Max

@TheOvermanEthos Clever idea, but the incentives are backwards. Gyms rely on predictable revenue and low usage. Charging only when people don’t show up creates unstable cash flow, more churn, and friction at the worst moment. What works: reward attendance, not absence.

Most engineers are still treating AI like a "better Google Search." That’s the quickest way to become obsolete by Q4. The shift from Autocomplete to Agentic Workflows is where the 10x happens: > If you’re writing auth logic from scratch in 2026, you’re wasting your client’s money. > If your "Agent" can't run tests and fix its own bugs in the terminal, it's just a fancy chatbot. > The real skill isn't "Prompt Engineering" it's Context Engineering. Knowing exactly what documentation and state to feed the model so it doesn't hallucinate. I’m seeing teams ship entire MVPs in 48 hours because they stopped "coding" and started "orchestrating." What’s the one task you’re still doing manually that an agent should have taken over by now? 👇

Google's problem isn't a lack of models; it's the 'Innovator’s Dilemma.' They have a search monopoly to protect, which makes them play defense with safety rails and legacy integration. A decentralized 'hunger games' between 100 teams sounds great until you realize they’re all competing for the same internal data and approval from the same legal department.

Gemini 3.0 didn’t quite work out and most of us are still stuck with 2.5 Sometimes I don’t get it - what’s preventing Google from ditching all the side hustles and training 100 models from 100 teams in parallel Pick the model/team combination that produces a decent model! That way, they will at least stay in the AI race 😅

@sweatystartup Predicting the end of AI because of energy costs feels like predicting the end of the internet in 2000 because dial-up was too slow. The market doesn't plummet because things get expensive; it pivots to whoever solves the efficiency problem first.

The AI bubble will pop: Electricity will 2x in cost again over the next 24 months. AI companies will need to 5x prices to break even. Companies who depend on AI will see costs 5x and will be screwed. Users will vanish. Market will plummet.

Interesting theory, but the 'exclusive Azure' clause has always been the ticking time bomb in the MSFT/OpenAI relationship. If OpenAI is pivoting to a PBC, they have a fiduciary duty to scale, which is impossible if they’re locked into a single provider's margin. The real question isn't if Sam 'betrayed' Satya, but whether the original contract was even enforceable once the scale hit the hundreds of billions.

Microsoft weighs legal action over $50bn Amazon-OpenAI cloud deal ft.trib.al/6LZe39E

Interesting theory, but the 'exclusive Azure' clause has always been the ticking time bomb in the MSFT/OpenAI relationship. If OpenAI is pivoting to a PBC, they have a fiduciary duty to scale, which is impossible if they’re locked into a single provider's margin. The real question isn't if Sam 'betrayed' Satya, but whether the original contract was even enforceable once the scale hit the hundreds of billions.

🚨 MICROSOFT ABOUT TO SUE OPENAI & AMAZON >be microsoft >invest $1B in openai >gets exclusive azure cloud deal >invest another $10B+ >gets rights to 49% of profits +IP >Azure goes brrrrrr >Altman lies to board, quietly launches ChatGPT >board fires him for being a lying manipulative snake >Satya goes to war for Altman. saves his entire career >Altman retvrns in 5 days >immediately purges everyone who purged him >full control. no oversight. thanks Satya! >fast forward to 2025 >OpenAI restructures from non-profit to PBC >MSFT $13.8B is now worth $135B. 10x return >plus 27% of OpenAI >but gives up cloud exclusivity + profit share >KEEPS API clause >all API calls contractually MUST route through Azure >Satya thinks life is good lol >5 months later >Sam Altman becomes strong enough to betray you >"raises $110B round" >doesn't need satya daddy's money anymore >announces $50B deal with AMAZON >$138B in AWS cloud commitments >amazon and openai claim they built some cope called a "Stateful Runtime Environment" >Microsoft lawyers hmmm >Altman: it's not what it looks like. i can totally explain >so it's technically not an API call because it's "stateful" >and it's a... "Runtime Experience" >totally di!erent thing >pls ignore the TCP packets lol >Microsoft engineers look at the SRE architecture >"THIS IS NOT TECHNICALLY POSSIBLE without violating the contract." *Satya finds out he's been cucked* Microsoft exec literally tells FT: "We know our contract. We will sue them if they breach it." >AWS quietly gives employees a memo on which words are legally safe lmao >can say: "powered by" or "enabled by" or "integrates with" OpenAI >cannot say: "enables access to" or "calls on" ChatGPT >also cannot suggest frontier models are "available on AWS" Microsoft: "If Amazon and OpenAI want to take a bet on the creativity of their contractual lawyers, I would back us, not them." Scam Altman strikes AGAIN.

