The Machines Will Do it All Themselves?
Challenges with Opus 4.7: Performance and Personality
The Impact of AI Memory on User Experience
Hallucinations and Contextual Errors in AI
Navigating AI's Memory and Contextual Conflicts
Consulting in the Age of AI: Myths and Realities
The Role of Human Orchestration in AI Solutions
Conclusion: The Future of Work with AI
The Role of AI in Job Replacement
Trust and Technology: The Human Element
The Future of Work: AI and Job Dynamics
Skill Development in the Age of AI
Navigating the AI Landscape: Opportunities and Challenges
Societal Fear and the Future of AI
Justin and Kellan dig into a frustrating few weeks with Opus 4.7 — the conversational personality has gotten worse, hallucinations are back, and memory files are creating their own problems. Then they pivot to the bigger picture: AI labs are signing massive consulting partnerships while LinkedIn keeps insisting "consulting is dead." Both can't be true, and the people in the middle of that gap are the ones who are going to matter.
The Drip:
- Opus 4.7 has been a step back for conversational and workflow-driven work — building code is fine, talking with the model is rough
- A guess at why: system prompt overhauls, an internal focus on uptime and security, and memory bloat that competes with your actual context
- Hallucinations are back at every encounter
Inside The Bottle:
- The "consulting is dead" narrative vs. Anthropic and OpenAI signing massive consulting partnerships in the same week
- Two categories of AI work: building stuff (momentum) and talking with AI (fragile)
- Why "self-service" never materializes the way the headlines promise — and why human orchestration is still the secret sauce
- Compute costs higher than entry-level employees, the broken career ladder, and the firms that haven't figured out the new on-ramp yet
- An IBM paper from the 70s and why "you can't hold a machine accountable" is going to matter
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