pankaj

@AiroPrompts This is the real shift. As connectivity improves, competitive advantage moves toward: → data quality → structure → context depth Clean systems are becoming incredibly valuable.

Clean data + MCP = AI on steroids With MCP becoming the standard for AI connectivity, data is about to become the most valuable asset you own. The companies with clean, organized, proprietary data will have AI that’s smarter than anyone running on generic public information. Before MCP - AI was only as good as its training. After MCP - AI is as good as the data you connect to it. Start organizing your data. Seriously. And there’s a lot of opportunities for those who start building in 2026 🧡

I trained Claude on 10,000 top 1% LinkedIn scripts. Here's the exact 3-step sequence it now runs. One skill. Three messages. All signal-based. Step 1 : Signal Detection Claude reads- name, company, LinkedIn activity, hiring signals, funding data. Picks ONE active signal. A new VP Sales. A funding round. An SDR job posting. If there's no strong signal, it doesn't fake one. Step 2 : Observation, not pitch First message sounds like conference talk - "Saw you're hiring 3 SDRs while building the APAC team. Curious how inbound is holding up." No links. No offer. No calendar. Step 3 : Value offer Follow-up turns the signal into a free win → A sample lead list based on their ICP → A signal report for their segment → A competitive outreach breakdown Something where the natural reply is "sure, send it." Trained on 100+ live campaigns. Every bad script became a rule to avoid. Comment SCRIPTS and I'll send you: → The skill file → The scripting framework → 6 signal-specific templates for Claude

This changes the abstraction layer completely. We’re moving from: → writing code manually to → orchestrating systems that generate, test, and refine code autonomously. The leverage won’t come from typing faster anymore. It’ll come from giving better direction, constraints, and workflows.

Grok Build is coming. Not autocomplete… a full coding agent. You describe it. Grok plans, codes, and debugs. Up to 8 agents run in parallel. Apps, sites, full repos. Built from plain English. Arena Mode picks the best output. The local CLI keeps your code private. This isn’t “help me code.” It just builds. @xAI @grok

@naturedotcom Systems thinking. AI is powerful at execution, but people who can combine: → context → judgment → communication → decision-making will stay incredibly valuable in the AI era.

What skill beats AI?

They said AI would take your job. It took the boring parts first.

@sumitrunsai High-quality data infrastructure AI-powered personalization workflows A repeatable outbound system With those 3, you can rebuild pipeline surprisingly fast.

Simple question for your weekend: If your entire GTM motion disappeared tomorrow and you could only rebuild with 3 things What are the 3? Drop them below.

@sukh_saroy This is the real AI leverage layer. The winners won’t be the people using the most tools they’ll be the ones building the best workflows between them. AI + automation + clean systems is becoming a serious competitive advantage.

10/ AI Automation Zapier + Make + n8n + AI = your personal army. Email triage. Lead qualification. Customer support. Content scheduling. Invoice processing. Meeting summaries. Every repetitive task in your job is automatable in 2026. The people who automate first get promoted. The ones who don't get replaced.

"using ChatGPT" is not an AI skill. In 2026, it's the bare minimum. Here are 12 AI skills that will decide who eats and who gets replaced 👇

Week in review as a builder: Things that worked: 2 Things that broke: 7 Things I learned: probably 9 The ratio isn't great. But learning compounds faster than wins do. Building in public would be terrifying if I took the losses personally. I stopped doing that in week 3. What's one thing that broke this week but taught you something you'll use for the next 6 months?

@bentossell That’s not a question anymore. That’s the beginning of an AI onboarding sequence

wife just asked if i've heard of claude

@Akasheth_ This is the right order. Learn just enough theory to build, then let projects expose what you actually need to learn next. AI rewards builders way more than passive learners.

If I had to learn AI from scratch in 2026 I would not start with complex math or research papers. I would follow this roadmap: > learn Python basics (variables, loops, functions, APIs) > learn how LLMs work (tokens, context window, prompts, embeddings) > build simple AI apps (chatbot, PDF summarizer, content generator) > learn RAG (chunking, vector DBs, retrieval, ranking) > learn AI agents (tools, memory, planning, workflows) > learn MCP (connect AI with real apps and data sources) > learn deployment (vercel, supabase, docker, monitoring) > learn evals (test outputs, measure quality, reduce hallucinations) build small projects every week that’s how you actually learn AI.

@stylishamrit @AnthropicAI @SpaceX @claudeai Exactly. Everyone chases the shiny model updates but infrastructure is the actual moat. Pipelines > hype cycles

@systems_pankaj @AnthropicAI @SpaceX @claudeai Everyone's racing to build AI products but nobody talks about who's actually solving the compute layer. Anthropic just did. Quietly the most important partnership of the year.

@AnthropicAI just partnered with @SpaceX for more compute. So @claudeai is now technically powered by rocket fuel.🚀 Jokes aside, this is what solving the compute problem at the source actually looks like. Not renting capacity. Not waiting in queue. Building the supply chain. And for people building AI GTM systems on Claude, this is actually huge. More capacity = fewer bottlenecks mid-workflow. If you're running Clay + n8n + Claude at scale, you've felt the limits. That ceiling just got raised. Are you building your outbound on Claude yet or still doing it manually?

@sumitrunsai @AnthropicAI @SpaceX @claudeai This!! 2am broken workflows hit different.. You already know the pain ! now imagine that same stack running without a ceiling. Rebuild season incoming 🔧

@systems_pankaj @AnthropicAI @SpaceX @claudeai Built Clay + n8n + Claude workflows that died mid-sequence because of compute limits. This partnership is literally fixing the exact thing that broke my automations at 2am. Infrastructure > features, always.

@xai @AnthropicAI We’re entering the era where AI labs think like infrastructure companies, not just software companies.

SpaceXAI and @AnthropicAI have also expressed interest in partnering to develop multiple gigawatts of orbital AI compute capacity

SpaceXAI will provide @AnthropicAI with access to Colossus 1, one of the world’s largest and fastest-deployed AI supercomputers, to provide additional capacity for Claude → x.ai/news/anthropic…

@SpockyMagicAI Yes that's the key !

@systems_pankaj The orchestration layer is where 90% of the complexity lives. Nobody talks about this.

The GTM market in 2026: Everyone's building AI agents. Nobody's talking to customers. The builders who win aren't the ones with the most automation. They're the ones who used automation to create space for actual human judgment. Tools are leverage. Not a replacement for thinking. What's one thing you've stopped automating because it needed a human?

@ayushagarwal This is why review systems matter. AI can generate fast, but: → validation → context checks → real-world alignment still sit with the operator. The edge isn’t just generation,it’s how fast you can refine and correct.

AI is incredible at generating first drafts. it is terrible at knowing when the first draft is wrong. that's still your job.

@dramaricic Senior dev… minus the coffee breaks and Slack pings but still needs a good PM to guide it

Is Opus 4.7 equivalent to senior developer?

@sumitrunsai The teams that improve fastest are the ones that: → capture loss reasons consistently → make it visible weekly → actually reuse the insights in messaging Simple loop, big compounding effect.

Your GTM has a memory problem. Every quarter, you rebuild context that already existed: → Why you lost deals → Which accounts went cold and why → What messaging actually moved the needle The fix: a simple loss analysis doc shared weekly. Not a CRM field. A human-readable doc. What does your team do with lost deal learnings?

Built a messy n8n workflow so I never had to send 300 emails manually again.