Fluixo
@fluixoo • 4,582 subscribers
Marketing & AI | Founder @firsayai & @0penoffers | BD @frameonx | Building @PlayTerra_ | Amb @1inch
Videos
I BUILT A ROBINHOOD CHAIN TOOL THAT MAKES MY AI CHECK THE POOL BEFORE IT TALKS ABOUT MY BAG Meet TRENCH. Give an MCP-compatible agent a token address and a USD position size: → reads public Robinhood Chain pools through DexScreener → checks the chain and latest block through RPC → selects the highest-liquidity observed pool → models how your position size presses against estimated depth → returns a DEEP / THIN / CRITICAL grade, the reason and the assumptions → lets your agent explain the evidence A token can have the same price, the same chart and the same pool - and still be a very different problem at $500 versus $5,000. That's the part I wanted the agent to calculate instead of hand-wave. The loop is: TOKEN + SIZE → PUBLIC DATA → PRESSURE MODEL → AGENT EXPLANATION Five read-only MCP tools. Open source. A browser playground you can try without installing anything. The browser uses manual inputs. The MCP server is where live token data comes in. Neither is an executable sell quote. No private key. No wallet signing. No trade execution. The axolotl can look cute. The assumptions still have to be visible. CHECK THE DEPTH. THEN ASK THE AI. GitHub walkthrough attached. Repo in the first reply ↓
Fluixo49,840 görüntüleme • 1 ay önce
A $170 AI bill in 10 days is not a cloud problem. It is a routing problem. Most devs send every task to the most expensive brain available. summaries small refactors docs scripts log parsing boilerplate That is how the bill gets stupid. The Mac Mini M4 trade is simple: run routine work locally keep private code on your desk pay once for hardware save frontier models for hard calls Local AI does not beat Claude at everything. It does not need to. It only needs to replace the boring prompts that never needed a frontier model in the first place. Cloud AI stays. The default route changes. Full breakdown below ↓
Fluixo35,295 görüntüleme • 2 ay önce
The humanoid race is not about robots. It is about collecting physical data. Today they move boxes. Tomorrow they assemble cars, repair machines and work beside humans. Every warehouse shift is another dataset. Every failed grasp is another training example. The companies that collect the most real-world physical data today will build the smartest robots tomorrow.
Fluixo39,997 görüntüleme • 3 ay önce
MOST PEOPLE BUY THE PRINTER BEFORE THEY FIND THE BUYER. That is why most 3D printing businesses die as a desk toy. The machine is not the moat. The moat is: the finishing work nobody wants the part needed in 24 hours the material nobody local stocks the file that ships before the object the business customer who orders again Same printer. Same plastic. Completely different business. Consumer trinkets compete with every Etsy seller on earth. B2B parts, measurements, fixtures, repairs and repeat orders compete with waiting, downtime and inconvenience. That is where the money is. The printer gets the headline. The system around it gets paid. Full breakdown below ↓
Fluixo24,047 görüntüleme • 2 ay önce
Codex is not just a coding agent anymore. It is becoming a skill-based operating system. Most people still ask it to “build the app”. Better builders give it specialised skills: frontend design browser automation market research lead research Figma implementation copywriting customer research cold email content strategy That is the real shift. One agent with no skills guesses. One agent with the right skills follows a process. The next advantage is not who writes the longest prompt. It is who builds the best toolbelt around the agent. Stop starting every task from zero. Give Codex the skills for the job. Bookmark this before you ask a general agent to do specialist work again.
Fluixo26,556 görüntüleme • 4 ay önce
Most people use Claude to get answers. That is why they forget everything a week later. Real learning is not answers. It is a system: - map the skill - find the 20% - study in sessions - get tested - expose weak spots - compress into one page - explain it back simply Claude should not be your shortcut. It should be your teacher, examiner, curator, and feedback loop. Ask it to quiz you until the gaps show. Ask it to re-teach only what you missed. Ask it to turn messy notes into a path. The best learners are not collecting more resources. They are building tighter loops. Bookmark this before you ask Claude to “explain this” again.
