"This book may seem like an ambitious goal in the face of exponential change.... But despite all the change, as programmers we often find ourselves doing many of the same kinds of things we’ve always done..."
—Vibe Coding by Gene Kim and Steve Yegge
The orgs that win aren't moving fastest. They invested early in resilience, automation, and observability—and built the infrastructure that makes sustainable speed possible.
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Capital One was an early cloud-first bank. Security maturity didn't keep pace. 100M+ people's data was exposed. Speed without safety infrastructure isn't competitive advantage—it's a countdown clock.
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Dr. Suzette Johnson and Dr. Robin Yeman have led AI transformation across 150+ defense and aerospace programs. On March 12, they bring that roadmap to a free virtual session on sustainable AI adoption. Register now.
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"Move fast and break things" vs. "move fast and fix things." One is a liability. The other is what observability, automation, and testing actually make possible.
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Where an org sits on the faster-cheaper-safer triangle should change as context changes. The problem is when it shifts—due to market pressure, AI hype, funding—without anyone noticing or deciding.
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Building resilience without validating it is the worst of both worlds—the cost without the protection. Chaos engineering and game-day testing aren't optional. They're what make a resilience program real.
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Aviation learned it hard: underinvesting in safety costs more than the savings. Safer, cheaper, faster—in that order. Every industry has its version of this reckoning eventually.
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Well said!
When every trade-off escalates to the C-suite, speed suffers. Push faster-cheaper-safer decisions to the teams with actual context. The GM model—and it works.
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AI compresses timelines. FOMO budgets unlock fast. Safety gets deferred. Then scale hits and costs become prohibitive. The AI multiplier effect makes the faster/cheaper/safer framework more critical, not less.
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The OODA loop—observe, orient, decide, act—isn't just military strategy. Elite engineering orgs use tight feedback loops to move fast without breaking things. Raw velocity isn't the goal. Learning speed is.
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Preordering Hyperadaptive gives individual leaders early access to frameworks, the AI Integration Handbook, the author's Substack community, and the Hyperadaptive™ Model PDF — a $278 value for preordering a single copy.
Cars bricked. Towed to dealerships. That's what happened to automakers who underinvested in OTA upgrade safety. The cheap path turned out to be the expensive one—every time.
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Snowflake's data gravity. Dynatrace's observability fabric. Glean's enterprise knowledge graph. These aren't UI features—they're moats built on compliance, context, and complexity no prompt can replicate.
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BMW replaced $500K physical crash tests with virtual simulations connected to CI/CD pipelines. Safety investment became their speed advantage. That's the pattern elite orgs follow.
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Speed vs. safety is a false trade-off. The real question: which two of faster, cheaper, and safer can your org optimize for right now—and is that choice being made explicitly?
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The SaaS era isn't dying. It's moving from systems of record to systems of execution. Winners buy commodity infrastructure and build only what truly differentiates them. Stephen Fishman makes the case.
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"Move fast and break things" sounds bold. The orgs that sustain speed invest in safety first. Capital One's 2019 breach exposed 100M+ customers. Moving fast without infrastructure isn't an advantage—it's a countdown.
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Project trackers and Kanban boards are highly vulnerable to vibe coding clones. Systems of record, data gravity platforms, and infrastructure players? The competitive calculus is very different. Here's why.
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The Complexity Tax consumes up to 40% of IT budgets. Vibe coding makes it cheaper to start. It does nothing about the 70–85% of TCO that accumulates after launch. Stephen Fishman has the receipts.
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AI doesn't fail because of the technology. It fails because people, workflows, and culture aren't aligned around it. Dr. Suzette Johnson and Dr. Robin Yeman tackle this head-on in a webinar on March 12.
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WiseTech Global manages customs clearance across 193 countries for 47 of the top 50 global logistics providers. Replacing it with AI-generated code means recreating thousands of regulatory integrations. Good luck.
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Cox Automotive's ecosystem drives 60% of automotive shoppers to start their journey there. 5.1 trillion vehicle insights. A flywheel no vibe-coded startup can replicate. Stephen Fishman explains why.
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Gartner data: SaaS deployments are 4–6x faster than custom builds. A prompt can generate a function. It can't automate SOC2 compliance, security patching, or multi-endpoint maintenance. Read the full breakdown.
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Coauthor Heidi Waterhouse joins Whitney and Coté on Software Defined to discuss Progressive Delivery — covering the 4 A's framework, coerced consent, why teams design for peers not users, and how to close the feedback loop in DevOps.
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Not all SaaS moats are equal. Stephen Fishman's "Foundational Resistance" spectrum ranks platforms from infrastructure (zero vulnerability) to systems of engagement (high). Where does your stack land?
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You cannot prompt your way into a 25-year-old global CDN. Akamai's edge network runs AI models at triple the throughput of centralized clouds. Infrastructure moats are physical—and they're unbreachable.
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Roles are fusing and fissioning like nuclear reactions. We don't yet have names for many resulting bundles of work. The comfortable middle where you could code competently without extreme specialization? Gone. Choose: specialize, hybridize, or commoditize.
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Have you preordered Hyperadaptive, by Melissa M. Reeve? Unlock exclusive resources today!
▪️AI Integration Handbook
▪️Substack Community Access
▪️Hyperadaptive Model PDF
...and more!
More info: itrev.io/3Mho16S
