Crypto boy

Gonna be an important week for $BTC - Testing the 100W EMA - Testing the 200D EMA At the same time the entire week is packed with events: • US CPI (May 13) • US PPI (May 14) • Retail Sales (May 15) • Trump-Xi / China headlines (May 15-16) imo one soft inflation print or positive China headlines and we rip through those levels..

@Axel_bitblaze69 good work btw

@Axel_bitblaze69 how did u made this?

Story of Ethereum 💔 He was supposed to be king. the flippening was supposed to come. But the world kept moving… without him. Part 2 coming soon. $ETH

@Axel_bitblaze69 🙈

Claude has a 10-20 message limit per session before context degrades.. Anthropic literally recommends restarting after that.. but the problem is, every restart loses the branch, the commits you shipped, the files you touched, every dead end you already hit. you spend 20 mins re introducing the project before you can do any actual work. now there's one claude code plugin that solves this entirely. call once, paste, done. ▫️ Setup (1 minute) inside claude code, run: /plugin marketplace add willseltzer/claude-handoff /plugin install handoff that's it. plugin's installed. ▫️ The 3 commands /handoff:create — full handoff with everything /handoff:quick — minimal handoff for simple tasks /handoff:resume — pick up from an existing handoff in a new session end of session you call /handoff:create. it generates a HANDOFF.md with your full state. fresh window the next morning you call /handoff:resume.. claude reads the doc, checks if the repo drifted, summarizes, and keeps building. ▫️ what the handoff actually captures the goal.. what you were trying to do what's done, what's not failed approaches + WHY they failed (so the next session doesn't loop on them) key decisions with their rationale current state of what works, what's broken with file:line refs resume instructions with expected outcomes warnings (env vars, sandbox limits, anything weird) the failed approaches section is the most underrated part. "tried X, didn't work because Y" saves hours of next-session debugging. ▫️ the bonus part HANDOFF.md is plain markdown. agent-agnostic. you can hand it to codex, gemini, cursor, anything.. just say "read HANDOFF.md and continue the work" and they pick up where claude left off. imo this kills 90% of the memory MCPs people install. zero infra, zero cost, zero context preloaded into every fresh session.. just a clean handoff doc when you actually need one. repo: github.com/willseltzer/cl…

While AI is doing most of the heavy lifting in SPX, I checked how AI in crypto is doing And it’s… rough Most of these are down 30–50% while AI stocks are up triple digits in the same window There’s a clear gap here AI-linked companies are now a huge part of SPX (~45%) while in crypto the whole sector is barely even 1% Bittensor held up better than most but beyond that, nothing really stands out Curious if this changes or if decentralized AI just stays a narrative..

If you want to try GPT 5.5 without rebuilding your entire Claude Code setup, this is my starter pack Codex (where GPT 5.5 lives) is way more compatible with your existing stack than you realise.. simply install the app. ▫️Step 1.. port your CLAUDE.md to AGENTS.md codex reads AGENTS.md from your project root the same way claude code reads CLAUDE.md. just copy and rename to: cp CLAUDE.md AGENTS.md most of your context, coding standards, file structure rules, and "do not" lists transfer directly. might need to tweak a few claude-specific phrasings but the bulk works ▫️Step 2.. wire your existing MCPs Codex supports MCP natively. your existing MCP servers work without modification your .mcp.json or ~/.claude.json configs can be moved into ~/.codex/config.toml. format is slightly different but the same servers work priority MCPs to wire first > filesystem MCP for project files > memory MCP for cross session knowledge > context7 for up to date docs > github MCP for repo ops > whatever domain MCPs you use (tradingview, dune, etherscan, polymarket, etc) if these already work in claude code, they'll work in codex with maybe 5 mins of config reformatting ▫️Step 3.. port your skills claude code skills are just markdown files in ~/.claude/skills/. codex has its own equivalent. most skills you wrote can be dropped into codex with minor edits what transfers > system prompts work the same > tool calling syntax is slightly different but claude can rewrite skills for codex format if you ask > context loading rules transfer cleanly ▫️Step 4: .. set up routing this is the actual move. don't switch fully. run both side by side and route tasks based on what each is best at claude code (opus 4.7) is better at > long context work (1M context window) > production code quality (still wins SWE-Bench Pro) > complex reasoning over big codebases > mature MCP ecosystem while codex (GPT 5.5) is better at > speed (2x faster on most tasks) > token efficiency (3.5x lower output tokens) > cost on high volume work > agentic benchmarks > simple one shot tasks ▫️step 5.. transfer your memory if you've been using memory MCP in claude code, your memory db is just a local file. point codex at the same memory MCP server and your past notes, decisions, project context all carries over ~/.claude-mem/claude-mem.db same file works for both because they're both reading from the same MCP what i actually run now > claude code with opus 4.7 + my 16 MCP stack for everything serious > codex with GPT 5.5 in a second terminal for prototyping, simple refactors, anything that doesn't need deep reasoning > same MCPs wired into both > same memory state across both > same project files via filesystem MCP setup time start to finish: about 30 mins if you already have a working claude code stack.

