In partnership with
Hello, Human Guide
Today, we will talk about these THREE stories:
A viral prediction that 99% of jobs could disappear by 2027
Why agentic engineering may quietly replace software developers
How the U.S. government is deploying AI at a scale nobody voted on
Ship the message as fast as you think
Founders spend too much time drafting the same kinds of messages. Wispr Flow turns spoken thinking into final-draft writing so you can record investor updates, product briefs, and run-of-the-mill status notes by voice. Use saved snippets for recurring intros, insert calendar links by voice, and keep comms consistent across the team. It preserves your tone, fixes punctuation, and formats lists so you send confident messages fast. Works on Mac, Windows, and iPhone. Try Wispr Flow for founders.
“99% of Jobs Could Vanish” And Nobody Has a Backup Plan
The number landed like a punch, not a forecast.
A widely shared claim from an AI researcher argues that up to 99% of current jobs could be automated by 2027, with only a handful of roles AI oversight, human care, and system control remaining. The prediction spread fast across tech media, amplified by recent data showing generative AI adoption jumping past 77.55% of large enterprises in under two years, according to multiple industry surveys.
What stands out is not whether the number is exactly right. What bothers me is how little disagreement there is about the direction. Late at night, scrolling job boards on a glowing phone, you can already feel roles thinning out tasks disappearing first, titles next. This is less about robots stealing jobs and more about software quietly deleting the middle layers of work.
If even half this prediction materializes, education systems, labor laws, and safety nets snap under pressure. Everything else gets cut.
If jobs disappear faster than new ones form, the real question is who absorbs the shock before the math catches up.
Agentic Engineering Is Replacing Coders Without Saying Their Names
The shift is already happening, just not in job titles yet.
The term “agentic engineering,” popularized by Andrej Karpathy, describes a move from humans writing code to AI systems that plan, write, test, and deploy software end-to-end. Instead of prompting, engineers supervise fleets of agents that call tools, fix errors, and rerun themselves, cutting development time by 60–80% in early enterprise pilots reported by internal teams.
What struck me is how unromantic this feels. No sci-fi moment just dashboards refreshing at 9 a.m., fewer pull requests, and codebases growing while human input shrinks. This is less about better code and more about removing the need for constant human judgment in the loop.
Once software builds itself, the bottleneck is no longer talent but permission. Speed compounds.
If AI can already ship features while teams sleep, the real question is how long “software engineer” stays a human default.
The U.S. Government Is Quietly Turning Into an AI Super-User
This rollout is bigger than most product launches.
Across federal agencies, AI systems are being embedded into more than 1,300 workflows, spanning healthcare claims, tax audits, intelligence analysis, and law enforcement support. Internal documents show automation targets ranging from 15% to 40% efficiency gains per department, with procurement accelerated under national competitiveness mandates.
What stands out is how little public friction there’s been. These systems arrive like fluorescent lights turning on at 7 a.m. sudden, bright, and already assumed to be necessary. This is less about innovation and more about governance moving faster than consent, especially when models trained on civilian data start shaping state decisions.
Once infrastructure is in place, rolling it back is politically and technically painful.
If AI becomes the default operating layer of government, the real question is who audits the decisions when the screens say “approved.”
