We Flattened The Org And All I Got Was 50 Direct Reports - Monthly News Update
Wed Jan 28 2026
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Layoffs, chips, and a lobster-shaped lesson in security—this month’s news run is a tour of how tech’s biggest bets collide with real-world constraints. We start with Amazon’s plan to complete 30,000 job cuts under the banner of “flattening the org.” That might clean up charts, but it also stretches managers thin and risks slowing the very decisions teams need to ship. The human cost is harder to quantify than a balance sheet win, and we unpack where productivity gains end and morale debt begins.
From there, we get into Microsoft’s Maya 200 inference chip and why efficiency is the story to watch. Performance per dollar, power budgets, and inference at scale matter more than leaderboard sprints. If the claims hold up outside marketing decks, Maya points to a future where better throughput and lower costs beat raw hype. We also dive into Satya Nadella’s push to retire “AI slop” and think of these systems as scaffolding for human potential—useful framing for knowledge work, but incomplete for roles where augmentation often previews automation. It’s the tension shaping careers, budgets, and product choices across the stack.
We pivot to enterprise infrastructure with Nutanix’s slower-than-expected VMware migrations. Even when customers want options, they face real friction: tooling parity, skill gaps, data gravity, and the risk of moving mission-critical workloads without bulletproof rollback. The lesson is pragmatic—platforms don’t win on promises, they win on migration paths that reduce toil and make costs predictable.
And then there’s Moltbot, the rebranded assistant formerly known as Clawdbot, which sparked a security backlash and a reminder that agents touching calendars, email, and payments need guardrails before cleverness. Limit scopes, sandbox actions, cap spend, log everything. AI that touches real life must be boringly safe before it’s impressive.
If this breakdown helped you cut through the noise, follow the show, share it with a friend, and leave a quick review. What story hit you hardest—and why?
Purchase Chris and Tim's book on AWS Cloud Networking: https://www.amazon.com/Certified-Advanced-Networking-Certification-certification/dp/1835080839/
Check out the Monthly Cloud Networking News
https://docs.google.com/document/d/1fkBWCGwXDUX9OfZ9_MvSVup8tJJzJeqrauaE6VPT2b0/
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Send us a text Layoffs, chips, and a lobster-shaped lesson in security—this month’s news run is a tour of how tech’s biggest bets collide with real-world constraints. We start with Amazon’s plan to complete 30,000 job cuts under the banner of “flattening the org.” That might clean up charts, but it also stretches managers thin and risks slowing the very decisions teams need to ship. The human cost is harder to quantify than a balance sheet win, and we unpack where productivity gains end and morale debt begins. From there, we get into Microsoft’s Maya 200 inference chip and why efficiency is the story to watch. Performance per dollar, power budgets, and inference at scale matter more than leaderboard sprints. If the claims hold up outside marketing decks, Maya points to a future where better throughput and lower costs beat raw hype. We also dive into Satya Nadella’s push to retire “AI slop” and think of these systems as scaffolding for human potential—useful framing for knowledge work, but incomplete for roles where augmentation often previews automation. It’s the tension shaping careers, budgets, and product choices across the stack. We pivot to enterprise infrastructure with Nutanix’s slower-than-expected VMware migrations. Even when customers want options, they face real friction: tooling parity, skill gaps, data gravity, and the risk of moving mission-critical workloads without bulletproof rollback. The lesson is pragmatic—platforms don’t win on promises, they win on migration paths that reduce toil and make costs predictable. And then there’s Moltbot, the rebranded assistant formerly known as Clawdbot, which sparked a security backlash and a reminder that agents touching calendars, email, and payments need guardrails before cleverness. Limit scopes, sandbox actions, cap spend, log everything. AI that touches real life must be boringly safe before it’s impressive. If this breakdown helped you cut through the noise, follow the show, share it with a friend, and leave a quick review. What story hit you hardest—and why? Purchase Chris and Tim's book on AWS Cloud Networking: https://www.amazon.com/Certified-Advanced-Networking-Certification-certification/dp/1835080839/ Check out the Monthly Cloud Networking News https://docs.google.com/document/d/1fkBWCGwXDUX9OfZ9_MvSVup8tJJzJeqrauaE6VPT2b0/ Visit our website and subscribe: https://www.cables2clouds.com/ Follow us on BlueSky: https://bsky.app/profile/cables2clouds.com Follow us on YouTube: https://www.youtube.com/@cables2clouds/ Follow us on TikTok: https://www.tiktok.com/@cables2clouds Merch Store: https://store.cables2clouds.com/ Join the Discord Study group: https://artofneteng.com/iaatj