AI tips and tricks

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For developers working with AI in advertising, this document could be a valuable resource. It addresses common questions about using Claude Code and Codex, which are tools that can enhance ad creative processes. Understanding frequently asked questions can help you troubleshoot issues more efficiently and leverage these tools to their full potential. If you're involved in ad creative work, consider reviewing this document to streamline your workflow and improve your output.

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This release is significant for developers looking to implement AI-driven automation at scale. By structuring bots into a chief and specialist teams, you can streamline operations and maintain continuous workflows without manual intervention. If you're building AI solutions, consider how this model could optimize your current processes, particularly in areas requiring high reliability and efficiency.

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15-25 agents covering most of what used to be one engineer's week. The detail worth stealing isn't the count, it's the chief-of-staff agent managing the rest — that orchestration layer is the part most people skip. Start with two agents and a third that checks their work.

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Latency is the whole product here. The games work because the model answers fast enough that you never wait between choices. Slow model, no game. If you've been hunting for a weekend build that isn't another chatbot, this is it.

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This is a big deal for anyone building AI agents. The key insight: ditching vector search for agentic retrieval was the single biggest unlock. No embeddings, no vector DB - just agents reasoning over structured knowledge. If you're building agents that need to remember things across sessions, bookmark this. The code is being open-sourced.

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Drop these .md files into .claude/commands/, set your Meta access token, type /bleed-check — it just runs. 10 skills that automate ~25 hours/week of Meta Ads work. The bleed-check skill alone (finding ad sets burning cash with zero conversions) pays for itself in a day. This is what production Claude Code skills look like.

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The numbers here are wild but believable. 250% lead conversion lift, 3x pipeline, 40 hrs/month saved per rep. The key: these aren't chatbots answering questions. They're internal AI systems doing account research, analyzing outreach history, and drafting emails. The compounding effect of AI agents on GTM is just beginning.

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This is the article I wish every CEO would read before saying "we deployed AI." One layer is a demo. Production is an onion. Every real system I've built required multiple layers — context, guardrails, feedback loops, human escalation. If your AI breaks after week one, you're still on layer one.

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Jesse runs multiple companies and his team tested every major AI tool. His verdict: Cowork is the one that sticks. That tracks with what I see in the Bootcamp — the people who switch from Chat to Cowork have a "holy shit" moment when they realize what persistent context actually means for their workflow.

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Skill files are the secret weapon most Claude Code users never discover. This resource walks you through the iterative process — write, test, refine, repeat. The key insight: your expertise is the baseline. The skill file just makes it repeatable at scale. Grab this and build your first skill today.

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This is the definitive post on Claude Code skills, straight from the team that builds them. The biggest revelation: skills aren't just prompts in markdown. They're folders with scripts, hooks, and configuration. Anthropic runs hundreds of them internally. If you're still treating skills as fancy prompts, you're missing the entire point.

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Send this to anyone who asks "what are AI agents?" Greg breaks down the entire stack in plain English — no jargon, no fluff. The key takeaway: context beats prompts. Stop writing perfect prompts. Load your agent with context about your business and simple instructions work. That's exactly what we teach.

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Level 1 is where 90% of marketers stay forever: typing into ChatGPT and getting generic output. The jump from Level 1 to Level 3 (custom context + skill files) is where the real leverage happens. If you're still prompting from scratch every time, you're leaving 10x productivity on the table.

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One prompt. Full OWASP security sweep. Reports in descending severity with suggested fixes. Arvid runs this in plan mode so Claude maps the attack surface before executing. If you're shipping production code without running this, you're rolling the dice. Copy this prompt. Run it today.

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Steal from the best. This curated library has high-performing B2B ads with breakdowns of why they work. Feed these into Claude Code with a bulk-creative skill and you've got an infinite ad variation machine built on proven patterns. Bookmark adfolio.design.

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The legacy GTM stack is dying. Salesforce, ZoomInfo, Outreach, Marketo — all being replaced by AI-native tools that capture data automatically, surface real-time signals, and create collaborative deal spaces. If you're still manually logging activities in a CRM, you're already behind. The new stack: Clay, Common Room, Pocus, Attio.