Day 2 of running GPT 5.5 on real work. Few things worth sharing.. Prompt style needs to change: old habit was writing detailed step by step instructions. with GPT 5.5 that actually hurts. it tries too hard to follow every line and burns reasoning tokens reconciling things you didn't need. what works better is describing the outcome and letting the model figure out the path. less prompt engineering, more goal definition.. bad prompt: "write a blog post about AI coding assistants. 1500 words. include intro, 3 main sections, conclusion. use these subheadings. mention these tools..." good prompt: "write a blog post about AI coding assistants targeted at solo founders shipping their first SaaS. make it specific and useful, not generic." second one gives way better output. the model fills in the structure intelligently. prompts i actually used today that worked > The perfection loop ‘before answering, do three things: 1. define what a 10/10 expert response would look like 2. draft your response 3. grade your draft against the definition if below 10/10, revise and grade again. show me only the final version. my request: [task]’ this one alone improved my output quality on important tasks by a lot. takes 15 seconds extra but the response comes back already self-corrected. > The meeting digest i'm pasting a meeting transcript. produce: 1. 5 bullet summary of decisions made 2. action items as a table (who, what, due date) 3. open questions that did not get resolved 4. draft follow up email, professional tone do not invent details. only what was said. transcript: [paste] stopped manually summarizing my calls. takes 30 seconds now. > The research synthesiser research [topic] using the web. produce a structured 1500 word report with: - executive summary - 3-4 main findings with evidence - counter-arguments where applicable - inline citations for every claim - flag where evidence is weak instead of padding target audience: [who's reading this] GPT 5.5 actually moves across tools to do this. searches, reads, cross-references, comes back with a sourced report. it flags weak evidence instead of making things up. things i learned the hard way is, context window is genuinely useful at 1M. dumped 200 pages of meeting notes and asked it to find every decision i'd made about a specific project across 6 months. found 14 decisions, organized chronologically, with the reasoning. impossible on smaller context windows. multimodal works smoother than expected. uploaded 3 screenshots of a dashboard and asked it to recreate the layout in code. one shot. used to need a paragraph describing every element. it's not great at every task. tried generating a polished slide deck and the output was rough. claude opus still wins for that. for everything else I tried, GPT 5.5 handled it cleaner and faster. cost reality check API is 2x more expensive per token than GPT 5.4. but my chatgpt plus sub at $20 includes 3000 messages a week of GPT 5.5 thinking. for normal usage that's plenty. if you're an agent builder running heavy workflows, the API price doubling matters more. so yeah my learnings so far after using GPT 5.5 is stop writing prompts like instructions. start writing them like goals. the model is genuinely better at figuring out the path than i would be at describing every step.

@Axel_bitblaze69 which one is better

GPT 5.5 shipped. my timeline is screaming switch switch switch.. but i stopped scrolling and compared it myself. fresh sessions. same prompts. both models.. full side-by-side comparison between Opus 4.7 va GPT 5.5

If you're a full time Claude Code user, don't switch to Codex from scratch.. Use Claude Code itself to export your workflow and help you migrate everything into Codex: prompts, rules, MCPs, skills, shortcuts, and repo conventions.` Ask Claude: prompt it this: Help me move my entire Claude Code setup to Codex without losing how I work. Audit my current prompts, rules, MCPs, workflows, and conventions; map each one to the best Codex native equivalent; generate the skills/config/plugin structure I should use; and give me a reusable starter prompt so Codex feels like home on day one.

@Axel_bitblaze69 @eng_khairallah1 nice build Axel

This prompt engineering article is solid. but most of you will read it, save it, and never apply it. below is the same 6 elements i applied to a real trading prompt and it works so well. thanks @eng_khairallah1 > Role: you are a senior crypto trader with 10 years of experience in onchain analysis, funding rate arbitrage, and macro narrative trading. you write theses like alex krüger, not like chatgpt. > Context: my current positions are [paste from memory MCP]. my cash balance on binance is [X]. my risk tolerance is 2% per trade. i'm swing trading 3-7 day timeframes. > Task: build a full thesis on [ticker] using all connected MCPs (binance, dune, twitter, Tradingview, perplexity). not a generic overview. a tradeable thesis with entry, invalidation, and size. > Format: 4 sections. macro setup. onchain flow. technical setup. trade plan (entry, TP, SL, size). no more than 300 words total. > Constraints: no hedging language ("might", "could", "potentially"). take a side. if the thesis is weak, say "skip this ticker" and explain why. never suggest more than 3% of portfolio in one position. > Quality standard: the output should be specific enough that i can place the trade in under 60 seconds without asking follow-ups. if i'm asking follow-ups, the thesis failed. that's 6 elements. every trading prompt i run has them. the outputs are night and day vs the generic "analyze $SOL" prompt most people use save this as a skill. name it trade-thesis. trigger on any ticker.

@Axel_bitblaze69 how to install the MCPs u shared ?

@Axel_bitblaze69 crazy

> Be cursor > build the best coding IDE on earth > $20/month subscription > hit $100M ARR > gpu bills start to eat the business > openai acquisition talks fall apart > anthropic acquisition talks fall apart > elon texts at 3am > "nice cursor. be a shame if it needed 1M h100s" > SpaceXAI + colossus supercomputer > $60B acquisition option or $10B exit payment > cursor: yes > meanwhile you: still wondering if you should switch to claude code > the stack consolidates while you sleep

@Axel_bitblaze69 💯💯

Claude responses just haven’t been the same lately… not really what i switched from ChatGPT for now seeing how fast chatgpt is shipping new products every day, feels like it might be time to switch back and give it another shot ?