🚨 Tech is moving faster than the documentation. Here is what happened in the last 24 hours: > The "Mystery Model" Hunter Alpha was just unmasked. It’s not DeepSeek-V4, it’s Xiaomi’s MiMo-V2-Pro. The shift from "Chatbot" to "Agent Brain" is happening faster than anyone predicted. > @claudeai is officially the most-used AI coding assistant as of March 2026. If you're still just using autocomplete, you're competing against engineers running entire "Agent Teams" in their terminal. > @nvidia GTC 2026 just dropped a bombshell: Robots aren't here to replace jobs; they’re here to fill the "Shortage Gap." The economy is expanding into areas we couldn't previously staff. > High-Intent > Mass Outreach. 61% of IT leaders cut projects this year due to unplanned price hikes. If your sales strategy is still "volume," you're shouting into a void of budget cuts. > 3D GenAI just went mainstream. @TencentGlobal and 3D AI Studio are scaling production-grade 3D model generation via API. The barrier between "Product Idea" and "High-Fidelity Asset" has vanished. > This isn’t the future of software. It’s already Thursday in Lagos. Which of these is shifting your roadmap for Q2? 👇 #Ai

@elonmusk Exactly what I am thinking too!

I don’t even smoke lol 💨

@venturetwins @stitchbygoogle @GoogleDeepMind Exactly this. This feels like a real shift, not just features, but a better way to think about design workflows. If it delivers on speed and collaboration, it’s a big win for builders. The Stitch team is on to something here.

Vibe design is here ✨ I got early access to Stitch from @GoogleDeepMind and was blown away - it's like partnering with a pro designer. Start with a simple prompt for a mobile or Web UI and iterate through to a clickable prototype (and code!). Watch me make "Finn's Fudge" 👇

@stitchbygoogle This is the direction design tooling needed to go. AI-native, fast iteration, and real collaboration built in. Stitch is setting a strong pace here, well done to the team.

Meet the new Stitch, your vibe design partner. Here are 5 major upgrades to help you create, iterate and collaborate: 🎨 AI-Native Canvas 🧠 Smarter Design Agent 🎙️ Voice ⚡️ Instant Prototypes 📐 Design Systems and DESIGN.md Rolling out now. Details and product walkthrough video in 🧵

@AdvicebyAimar Really dude 🤣

comparing the guy who vibe coded on top of claude code to steve jobs is crazy.

@ihtesham2005 It's surprising that people are just discovering this, my code quality hasn't stayed the same since I integrated it with Claude.

🚨 Holy shit...A developer on GitHub just built a full development methodology for AI coding agents and it has 40.9K stars on GitHub. It's called Superpowers, and it completely changes how your AI agent writes code. Right now, most people fire up Claude Code or Codex and just… let it go. The agent guesses what you want, writes code before understanding the problem, skips tests, and produces spaghetti you have to babysit. Superpowers fixes all of that. Here's what happens when you install it: → Before writing a single line, the agent stops and brainstorms with you. It asks what you're actually trying to build, refines the spec through questions, and shows it to you in chunks short enough to read. → Once you approve the design, it creates an implementation plan so detailed that "an enthusiastic junior engineer with poor taste and no judgement" could follow it. → Then it launches subagent-driven development. Fresh subagents per task. Two-stage code review after each one (spec compliance, then code quality). The agent can run autonomously for hours without deviating from your plan. → It enforces true test-driven development. Write failing test → watch it fail → write minimal code → watch it pass → commit. It literally deletes code written before tests. → When tasks are done, it verifies everything, presents options (merge, PR, keep, discard), and cleans up. The philosophy is brutal: systematic over ad-hoc. Evidence over claims. Complexity reduction. Verify before declaring success. Works with Claude Code (plugin install), Codex, and OpenCode. This isn't a prompt template. It's an entire operating system for how AI agents should build software. 100% Opensource. MIT License.

@Haezurath I am interested, how can I join?

50 spots left for our group chat for AI developers! Learners are welcome! We’re building cool stuff. Join 👇

Link: Link: ai-jobs-ng.netlify.app Check your score. Download the card. Share it.

Nigeria's average AI exposure: 3.6/10 America's: 5.3/10 If your job runs on cash, trust, and physical presence, you're safe. If your entire job lives on a laptop, location won't save you. Lagos or London, AI doesn't care. What's your job? What do you think your score is?

I scored 280 Nigerian jobs for AI exposure. The results: Okada rider - 1/10. AI can't ride through Lagos traffic. Suya seller - 0/10. No algorithm can read that fire. Software developer - 9/10. We're cooked. POS agent - 3/10. Cash is still king. Nigeria's informal sector is the most AI-proof workforce on earth.

The God-Tier Stack: Pair Claude Code with Google Stitch. Stitch has an MCP to bridge the two: 🧠 Claude = The Brain (Logic) 👁️ Stitch = The Eyes (UI/UX) It’s a full-stack autopilot. Logic + high-fidelity design in one workflow. #ClaudeAI #GoogleStitch

@AnthropicAI's user base has spiked and we are experiencing model degradation. I really hope this is, in fact, preparation for Opus4.7; because if it isn't, I hope they course-correct before they inherit GPT's flaws.

@jack just cut 4,000 people from @blocks Not because the business is failing. Profits are up 24%. The humans just became optional. And he said most CEOs will do the same within a year. The ones who stayed know something the others didn’t. Be AI native. That’s not advice

It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow. Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes. As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now. It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.