OhMyself

Jack's notes on AI, software, and the industry around them.

Page 2

21 posts

Older posts

Posts 11–20

  1. Why ChatGPT Can Feel Less Capable: What to Check

    When ChatGPT feels less capable, check model selection, reasoning effort, context, and repeatable results before treating a bad answer as a hidden downgrade.

    AI, OpenAI

  2. GPT Image 2.5: Flare, Sunburst, and 12 Prompts

    Explore GPT Image 2.5 Flare and Sunburst, with 12 reusable prompts, eight generated examples, and a practical look at speed, image quality, and editing.

    AI, Image Generation

  3. AI Workflows: How to Choose Models and Agents

    A practical AI workflows guide for choosing models, designing agents, controlling costs, and evaluating real work without trusting benchmarks alone.

    AI, AI Agents, Model Evaluation, Codex

  4. GPT-5.6 Sol vs. Terra vs. Luna: Which Should You Use?

    Fresh CodexRadar data shows when GPT-5.6 Sol, Terra, or Luna makes sense, separating repeatable task coverage from latest-run cost and speed.

    AI, Codex, GPT-5.6, Model Evaluation

  5. DeepSeek V4 Flash + GPT-5.6 Luna: A $0.42 Sol Alternative?

    DeepSeek V4 Flash and GPT-5.6 Luna theoretically match Sol xhigh's coverage for about $0.42, but only if a verifier can identify the correct patch.

    AI, Codex, Model Evaluation

  6. How to Use GPT-5.6 Luna Max as a Codex Subagent

    GPT-5.6 Luna is now 80% cheaper in the OpenAI API, making Luna Max practical for bounded Codex subagent tasks while Sol handles planning and review.

    AI, Codex, AI Agents

  7. GPT-5.6 Sol Max vs. xhigh: Why Max Isn't My Default

    GPT-5.6 Sol passed fewer repository tasks at max than xhigh while costing 46% more. This benchmark maps the full Codex effort curve across 112 tasks.

    AI, Codex, Model Evaluation, Performance

  8. GPT-5.6 Juice Values for Sol, Terra, and Luna

    Personal GPT-5.6 Juice value observations for Sol, Terra, and Luna across reasoning effort levels in Codex, plus prompts used to reproduce them.

    AI, GPT-5.6, Model Evaluation

  9. How to Build a Custom LLM Evaluation You Can Trust

    Build a custom LLM evaluation with hidden tests, mechanical scoring, blind review, and checks for variance, leakage, and framework confounders.

    AI, Model Evaluation

  10. Astro Blog SEO Audit: What Actually Mattered

    An Astro blog SEO audit uncovered missing social cards, 12 MB of images, inconsistent canonical URLs, and weak archive and tag discovery.

    SEO, Performance