s Productivity Paradox” with Andrew Boyagi, Customer CTO and Head of DevOps Evangelism at Atlassian.

At Atlassian, Andrew helps some of the world’s largest organizations optimize their developer experience and productivity. Atlassian is a recognized leader in software development, work management, and enterprise service management software, enabling enterprises to connect their business and technology teams with an AI-powered system of work that unlocks productivity at scale.

https://t.co/ciANIfDfjG

[Codestrap @Codestrap_ai]

Why AI Voice Actually Works

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]

Are AI Agents Actually Creating Business Value?

In the latest episode of Code x Connor, Lee McCabe of Claymore Partners joined us 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]

AI Should Build the Software, Not Run the Business

Lee McCabe of Claymore Partners joined us on Code x Connor this week 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]

Are Companies Giving Away Their Institutional Knowledge to AI Labs?

Check out Code x Connor Episode 32 with guest Lee McCabe, Partner at Claymore Partners and private equity advisor, board member, investor and growth leader.

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

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]

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]

Private Equity’s “Easy Money” Era Is Over

Out now: CodeStrap’s "Code x Connor" Episode 32 with guest Lee McCabe, Partner at Claymore Partners and private equity advisor, board member, investor and growth leader.

Claymore Partners is a digital-first growth advisory firm built for private equity. They help sponsors and their portfolio companies unlock value by embedding seasoned operators and specialists across digital marketing, data, and technology. Acting as an extension of the sponsor’s team, they bring the capabilities and execution horsepower typically out of reach for lower and middle-market companies.

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

[Codestrap @Codestrap_ai]

Snowflake Summit Preview

In the latest episode of Code x Connor, Umesh Unnikrishnan of Snowflake joined us 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!

[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!

[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]

Snowflake Doesn’t Force Users to Conform to Pre-Ordained Behaviors

This week on Code x Connor, we’re joined by Umesh Unnikrishnan of Snowflake 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!

[Codestrap @Codestrap_ai]

Snowflake Helps Developers Quickly Transform Ideas into Production

Out now: CodeStrap’s "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]

Episode 31 is live! Codestrap’s CxC Ep31: “DevEx Matters: Snowflake Gets It Right With Cortex Code” with Umesh Unnikrishnan of Snowflake.

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.

Snowflake is powering the shift to the agentic enterprise, where AI doesn’t just generate insights, but takes action on trusted data. With tools like Snowflake Intelligence for business users and Cortex Code for builders, Snowflake serves as the control plane for enterprises bringing data, AI, and governance together in a single platform.

https://t.co/2fdxVf0O8w

[Codestrap @Codestrap_ai]

Snowflake, Databricks, or Palantir: Choosing the right architecture platform

Brian Fornelli of Conagra Brands joined us on Code x Connor this week to discuss operationalizing AI in large enterprises, why companies are overcomplicating adoption, and where generative AI actually delivers value.

Brian is a Senior Director of Data Solutions and Engineering at Conagra Brands, where he focuses on building production-grade machine learning systems and scalable software solutions that improve operational decision-making. With over 15 years of experience spanning applied machine learning, engineering, and enterprise systems, his work centers on deploying practical AI solutions that drive measurable outcomes in complex operational environments.

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!