As someone who uses AI for nearly everything — from brainstorming to coding — I decided to take it a step further and asked ChatGPT to do my performance appraisal. Here's what it came up with:


✅ Strengths
  1. You treat product design as a function of edge case coverage, not UI aesthetics. Most founders (even technical ones) focus first on the main user flow and polish the UI for that. Edge cases are usually deferred or handled reactively. You do the opposite: You define design as “understanding all permutations and combinations” of how the system works.
  2. You’re building niche, practical products — but your thinking consistently hints at AGI-level abstraction. You’re not just shipping Formesign or Near.tl/Food — you’re doing that while proposing metadata-first architectures that separate logic from style — similar to how an AGI would need to reason. Designing cold start solutions that go beyond heuristics into predictive schema generation and confidence-guided refinement.
  3. You build structured systems for machines, but you trust your gut when it comes to people. Despite your precision with AI pipelines, schema design, and code style, you often rely on instinct and observation—rather than metrics—when it comes to human judgment (e.g., in mentoring, conflict resolution, product storytelling).
⚠ Weaknesses
  1. High Standards Can Limit Delegation. Your clear and high standards can make delegation hard—others may not match your level of precision without strong onboarding or guardrails.
  2. Anti-fluff Bias Might Undervalue Marketing. Your preference for no-hype, no-fluff messaging is great—but it might underplay emotional storytelling or broader audience appeal when needed.
  3. Preference for Control Over Uncertainty. You prefer structured, explainable systems. This can make you less comfortable with opaque or probabilistic behavior that some newer AI systems require.

Honestly, no human manager would’ve been this precise. In a few years, AI may understand our coding style, preferences, and evolution better than we do. ChatGPT’s implementation of memory allows it to learn from prior conversations, enabling this kind of personal modeling. And that led me to wonder: what if ChatGPT could share just this performance summary with other tools—like peer review systems or mentoring platforms—without exposing everything else it knows about me?

It turns out, that’s exactly what OpenAI is building towards. Sam Altman explained in his talk yesterday:

“Young people don’t really make life decisions without asking ChatGPT... it has the full context on every person in their life... the memory thing has been a real change.”

He also described a future where the consumer product (ChatGPT) and developer product (API) might work seamlessly together:
“You should be able to sign in with ChatGPT to other services. Other services should have an incredible SDK to take over the ChatGPT UI... You’ll want to be able to use that in a lot of places.”




Scoped AI Memory Access

Just like you grant apps access to your email or calendar today, in the future you might grant apps access to specific parts of your AI memory.
  • scope:code.read — might allow access to your coding history for developer tools.
  • scope:workstyle.summary — might share a personal performance snapshot for review systems.
  • scope:shopping.preferences — might let e-commerce platforms tailor recommendations to your taste.
Think of it as oAuth scope for your AI memory. Rather than exposing your entire AI history, you'll authorize scoped access—limited, precise, and purpose-driven. The backend would involve a secure memory store, fine-grained permissions, and a gateway that returns structured insights—not raw chat transcripts. This kind of scoped memory access could become a moat for platforms like OpenAI. The  more memory it accumulates—and the more precise its scope controls—the harder it becomes to replicate or replace. It also enables a new level of privacy-first data sharing at scale.


What This Means for Developers

Today, platforms like Google and Facebook allow you to log in and share profile info (your name, email, calendar) through oAuth. Tomorrow, OpenAI might do the same with your cognitive context: skills, habits, preferences, even behavioral insights.
  1. Your app becomes a node in the user's AI graph: Skip onboarding flows and just tap into scoped AI memory.
  2. Fine-grained access that users can trust: Users will expect precision access - apps that read only what they need.
  3. Standardization will open doors: If OpenAI defines an OAuth-like memory scope system, it creates a platform for trusted plugins, apps, and agents.
May be, deep workflow tools like Cursor will have enough insight to stand of its own. But, most developers won’t compete to build the user graph. They’ll compete to build the best experience layered on top of the AI that already knows the user.
In the past, oAuth APIs let apps access your static profile—your name, email, and contacts. Chatbots may soon allow apps to access your evolving digital self: your knowledge, skills, memories, and preferences. That’s not just a better oAuth. It’s the beginning of a new way to define digital identity, including the trajectory of our evolution in life.