3 AI stories explainx.ai reported on April 22, 2026, ranked by reader interest and grouped by topic. Each links to the full write-up with sources.
The product story is 'precision and iteration'; the platform story is gpt-image-2 on the Image and Responses APIs with flexible sizes and quality tiers. Here is a concise map of what OpenAI published and where to read the current limits.
Stanford HAI’s AI Index and HAI’s own “12 takeaways” article, read alongside IEEE Spectrum’s “12 Graphs That Explain the State of AI in 2026”—with attributed stats, Perrault-on-benchmarks color, and explainx.ai’s take for developers.
A one-day pricing-page shift put Claude Code next to $100 Max plans, drew a sharp transparency backlash, and was rolled back by evening. Anthropic said it was a 2% new-signup experiment with no change for existing customers; Pro keeps Claude Code again. The same week, competitors highlighted their own clarity—another reminder to treat frontier tools as a budget line, not a fixed utility.
“Aligned” is not a vibe from a good chat. It is a design problem: what we specify, what the system optimizes for, and what actually happens in the world can drift apart. Here is a complete map of that space for people shipping agents and tools.
A readable blog-style take on Hermes: what problem it solves, how the pieces fit together (CLI, gateway, memory, skills, cron), how builders route frontier vs budget models, and what a typical remote setup looks like—with links to official sources.
Context length is the cap on 'how much the model can read at once,' not the same as how many parameters it has. This guide defines the window, input vs max output, long-context tradeoffs, and what Anthropic, OpenAI, Google, and Meta publish today.
Bigger is not a synonym for smarter, but parameter count is still the first axis people use to compare scale. This guide explains what parameters are, how mixture-of-experts changes the math, and which flagship models still publish size—and which do not.
If you have ever seen
Founder-mode review that asks what product is really being built, not just what feature was requested. Supports scope expansion, selective expansion, hold-scope, and scope-reduction modes.
Engineering-manager style review that hardens the plan around architecture, boundaries, state transitions, edge cases, tests, and diagrams before coding starts.
Interactive design-plan review that scores design quality, identifies unresolved UX issues, and improves the plan before anyone ships UI.
DevEx review for developer-facing products. It explores personas, benchmarks onboarding, and scores friction across APIs, CLIs, SDKs, libraries, docs, and platform flows.
Lets users tune how often gstack asks certain planning questions and inspect the psychographic/developer profile inferred from prior interactions.
Design system creation workflow that researches comparable products, proposes an aesthetic system, and writes `DESIGN.md` as the canonical design source of truth.
Get each day's AI news in your feed reader: daily RSS · every post
