Agile didn’t get the engineering wrong. Enterprises often implemented Agile management more completely than Agile engineering. AI gives us an opportunity to close that gap.
Zombie GenAI PoCs. No clear vision. Endless "Wack-a-Mole" problems.
You don’t need another demo. You need a roadmap.
Start with a 60-minute GenAI readiness scan: https://t.co/L22vOUG7AE
Your GenAI plan is broken if:
– Teams define GenAI differently
– Leaders chase random use cases
– The vision doesn’t guide decisions
– Stakeholders ignore it
– You never update it
A real “Vision to Win” aligns, excites, and adapts.
https://t.co/95TdPcXqyp
Most GenAI projects fail to scale.
Not because of the tech-but due to missing strategy, alignment, and clear goals.
Zombie PoCs, black-box models, and endless “Wack-a-Mole”
Link: https://t.co/L22vOUG7AE
Your GenAI strategy is broken if:
– Leaders disagree on what GenAI means
– Teams run unaligned pilots
– Your goals sound like jargon
– Execs don’t believe the pitch
– Your plan hasn’t changed in a year
Fix it, now.
https://t.co/95TdPcXqyp
Most teams aren’t ready for GenAI.
They run endless pilots, but nothing goes live.
They chase tools, not strategy.
They have no clear goals, no real outcomes.
Fix it in 60 minutes: https://t.co/L22vOUG7AE
Most GenAI projects fail before they start.
Why?
No clear vision. No team alignment. No shared urgency.
A one-page "Vision to Win" can fix that fast.
Start there—or keep spinning in circles.
https://t.co/95TdPcXqyp
Most GenAI projects fail before they start.
Why?
No clear strategy. No real alignment. Too many dead-end pilots.
Use this 60-minute GenAI readiness check to spot the gaps and fix them fast: https://t.co/L22vOUG7AE
Your GenAI strategy won’t work without a clear vision.
Most teams skip this and chase random pilots.
The result? Confusion, low impact, wasted budget.
Define a measurable GenAI “North Star” that guides every decision.
https://t.co/95TdPcXqyp
Most GenAI projects fail before they start.
Why? No strategy. No alignment. Just demos.
Thousands of PoCs. Zero business impact.
Run a GenAI readiness check before you waste time: https://t.co/L22vOUG7AE
AI-first teams don’t deliver from stories—they deliver from behavioral contracts (Gherkin), scoped decisions (ADRs), and running code. User stories help explore ideas, but working software speaks louder.
→ Stories helped us understand users.
But shipping reliable AI-era software? That takes executable truth.
Shift from conversation to confirmation.
Demote stories.
Test everything.
Trust evidence.
In AI-first development (AI-DLC), user stories no longer drive delivery.
Gherkin defines behavior, ADRs guide design, and pipelines prove progress.
Executable evidence—not stories—controls execution.
Stories help align, but delivery runs on green pipelines.