The Inner Intelligence Era
The Observatory
Tracking the transition from software outward.
New AI capabilities are announced every week. It is much harder to see how those capabilities change what people do, how work is organized, how institutions respond, and how people experience it. The Observatory collects quantitative and qualitative evidence on those changes, one domain at a time.
It starts with software engineering. Software is one of the first fields where machine-produced work shows up at scale, and it is the one I know best. Other domains will be added when there is enough evidence to say something honest about them.
What the Observatory tracks
Capability
What can AI systems actually do?
Behavior
How are people changing how they work?
Work
How are tasks, skills, roles, and organizations changing?
Economics
What is becoming abundant, and what is becoming scarce?
Institutions
How are education, government, defense, healthcare, regulation, and other systems responding?
Humans
What is happening to identity, ambition, creativity, relationships, responsibility, and purpose?
Domains
Software Is Changing First
The Observatory's first case study follows how AI capabilities in software engineering turn into changes in how engineers work, how teams are organized, and what skills are valued.
Possible future domainsEducation · Labor · Arts and writing · Finance · Healthcare · Legal · Defense and high-consequence systems · Blue-collar work and the trades · Organizations and management
Principles
- No invented data. Empty means empty. A signal is published only when there is public evidence behind it.
- Sources are always shown. Every signal links to where it came from, so an outsider could rebuild it.
- Confidence is stated. Signals carry a confidence level, and competing signals are shown together.
- History is kept. Revisions are dated and earlier readings stay available, so the record shows how understanding changed.