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This is the future of marketing tools. Instead of a SaaS dashboard, your marketing frameworks live inside Claude via MCP. Strategy development, homepage reviews, campaign briefs — all powered by proven B2B templates that Claude can reason over. The MCP server approach means your frameworks get smarter as Claude does.

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Forget stage progression. Focus on milestones. Discovery calls = 3.2x win lift. Executive sponsor = 1.9x. Articulated use case = 2x. These aren't coaching tips — they're structural requirements. If your sales process doesn't enforce these milestones, you're leaving wins on the table. Build these into your CRM as gates, not suggestions.

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Stop guessing which accounts will churn. Four signals, all already in your data: seat utilization (85% = capacity), feature adoption (60 days without core features = red flag), org spread (single-team = fragile), usage velocity (40%+ spikes = expansion opportunity). Build an AI agent to monitor these weekly and you've automated your CS team's early warning system.

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Five skills that turn Claude into a demand gen machine. Campaign briefs, content offers, lead scoring models, landing page wireframes, webinar promo plans — all the repetitive strategic work that eats your week. The template-driven approach is smart: your expertise becomes the template, Claude handles the execution.

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This is the "AI replaced my intern" moment for DTC brands. One prompt → scrapes TikTok, finds creators in your niche, researches their content, writes personalized DMs that reference their actual videos. If you're still scrolling TikTok manually and DMing creators one by one, this agent eliminates that entire loop.

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This is the video that makes GTM engineers sweat. Cody shows the exact loop: bulk Facebook ad uploads, negative keyword analysis for Google Ads, landing page generation from winning creatives. The hours of keyboard work between strategy and results? Claude Code eats it. If you run paid ads, watch this.

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The smartest GTM automation isn't fully automated — it's human-in-the-loop. Everett nails the balance: AI handles CRM updates, event gathering, signal-triggered emails, pre/post-call prep. Humans make the judgment calls. Slack as the coordination layer is genius because that's where your team already lives. Start here before going full autonomous.

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This is galaxy brain stuff. Instead of giving every developer a $3,000 laptop, put Claude Code on a $7 VPS and let the whole team access it from phones, tablets, anything. Then he layers a cold outreach system on top that books 63 calls/month. From local dev prison to collaborative AI team for $7/month. The math is insane.

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400 sessions in 7 weeks. This guy stress-tested Cowork harder than most people use it in a year. The biggest insight: the gap between casual and power users has nothing to do with prompting. It's about setup and structure. Context architecture (practices 1-5) is where you get the 100x. Bookmark this.

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This is demand data, not opinions. 1,804 people downloaded an email assistant agent. Content planning, morning briefs, time management, weekly reviews — all workflow automation, not coding. This tells you exactly what to build first if you're creating AI agents for a business audience.

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Compound Engineering is the mindset shift that separates people who use AI as a spell-checker from people who 10x their output. Kieran walks through Every's guide on what beliefs to abandon (you need to write every line) and what to adopt (AI as a force multiplier). Essential viewing for anyone building with AI.

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This is one of the better comparisons I've seen. The TL;DR: Cursor is great if you want a visual IDE. Claude Code is unmatched for complex, multi-file projects. We wrote our own take at masteringai.io/claude-code-vs-cursor.

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Fireship makes complex topics click in minutes. If you've been confused about what AI agents actually are vs. the hype, start here. Then come build one with us in the Bootcamp.

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Alex nails it — Cowork is Claude Code for your entire life. Not just coding. Email, research, operations, content, analysis. The workflow he outlines is dead simple and saves real hours. If you've been intimidated by Claude Code's terminal interface, Cowork is your on-ramp.

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Plan Mode is the single most underused feature in Claude Code. Most people jump straight into building - but spending 5 minutes in Plan Mode saves you hours of rework. I use it on every project now.

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Pieter has been proving this thesis for years, but it's different now. The tools are so good that the gap between "technical" and "non-technical" is closing fast. If you're still waiting for a co-founder, you're wasting time.