Create Three Spec Files Before Using Claude Code and Codex
I spent a year getting wildly inconsistent results from Claude Code and Codex. Three spec files, each with a distinct role, fixed it.
Anthropic, OpenAI, Google, and other AI platform deep dives.
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I spent a year getting wildly inconsistent results from Claude Code and Codex. Three spec files, each with a distinct role, fixed it.
Subscribing puts you in the top 0.3%. These five configurations — agents, teams, MCP, monitoring, automation — push you into the top 0.01%.
I classified every term I kept encountering while using Claude Code and Codex daily. Five groups emerged, and they map the entire system these tools run on.
I dug into SDK type definitions and system prompts for both tools. The 29 vs 7 gap isn't about feature count. It's about two fundamentally different answers to the same question: how should an AI coding agent interact with your system?
I reverse-engineered how Codex handles context overflow compared to Claude Code. The answer involves AES encryption, session handover patterns, and KV cache tricks.
A race condition between Auto Memory and context compaction in Claude Code v2.1.59–v2.1.61 broke prompt caching and corrupted sessions. Anthropic reset all weekly limits as compensation.
I couldn't sleep after a conversation about shipping more work publicly, so I built frouter at 3am. It pings free AI models in real-time and wires them into your coding tools with one keystroke.
Three companies updated their coding agents at the same time. The directions overlap. The real battleground isn't models; it's how fast they absorb developer workflows.
My API costs jumped 10x when the cache broke in production. The same day, Anthropic engineers explained exactly why.
From Cloudflare and Vercel's Markdown for Agents to Google's WebMCP, reading and writing are being standardized simultaneously, ushering in the Agent-Native Web era.
Korea-exclusive KakaoTalk promotion offers ChatGPT Pro at 29,000 KRW instead of $220/month, plus the new Codex-5.3-Spark delivers 1,000 tokens per second.
Peter Steinberger joining OpenAI isn't just a talent grab. It signals the dawn of AI-native messengers that could redefine how we communicate.
OpenAI's Codex team built a 1M-line codebase using only AI agents. Here are the five harness engineering principles they discovered along the way.
Opus 4.6 Fast mode costs $150/output tokens. This isn't just pricing, it's the birth of a new economic divide where token access determines competitive advantage.
Meritech Capital's analysis of 100+ public software companies reveals a stark valuation gap between AI-executing and non-AI firms.
While the market warns of GPU overcapacity, OpenAI declares it needs even more compute. The real winner won't be whoever has the most power - it'll be whoever closes the gap between AI capability and actual user experience.
OpenAI and Google are racing to launch affordable AI plans while Chinese competitors shatter price floors. Here's why this moment is your best entry point.
Anthropic's Tariq Shihipar breaks down what it actually takes to build production-grade agents - from Bash-first tooling to file-system-driven context engineering.
Anthropic launches Cowork, an autonomous agent that reads, edits, and creates files on your local machine. Vibe coding meets vibe working.
Anthropic's Claude Opus 4.5 didn't just set new benchmarks. It proved that going all-in on text, code, and agents while competitors spread thin is the winning play.
Why $300B evaporated from SaaS stocks as ChatGPT and Claude race to become the AI app store - and what the 2008 mobile wars tell us about what comes next.
Anthropic's Claude in Excel reveals the gap between AI-augmented and AI-native - and why most startups building 'AI + X' products won't survive 2026.
Manus shared the hard-won lessons behind building production AI agents - from context rot to evaluation rethinking - in a joint presentation with LangChain.
Meta acquired Manus for $3.6 billion. The secret wasn't a bigger model - it was context engineering. Here's what most AI agents get wrong.
Meta acquired Chinese AI startup Manus for billions. This deal reveals a new reality: going global isn't a growth option - it's a survival strategy for every startup in the AI era.
A deep dive into Oh-My-OpenCode's multi-agent orchestration architecture - how programmatic context isolation, parallel execution, and evidence-based research are redefining what AI coding agents can do.
Opencode's open-source documentation doubles as an introductory guide to agent architecture. Here are the seven core concepts every developer should understand.