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97% of enterprise developers use AI coding tools. Trust crashed from 40% to 29% in one year. METR found experienced developers 19% slower while believing they were 20% faster. The 39-point perception gap exposes why your AI investment isn't delivering—and the 4-dimension framework that fixes it.
🎙️ EP81 - The AI Readiness Assessment | The Last Mile to 4X Results with AI Coding Tools
You made the right investment. GitHub Copilot, Cursor, Claude Code—the tools work. But without readiness across 4 dimensions, AI amplifies dysfunction instead of excellence. This episode reveals the diagnostic framework and the pathway to turn your investment into exponential results.
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In this episode, Michele (Mike) Brissoni exposes the AI-readiness gap costing CTOs millions: the delta between how fast organizations adopt AI and how prepared teams are to supervise it, validate it, and integrate it. He introduces the AI Readiness Assessment framework measuring organizational capacity across four critical dimensions, reveals why spec-driven development unlocks AI for experienced developers, and demonstrates how behavioral engineering—not more tools—closes the last AI-mile.
💡 KEY INSIGHTS:
- 97% of enterprise developers have used AI coding tools
- Trust in AI accuracy dropped from 40% to 29% in just one year
- 39-point perception gap: teams 19% slower while believing 20% faster
- Experienced developers find traditional AI coding tools distracting without proper workflows
- Spec-driven development expands AI's reach from 30% to full development lifecycle
- AI readiness gap = delta between adoption speed and organizational capacity
- The bottleneck is behavior, not infrastructure
- Four dimensions determine AI success: focus, technical practices, product health, customer feedback
- Miss one dimension and you stall, miss two and you suffer, miss four and you fail
- Companies with strong fundamentals see 4X better AI results than those without
- Elite XP teams correct mistakes in one week; canonical enterprises take a quarter
- AI becomes an expensive accelerator for your failure without readiness
🗣️ KEY QUOTES:
"They were 19% slower while believing they were 20% faster."
"AI amplifies what you have in the company."
"Driving a Ferrari Enzo at 200 mph with 45% brakes—that's your AI adoption gap."
"If developers don't have the cognitive capacity to supervise AI, you're dead on arrival."
"Spec-driven development turns AI into a real co-pilot."
"Miss one dimension and you stall. Miss two and you suffer. Miss four and you fail."
"Stop embracing AI blindly. Start being aware."
---
🎯 READY TO CLOSE THE GAP?
Get your FREE AI-Readiness Assessment for your software team.
One number showing where you stand across 4 dimensions. Zero cost.
👉 https://brix.consulting/free-ai-readiness-assessment/
Hosted on Acast. See acast.com/privacy for more information.
By Michele Brissoni97% of enterprise developers use AI coding tools. Trust crashed from 40% to 29% in one year. METR found experienced developers 19% slower while believing they were 20% faster. The 39-point perception gap exposes why your AI investment isn't delivering—and the 4-dimension framework that fixes it.
🎙️ EP81 - The AI Readiness Assessment | The Last Mile to 4X Results with AI Coding Tools
You made the right investment. GitHub Copilot, Cursor, Claude Code—the tools work. But without readiness across 4 dimensions, AI amplifies dysfunction instead of excellence. This episode reveals the diagnostic framework and the pathway to turn your investment into exponential results.
---
In this episode, Michele (Mike) Brissoni exposes the AI-readiness gap costing CTOs millions: the delta between how fast organizations adopt AI and how prepared teams are to supervise it, validate it, and integrate it. He introduces the AI Readiness Assessment framework measuring organizational capacity across four critical dimensions, reveals why spec-driven development unlocks AI for experienced developers, and demonstrates how behavioral engineering—not more tools—closes the last AI-mile.
💡 KEY INSIGHTS:
- 97% of enterprise developers have used AI coding tools
- Trust in AI accuracy dropped from 40% to 29% in just one year
- 39-point perception gap: teams 19% slower while believing 20% faster
- Experienced developers find traditional AI coding tools distracting without proper workflows
- Spec-driven development expands AI's reach from 30% to full development lifecycle
- AI readiness gap = delta between adoption speed and organizational capacity
- The bottleneck is behavior, not infrastructure
- Four dimensions determine AI success: focus, technical practices, product health, customer feedback
- Miss one dimension and you stall, miss two and you suffer, miss four and you fail
- Companies with strong fundamentals see 4X better AI results than those without
- Elite XP teams correct mistakes in one week; canonical enterprises take a quarter
- AI becomes an expensive accelerator for your failure without readiness
🗣️ KEY QUOTES:
"They were 19% slower while believing they were 20% faster."
"AI amplifies what you have in the company."
"Driving a Ferrari Enzo at 200 mph with 45% brakes—that's your AI adoption gap."
"If developers don't have the cognitive capacity to supervise AI, you're dead on arrival."
"Spec-driven development turns AI into a real co-pilot."
"Miss one dimension and you stall. Miss two and you suffer. Miss four and you fail."
"Stop embracing AI blindly. Start being aware."
---
🎯 READY TO CLOSE THE GAP?
Get your FREE AI-Readiness Assessment for your software team.
One number showing where you stand across 4 dimensions. Zero cost.
👉 https://brix.consulting/free-ai-readiness-assessment/
Hosted on Acast. See acast.com/privacy for more information.