Fluixo26,165 görüntüleme • 4 ay önce
MOST PEOPLE DO NOT HAVE A SUBSCRIPTION PROBLEM. They have a default-price problem. $20 here. $12 there. $10 for a tool used twice a month. Another $23 because cancelling feels annoying. The trap is thinking the sticker price is the real price. It usually is not. Audit the stack. Cancel what does not pay back. Move real tools annual. Use student/education pricing if you qualify. Replace lazy subscriptions with free tools when the output is the same. The win is not “pay $0 for everything.” The win is knowing which tools deserve your card at all. Full breakdown below ↓
Fluixo15,063 görüntüleme • 2 ay önce
Most people use Claude Code like a chatbot. That is the mistake. The real power is not in better prompts. It is in controlling the session. /init gives the project memory. /memory keeps the rules alive. /clear removes old context. /compact saves the important parts. /context shows where the tokens go. /rewind fixes bad turns. /plan stops blind edits. /model matches the brain to the task. Claude Code gets 10x better when you stop letting the conversation run itself. Memory. Context. Boundaries. Rollback. Planning. That is the system. Stop asking Claude Code to “just do it”. Teach it what to remember, what to forget, and when to stop. Bookmark this before your next session turns into 40 messages of context debt.
Fluixo19,226 görüntüleme • 4 ay önce
Most AI agents do not fail because the prompt is weak. They fail because there is no loop around the prompt. A real loop: - Finds work - Executes - Verifies - Saves state - Stops or escalates If an agent can say “done” without tests, a budget cap and an independent verifier, you built a demo. Prompts make you the operator. Loops make the agent useful while you are offline.
Fluixo16,419 görüntüleme • 3 ay önce
AI animation is not one prompt. It is a factory. Most people try to generate one impressive clip. The real money is in the pipeline: script character sheet scene frames motion voice cast music publishing Claude writes the structure. Midjourney builds the frames. Runway adds motion. ElevenLabs gives the characters a voice. Suno scores the scene. Make moves the files while you sleep. The point is not to replace a studio. The point is to turn one creative direction into repeatable output. One animation is content. A pipeline is leverage. Bookmark this before you spend another week making one beautiful clip with no system behind it.
Fluixo18,074 görüntüleme • 4 ay önce
MOST PEOPLE BUILD AI AGENTS BACKWARDS. They start with prompts, then add tools, memory, subagents, dashboards, and a graph nobody can debug. Then they wonder why the agent is expensive, confused, and unreliable. The better order is simple: harness first loop second graph only when needed A harness gives the model a workspace, tools, permissions, logs, and a definition of done. A loop lets it try, fail, read feedback, repair, and stop. A graph only makes sense when the workflow branches: approvals, parallel work, durable state, different routes, restart recovery. A graph is not a smarter prompt. A loop is not a production system. A harness is not just a system prompt. Most agents do not fail because the model is weak. They fail because nobody defined what success means.
Fluixo12,244 görüntüleme • 3 ay önce
You do not need a CS degree to become an AI engineer. You need the map. Tokens. APIs. Python. Git. Context engineering. Structured outputs. RAG. Vector databases. Agents. Tool use. Evals. Cost control. Security. Shipping. That is the real curriculum. Not conference words. Not ML theory cosplay. Not pretending you need a PhD before building anything. The people getting hired are not the ones who memorised all 36 concepts. They are the ones who learned enough to ship 3 real projects and explain the tradeoffs. AI engineering in 2026 is not about knowing everything. It is about building systems that survive outside the demo. Bookmark this before you spend another year waiting for permission to start.
Fluixo14,539 görüntüleme • 4 ay önce
OpenAI just killed the idea of one best model. GPT-5.6 is three different jobs: - Sol for hard reasoning and long agent runs - Terra for everyday work - Luna for cheap high-volume tasks Most people will send every prompt to Sol, then complain about the cost. The edge is not having the flagship. It is knowing when you do not need it.
Fluixo12,641 görüntüleme • 3 ay önce
Most builders do not need a paid domain for every idea. They need a real URL fast. A side project should not ask for a subscription before it has one user. The $0 stack: - free domain - Cloudflare DNS - free SSL - GitHub Pages - Vercel - Netlify - Cloudflare Pages That is enough for MVPs, demos, portfolios, and weekend experiments. Buy the .com when it becomes a real brand. Until then, stop letting tiny bills kill unfinished ideas. Bookmark this before another project dies on localhost.
Fluixo12,542 görüntüleme • 4 ay önce
Daha fazla içerik yok.